Hi! We're HIGS, welcome to our page! You'll find our latest projects, project topics, and any helpful info here. Just go through our recently completed projects picked from over 9000 successful research works. Get inspired to craft your research work to reflect your refined requirements. HIGS has achieved numerous milestones by contributing to various PhD research services such as in Thesis, proposal, research paper, review paper writing, and also in implementation especially in Java, Matlab, Matlab Simulink, Python,Python Spyder,Python Anaconda, Python PyCharm, and more. We also engaged in paper publication under the journals SCI, Scopus, IEEE, UGC, Q-ranked, Annexure 1 & 2,and more. We have a dedicated team to help get your project off the ground and reach your goals. Our superior aim is to reduce the stress of PhD aspirants while doing their PhD research projects. We establish creativity, novelty, and originality in each of your works. We undergo project construction with the help of only well-trained and highly experienced research mentors. We are your end-to-end research partners fulfilling all your research needs. You can have free add-ons along with your service such as free technical discussions, free Turnitin plagiarism reports, free citations, free demo sessions, and more. We help you from the beginning of your research to the end that is we will be with you from the admission process to PhD viva process. You can reach us for any kind of assistance. We are having highly experienced and well qualified programmers to help you in this way. We give endless benefits and advantages to our clients for their first & frequent orders. Here, you pick your favourite topic or domain and start doing your dream research. You can have a year full of assistance from any corner of the world through calls, emails, chat, and any of the convenient modes. Get a stress-free, and affordable research services for all your PhD needs. You can dial +918681018401 and send us mail through phdguidance@higssoftware.com.
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The method of conducting Human Resurce Management (HRM) evaluation & analysis has become an essential research direction. This research paper depends on the multi-mode fuzzy logic control algorithm that assesses the comprehensive level of the employee’s ability. Fuzzy sets and other methods to improve work efficiency, trying to assess the effective support of enterprise HRM.
This paper introduced the BP- NNC Algorithm. By using the BP- NNC method, enterprise network marketing is performed. At last, the actual enterprise network marketing assessment is performed based on the particular calculation of an index. The outcome of the simulation experiment exhibits a 0.435 estimated value of 0.096 standard deviation and 4.545 Z-value of the BP- NNC algorithm.
The analysis of the family investment behavior of Dongguan City plays an important role in Dongguan's economic society. In the future, it will be an essential factor affecting the development of the Dongguan investment market, local economic operation, and improvements in people’s lives and family wealth. In this regard, the paper chooses Dongguan family investment behavior for analysis.
Domestic generators will help consumers handle both schedules & unplanned power cuts. The digital generators can run at variable speeds. This research work is an outcome of 120 consumers from Faisalabad who utilize digital generators. This work will help the higher management of heavy electrical industries in establishing steps where consumers get excited about their manufactured products.
We believe this is a time to take research on strategic management in India. Our research finds ‘3’ dominant themes. They are: (i) Impact of the environment on firms, (ii) Strategies (iii) different ownership structures of firms. We discuss the key findings. Theories and methods that scholars have used to address questions. We end this by identifying important areas of research and urging strategy scholars to engage with the opportunities provided by the business environment.
Lately, industries have been involved in improving their effectiveness through financial, ecological, and societal dimensions. The objective of this research is to map a structure that helps organizations in assessing their sustainability. To achieve this goal, a publication approach is utilized by emphasizing 22 articles of Scopus-indexed publications. Results showed that this research mainly defines the importance of reliable data and suitable methodological strategies.
In this article, we have taken various types of phishing attacks & detection methods. Phishing is one of the main issues and there is no permanent solution to mitigate the susceptibility. In this research, we have mentioned different types of mitigation methods for phishing websites like detection, correction, prevention, and offensive defense.
Lately, the method of in-depth learning has made huge accomplishments in the field of medicine. This research has reviewed and analyzed the benefits of deep learning in the diagnosis and prognosis detection of ovarian tumors. This research has also explored the application value and research prospects of deep learning in the diagnosis and treatment of ovarian cancer.
Our work aims to develop an Auto-speech recognition system for English Lectures. In this research, we employ the DNN-HMM-based speech recognition system, we accomplished an 88% word accuracy to recognize TED lecture speeches. Likewise, speech summarization has proved the robustness to speech recognition errors. It is also the same in the summarization of text process.
This paper involves in collecting data on the damage to the traffic system caused by earthquakes in China in the past ‘2’ decades. It mainly uses the KNN algorithm, SVM algorithm, Logistic regression algorithm, Naive Bayes Algorithm, and Decision Tree Algorithm for training the data and establishing earthquake prediction models. The prediction accuracy is relatively exact and it is very useful to predict earthquakes and rescue operations.
In order to get the essential information concealed inside traditional Chinese medicine, the development and intellectual qualities of traditional Chinese medicine are examined. The analysis offers sources for scientific research so that researchers can identify the areas of effective integration, investigate the potential of traditional Chinese medicine from a scientific standpoint or view, and keep developing technology to support Chinese medicine.
The World Economic Forum regularly ranks addressing complex problems as one of the top "10" abilities that companies value in graduates in 2015, 2020, and 2025. This study assessed the perception of complex engineering problems among capstone design students. The conclusion of this study is expected to be beneficial to students and teachers, as it provides ideas for addressing complex engineering problems.
The science of using living things to improve both the environment and human existence is known as Biotechnology (Technology based on Biology). The field of biotechnology has grown rapidly in recent years. This research study uses bibliometric approaches to investigate Medical Decision Making and Biotechnology through scientific mapping. It is involved in investigating the productivity of science and contrasting significant factors.
During the COVID-19, educational institutions were closed. Teachers needed substitute sources for lab work. This study assessed ‘2’ devices for the Microbiology. The 1st tool is Virtual BioLabs to manage specialized lab equipment. The 2nd is Virtual Journey, an interactive 360-degree film explaining a bacterial foodborne illness. We used qualitative and quantitative evaluation to measure the impact of these tools during the pandemic.
In recent years, many professionals and scholars have also become interested in computer science and technology applications in other sectors. Additionally, this research paper discusses the challenges that have arisen as computer science and technology have grown in importance and features. At the same time, this research paper discusses computer science and technology application principles, development approaches, and development strategies.
This paper investigates the potential of incorporating deep learning techniques into English language and linguistic teaching strategies. The objective of this study is to examine the possible advantages, difficulties, and methods for implementing deep learning in English language and linguistic education. This research studies evaluates and offers guidance on how to use deep learning to improve the efficacy of language instruction.
AI aids in modeling and replicating the human brain. To identify relevant research, and the scope of study in cognitive science and AI, this work makes use of the VOS. The top 5 countries with the most publications are the US, UK, China, and Germany. This will work as a guide for upcoming researchers in AI and cognitive science theory.
The world became a catastrophic pandemic due to the new COVID-19. Humans were rapidly infected by this virus. As a result, to get out of this pandemic condition, preventive actions were crucial. A thorough analysis of COVID-19 is given in this paper, covering a number of significant and connected topics that will aid readers in comprehending the virus and conducting additional studies.
The parity check algorithm in the human anatomy is used in this work. It uses the points in the closed curve. It was observed that there was a statistically significant difference in the satisfaction rate of teaching methods. It resulted that the control group had a relatively low satisfaction rate, whereas the observation group 1 and 2 had higher satisfaction rates.
The use of machine learning in the diagnosis of cancer. We provide several attributes for three cancer systems that require data entry from the user to produce a result. Considerations for lung cancer include smoking, anxiety, pressure, etc. Radius, texture, perimeter, and area, are considered when diagnosing cancer, and the outcome for both types of cancer is the chance of developing the disease.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
This standard extends in IEEE Std 1872-2015. This standard can be applied in a multitude of ways, such as defining the domain knowledge required to clearly describe the design patterns of AuR systems, unifying the representation of AuR system architectures, or serving as a guide for the development of autonomous systems made up of robots that operate in diverse environments.
A new class of mRNA has been introduced to medicine for producing a vaccine against SARS-CoV-2. This paper presents a four-module COVID-19 RNA-based vaccine: neural codon optimization, interaction box, mRNA-based vaccine design, and SARS-CoV-2 profile. The results demonstrate that the vaccination offers strong protection against viral alterations. The vaccine still offered 78% protection.
Raising fish in a pond is called Pisciculture. Farmers today have to test a variety of water characteristics, including temperature, turbidity, and pH. They will Manually test the samples under the current method. Through an Android app, our application will enable the farmer to remotely monitor the parameters. If the values depart from the threshold value, the farmer will receive an alert.
Construction has grown considerably in importance to the growth of the economy. Building construction projects have high requirements for the application of building information modeling. To offer ideas for the application of BIM in housing construction project management, the article examines how it is used in each stage of the project and how to choose and apply it. It also suggests development measures.
Mobile Communication Technology is a developing technology. We used the advancement of mobile communication technology as a study subject. Beginning with the areas in which mobile communication technology is applied, this article describes the process of mobile communication technology. Here, we explained the potential practical application and its underlying principles.
Information technology has made use of Java. Java virtual machine provides the foundation for the development of Kotlin. Here, we analyze the performances in Kotlin and Java based on this ecosystem implementation. (1): we assess how the loop function performs. (2): we discuss the reason for these performance declines. (3): discuss a method for improving the performance. Finally, we assess the performance-improving approach.
This research paper shows you how to use a functionally driven approach to Python coding to take a modest project and build it out. This research study mainly explains about the distributed technologies that enable high data throughput techniques and built-in Python tools. This practical tutorial's hands-on exercises will solidify these fundamental abilities of research for any ambitious data science project.
A simulating MATLAB system model in the PSpice environment is presented. An algorithmic element is created and exported to a C-model. This research paper provides a detailed description of the modifications needed to bring the MATLAB C-Model into compliance with PSpice device modeling specifications. Once circuit simulations using PSpice are signed off, the algorithmic module can be targeted to FPGA, and PCB for implementation.
Small and medium-sized businesses have a significant role in China. The growth of small and medium-sized businesses has the potential to propel regional development. However, COVID-19 had a bigger effect on international e-commerce enterprises in Dongguan. The growth of small and medium-sized businesses has the potential to propel regional development. However, COVID-19 had a bigger effect on international e-commerce enterprises in Dongguan.
It is notch signaling that causes adjacent cells to differentiate into various states. We use a realistic epithelial layer cell model. We found that, in the early stages of embryogenesis, smaller cells have a higher probability of becoming signal-generating cells because cell signaling intensity is inversely related to cell area. Our research emphasizes how cell morphology affects the stochastic cell destiny decision-making process.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
Numerous methodological advancements in brain imaging genetics can be attributed to initiatives like the UK Biobank, Neuroimaging Initiative, and Alzheimer's Disease Sequencing Project. We discuss fundamental concepts, statistical and machine learning methods, and innovative applications. We demonstrate how the extensive availability of genomics data related to brain imaging from multiple biobanks and developments in biomedical computers, and statistics.
Oyster mushroom is one type of mushroom that is commonly used in Indonesian. This study details the creation of a prototype fuzzy logic controller-based temperature and humidity management system for oyster mushroom farming. The Arduino microcontroller has a fuzzy logic controller installed to generate the temperature and humidity setpoints. The time response to reach the setpoint spans from 1 minute 27 seconds to 8 minutes 10 seconds.
In the Philippines, agriculture is extremely important. Mango production in the Philippines is ranked 7th in the world. The main objective of this project is to develop an electronic nose can differentiate between ripe and unripe Mangifera Indica. A mango's ripeness can be determined via the Fuzzy Logic Algorithm. Unripe mangoes were identified with an accuracy of 93.33%, whereas ripe mangoes were identified with 86.67%. The system's total accuracy is 90%.
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It was investigated to use the Na 3 NiZr(PO 4) 3 superionic conductor-type as an anode for SIBs. the structural and electrochemical properties of this phosphate were investigated using XRD, SEM, and electrochemical testing. An initial discharge energy of 140 mAh/g is provided by Na 3 NiZr(PO 4) 3 /C in a sodium half-cell at a density of 25 mA/g. Even at high-density rates from 25 to 500 mA/g, good capacity retention was maintained.
Outgassing is an unavoidable problem, particularly when using photoresist masks for high-energy ion implantation. Two factors influence the ion beam under the outgassing. The first is the charge exchange brought about by ions interacting with molecules or atoms that are exhaling. The other is nuclei in the outgassing molecules or atoms scattering ions. After assessing the impact of the second event, we discovered that the ion beam's scattering angle is substantially smaller than the Si <;100> channeling critical angle.
Technology and art are combined to create graphic design. As society and the times evolved, computer graphic design software was integrated with various forms of graphic design. This article first examined the idea of computer graphic design software, then it introduced the idea and the condition of graphic design today before examining how computer graphic design software is used in graphic design.
Daihai is the third-largest lake in Mongolia. In response to the ongoing water level drop, this paper examines the interannual water level of the lake from 1960 - 2019. This study employs the water balance model to calculate the average multi-year water deficit in Lake by examining changes in inflows & outflows from 2010- 2019. The results say that the theoretical foundation is grounded in science for Daihai Lake's sustainable development.
Fuel loads in Longleaf Pine forest ecosystems have been mapped using lidar. This study aimed to evaluate how well the ALS and TLS, and their combination, could forecast CBD in the ecosystem of a longleaf pine forest. This study aimed to assess the utility of ALS and TLS and combination in predicting CBD. Tree attributes, such as tree height, crown width, height, and diameter at breast height in three plots of ~ 0.19 were measured and calculated.
Terrorism is a major threat to the world. Based on the GTD database, with big data, this paper optimizes the GTD-related data of terrorist attacks by mathematical methods. They are hierarchical, fuzzy clustering, and regression analysis. The values are calculated, values are sorted. The similarity coefficient, the suspicion degree of terrorists about events is determined, thus the counter-terrorism is effectively predicted.
This paper presents results on differentiation between healthy wheat plants and plants infected with Fusarium Head Blight. The CMUT sensor array is functionalized with organic/inorganic materials to capture disease-related volatile signals. Experimental results demonstrate the effectiveness of the proposed approach in achieving high accuracy for plant disease detection at the end of the 11th day after plant inoculation.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
Digitally stimulating one or more sensory systems is the fundamental concept of an XR application of the human user in an interactive way to achieve an immersive experience. Virtual Environments is a growingly popular usage of XR technology for animals. We offer this review as evidence for our claim, which summarizes animal behavior studies carried out in virtual settings.
As the biological environment has improved, transmission line breakdowns brought on by bird activity have become more frequent, particularly in the spring, and are now one of the biggest risks to the operational safety of transmission lines. In this paper, a variable-angle anti-bird cage is designed to effectively remove the error gap between the device and the tower on the side.
An alternative for fiber sensors based on lossy mode resonance (LMR) is a planar waveguide design. This study compares the performance of three biosensors that are manufactured with and without a SiO 2 intermediary layer to detect anti-IgG. The biosensor used an intermediate layer and placed the LMR in the visible range. This displays the lowest possible limit of detection of 0.02μg/ml.
By using visual image analysis, the surgical instrument robot can accomplish the delivery and classification management of surgical instruments. In this work, we suggest a system for segmenting surgical instruments based on the enhanced MobilenetV2 network. According to the results of the experiment, the improved network's MIoU, PA, and fps values on the surgical instrument dataset are 24.8, 0.885, and 0.861, respectively.
The paper discusses the need for IT specialists, and informatics teachers, to learn about dynamic mathematics software. The authors raise the issue of teachers, students of specialty 014 Secondary education, and 122 IT. It is observed that these abilities happens when utilizing dynamic mathematics software to write a lesson fragment. It demonstrates the dynamic of qualitative shifts in the lab.
This article discusses the difficulties in generating Key Delivery Messages (KDMs) in the digital cinema sector. This paper explains the concepts of encrypted Digital Cinema Packages, Trusted Device List, and Digital Certificates. The suggested platform is a effective solution that may be used in real situations and act as a model for other sectors of society that are dealing with related issues.
We discuss a toy model that makes it possible to derive important truths about thermodynamics. We reproduce the possibility of negative temperatures, the notion of equilibrium as the coincidence of two notions of temperature, statistical versus structural, and the zeroth law of thermodynamics, which we find to be redundant, as other authors, yet at the same time not to be universally valid.
This study provides a comprehensive assessment and summary of the recently published research on the growth kinetics of intermetallic compounds (IMC) in solder joints under temperature cycling in electronic packaging applications. There have only been a few diffusion studies on the isolated IMC morphology in the solid state, and few quick talks have been held in anticipation of more thorough research in the future.
Virtual reality, or VR, has been used in industries. The results of a VR-based Interactive Education System for construction hazards (VRIES) to support construction safety are presented in this study. The results demonstrated that knowledge and awareness of construction safety had improved following training with the suggested VRIES. The VRIES has the potential to improve construction safety, knowledge, and behavior to reduce accidents.
The basic stages of the nation's transport system and the growth of transportation services. The field of transport construction demonstrates the need for increased coordination and research development, as evidenced by the maintenance of normative equipment, the proper incorporation of building manufacturing norms and rules based on the accomplishments of related fields of knowledge, and the validated experience of completed building objects.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
We proposed wearing art as a fashion in daily life by fusing digital art with digital printing technologies. We set up a production setting and verified that art fashion could be made quickly. Taking advantage of the art fashion display, we distributed questionnaires to the audience asking them to rate the art outfits. The initial report of the questionnaire analysis is this publication.
Today, Global warming is one of the major issues. This study presents an architecture for the Green Warming Model (GWD) and describes how data engineering and analytics may be utilized to control global warming. Thus, the main contribution of this research project is the application of data engineering and machine learning (ML) to the preservation of the environment.
An overview of Turkey's Moon Research Program has been provided in this article. The National Space Program of Turkey was produced and released in 2022. Among the main subjects covered in the research were developing deep space technologies, planet exploration initiatives, and Moon missions. The Moon Research Program Project was started to make Türkiye one of the capable participants in the space race.
One method of doing this is by automatically extracting a few text passages from the given document and summarizing them. This proposed work does automatic text summarizing in Tamil language using a hybrid model that integrates sentiment, keyword, and text ranking scores. An average accuracy of roughly 0.81 for recall, 0.61 for precision, and 0.67 for F score is obtained when employing the suggested model.
Using natural language processing (NLP) and machine learning, this paper outlines the design and development of a computer-aided foreign language learning grammatical knowledge database for learning Japanese sentence patterns. This database can be viewed as an additional useful resource for learning Japanese grammar and an advancement in the efficacy of the already-existing intelligent computer-assisted Japanese language learning system.
Distributed photovoltaic market transactions will involve a growing number of players, including equipment suppliers, integrated energy firms, investors, and others due to the rapid growth of distributed solar power generating technology in China. It examines the core elements and organizational structure of diverse submarkets and leverages the demand features of the primary submarkets. Thus, it lays the groundwork for enhancing market service capabilities.
The general state of the technical field, development trends, and hotspots for industry technological innovation can all be found using analysis techniques based on large data sets from patents. In this research, we used the patents database to search the technical sector. To comprehend industry development trends and policy formulation, appropriate conclusions might serve as references for agencies and civil aviation units.
A thermal performance simulation of a solar central heat generating system for multifunctional applications is presented in this paper. Utilizing TRNSYS software, a theoretical model is created, and the Center for Solar Energy Research and Studies in Libya is going to host an experimental test rig. The simulation's findings indicate that the solar system can supply more than 90% of the energy.
The human immune system (HIS) is responsible for the defense of the organism against pathogens. In silico experiments are used to study mathematical models of HIS. Using these models, we examine the primary and secondary responses to the Yellow Fever virus (YFV). It was feasible to quantify the impact of model parameters and replicate aspects of antibody dynamics in a secondary reaction to the YFV.
Technology has impacted every aspect of our lives. Consequently, it has evolved into an essential teaching tool that parents are finding challenging to argue with their kids. Social media platforms can have positive or negative effects based on the user and their intentions, as well as the engagement and awareness of other users.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
Recently, questions concerning engineering students' ethical consciousness have been addressed. Using a mixed method research methodology, the study reviewed the curriculum and spoke with lecturers to identify the modules that included the teaching and evaluation of engineering ethics. It is advised, the results, to employ ethics across the curriculum approach, bolstered by a special engineering ethics module.
To maximize the marine information resources, we suggest researching the essential technologies for the collecting of information about the marine environment. To train the samples for the creation of a marine target recognition network, a lightweight target detection framework network model is chosen for the work. This network is then installed on intelligent terminal equipment to enable marine target detection and recognition.
Based on big data, this study creates a platform for gathering information about the connection between postpartum depression and social support in fetal women. Postpartum depression is comparatively common among mothers of second children. It is possible to improve the physical and emotional well-being of second-born mothers and foster family harmony by taking a closer look at how the maternal social support system affects postpartum depression.
Dempster-Shafer theory, a generalization of probability theory, performs better when handling ambiguous data. Evidence is given more weight when the majority of sources support it. Evidence with lower entropy has a stronger capacity to deliver reliable information. Experiments conducted on real data demonstrate that this method has a higher accuracy when compared to other methods and can address the combination problem of conflicting evidence.
Botany, agriculture, and environmental science all depend on the process of classifying plant species, which offers important insights into ecological systems, biodiversity, and agricultural methods. To make plant species categorization easier, this research offers the construction of Convolutional Neural Networks, a deep learning-based technique that extracts information from leaf photos. By using CNNs, it is easier to extract features from leaf photos, which increases efficiency and accuracy.
The music industry has grown from independent composers releasing their self-published work. We generated a collection of Hindi songs to illustrate this. We contrasted the outcomes of methods, including AdaBoost, Multi-layer Perceptron (MLP), Gaussian Naive Bayes, Random Forrest, and Logistic Regression enhanced with SGD. Based on the findings, MLP produced the greatest results, with an F1 score of 0.8849, recall of 0.8875, and precision of 0.9429.
China's economy is growing at a rapid pace. The study's findings can assist relevant traffic departments in keeping an eye on the tunnel's speed, which will lower the number of accidents that occur there. They can also serve as a strong deterrent, making drivers afraid to break the law, which will help to ensure the tunnel is operated and managed safely.
This research paper mainly focuses on the “Digital Educational Platforms” that can aid students in measuring basic power electronics converters in a remote method. The user can be connected through a remote method and view real-time oscilloscope waveforms, register operation parameters like voltage & currents, and change operation points such as Duty cycle, and frequency.
Imaging methods for the diagnosis of cancer include MRI, X-ray computed Tomography, Optical Imaging, Ultrasound, and PET method. Here, we have worked on Neutron Radiography to detect tumors from normal lung tissues at a spatial resolution of ≈100 μm. The neutron images of cancer cells were associated with the histology data. It can provide information about the structure of cancers in biospecimens.
Autonomous Robot Taxis are the future self-driven robots that can be operated on is own without the help of the driver. One of the major challenges is to change the existing form of cars into robot taxis. A brief analysis of the sensors used in the Autonomous Robot Taxis is explained in the architecture section. Hopefully, these vehicles will be in use globally in the future.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
Airplanes are one of the most common modes of transport by so many people. The aim of this study is to identify the rate & cause of the aircraft accident. Here, we examine the most occurred reason for eh airplane crash. The proposed methodology aims to form a prediction model by machine learning such as random forest and Bayesian classifications. The prediction range is 80-90%.
Real-time monitoring is needed to save endangered wildlife. To monitor wild animals, camera-trapping technology is highly used. The proposed work is simulated in the iFogSim simulator. It results that the proposed fog-based model successfully reduces latency and network usage compared to the traditional cloud-based model. The comparative study shows a significant improvement in the execution time over the cloud system.
Whales are the important marine mammal. In this work, we worked with experts in aquatic and fishery science to create WhaleVis. We illustrate key analysis tasks among whale researchers for this database. This research model facilitates the visual estimation of whale search efforts & spatial distribution of whale populations normalized by the search effort. We present the use of our dashboard with a real-life use case.
In this paper, we describe the orthogonalized version of the Oja algorithm. It can be used for a estimation of minor and principal subspaces of a vector sequence. When compared with ooja, the new algorithm provides benefits of weight matrix that are ensured at each iteration, numerical stability, and a quite similar computational complexity.
This paper exhibits a tsunami hazard assessment of the Lianyun District. Based on the Historical Seismic Events Catalogue & Analysis, the local, regional, and distant tsunami sources that may produce dramatic potential tsunami threats to the evaluation area were given scientifically. The outcome of the hazard assessment can supply decision-making support for emergency management, urban planning, and coastal fishery in the assessment area.
To study the mechanical characteristics of the Chrismas Tree, the parameter sensitivity analysis of the subsea Christmas Tree deepwater lowering system (DLS) is performed. The result showed that the DLS is affected by the combination of wave & current force. The reason for the docking failure is the current force. The maximum lateral displacement(L.D) is noted as 2.7m by the conversion of current velocity into the L.D.
Apple trees are a significant economic crop. Lately, deep learning algorithms have performed well in automating maintenance, and disease detection of apple plants. The paper shows various methodologies of feature extraction, dataset creation, and annotation. We also talk about the evaluation metrics & comparison of results. The purpose of this research is to review various techniques and highlight the possibilities for future development.
With the improvement of technology, AI technology in pollution detection has attracted people's attention. First, analyze the environmental pollution detection model based on AI technology is proposed. Finally, use the experimental analysis method to verify the practical applicability. Results showed that the pollution detection method of IT is more effective, has a larger carrying capacity, and can better ensure the follow-up effect later.
Chinese spirits is a distilled liquor with a long history. This research paper collects the image datasets of Chinese spirits of various distillation stages. It has attained 86.8% distillation bubble segmentation. This paper gives the way for domestic-related research to improve the intelligence level of the distillation process and improve the production. This research work fills the gap in domestic-related research.
Nearly 1 million Americans are living with HIV currently. The RWHAP gives funds for HIV care. By using spatial analysis techniques, the drive time from the center equal to the nearest RWHAP clinic was determined. These results were useful for making specific policy recommendations to improve access and reduce difficulties of HIV care.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
Today, AI is providing novel things to learn & do research. Today, research on AI depends on the usage of some goals & some particular tools. In this research work, we have carried out a survey analysis on Chat GPT. With this research work, we have given a vast range of information regarding chatbots and chat GPT.
SLU Forest Maps are maps of the Swedish forest state- stated by the Swedish University of Agricultural Sciences (SLU). It gives publicly available data, free of charge, operational uses in forest management planning, biodiversity assessment, monitoring, and more. This paper gives the SLU forest map, the data, methods used in the production, and an evaluation of the estimation accuracy of each variable.
Beef cattle raising in Thailand has evolved to business farming. The base of beef cattle production is profitable farming. To attain this, farmers must study factors affecting animal production. This study revealed the requirement of farm management and support system with stakeholder and user analysis and the design of beef cattle farming for Thai farmers' context.
Lately, women and girls are facing harassment. It is from society & social media or through any other methods. This paper focuses on the review of women's safety in different social media platforms. This paper focuses on women's safety in social media. Tweets, posts that contain videos & images, and written text that are abusive to the women.
In a developed economic situation, the e-commerce service industry has improved as a new field. With the rapid development of e-commerce, enterprises are also having great pressure. To develop it better, it needs some good financial capability. This research work proposes and discusses the key problems of financial management of the E-Commerce service industry.
Grapes are common fruits. But the varieties are huge. By using Deep Learning, the classification of grapes can be defined. Here, we have taken the CNN-GLS model, and undertaken “5” grapes leaf images. The results showed the accuracy of a small sample od grape leaves identification based on the CNN-GLS model. The accuracy is 95.13%. The model has robustness and high generation ability.
Lately, Cancer subtyping has provided valuable insights for studying Cancer Heterogeneity. We propose a novel Deep- Learning algorithm “Moanna”. The Moanna model has attained high accuracy in sample prediction ER status (96%), basal-like samples (98%), and classifying samples of PAM50 subtypes. Also, Moanna’s predicted subtypes correlate more strongly with patient survival when compared with the original PAM50 subtypes.
Deep learning is used in the medical field to detect cancer, diabetes, kidney disease, etc. Kidney disease is one of the major health issues across the globe. If CKD is not diagnosed earlier, it may lead you to dialysis or a Kidney transplant. CNN are used to classify the Chronic Renal Disease in this proposed system. This can be predicted with an accuracy of 95%.
Poetry can be differentiated by humans even in the absence of special equipment. In this paper, the problem of poetry identification was achieved by Hindi & Rajasthani Corpora. This work first reviews the rhyming detection methodologies and followingly introduces our unique statistical-based approach. It was evaluated against various learning methods using MATLAB.
Foodborne illness has emerged as a serious issue. This paper presents the design, fabrication, & characterization of the biosensor detection of E. coli in water. The fabricated interdigital electrodes are used to discriminate between dry & wet conditions by presenting outcomes at low frequencies. This paper provides the guidelines for the detection of E. coli at different concentrations with corresponding impedance ranges.
We adhere to novelty, and contemporary research trends. We work on PhD research projects with 100% customization. Explore more projects & do your work with us.
Autism shows a varied range of disabilities. To detect autism in 4-7-year-old children, we have recorded magnetoencephalogram signals from 30 autistic and 30 age-matched typically developing children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). This work exhibits a spatial brain activation pattern that can be used as a potential biomarkers of autism.
Today, Social media has become the backbone for all. Whatsapp messenger is one of the well-known social media platforms. It is free & cross messaging software that provides messaging services. The solution contains a semantic search mechanism between each claim associated with news sources. The similarity comparison done by the model predicts the truthfulness of the claim.
Today, we are living in a technological world! This research aims to design “3” E-learning techniques within the virtual studio by advancing the application of educational theories and strategies and developing the skills of interior among students. The research finds novel methodologies for educational techniques that fit the interior design curriculum using virtual studios. This will encourage students to develop ideas and foster creativity.
Engineering Education is the primary concern for developing future engineers. To attain this goal, we should teach students with the related subjects. All engineering professors can be effective and evaluate students to improve engineering education. In this study, authors have explained what is the way of teaching multi-disciplinary courses in various engineering programs and how to maximize the benefits of these courses.
For the first time, data are presented on passenger airplane production in the 20th century in the USSR & Russia. Notably, there was a continuation in the growth and production of airplanes. The result shows that the developers responded to this decline with an increase in activity that cannot be considered effective behavior in a time of sales reduction.
Stem cells give rise to various cell types. They can repair or replace cells that are missing or dysfunctional. Lately, there are so many clinical trials involved in stem cell therapies. We need a greater understanding of the fundamentals of stem cell biology. We need a greater understanding of the fundamentals of stem cell biology and the specifics of different disease processes.
Earthworms are used to crawl on the ground and burrow through soil by “2” types of muscles. We do research with the interwoven morphology of earthworms’ musculature to form a multimodal soft actuator (MSA). We carried out extensive experiments and characterized the evolution of pressure & elongation of MSA. Lastly, we adopted one of the identified actuation sequences to attain in-pipe locomotion.
DNA is known as the Blueprint of life. Through this paper, we aim to assess DNA evolution by sequencing methods (SM). We carry out a comparative analysis of modern-day DNA SM. We expose the potential of machine learning by taking exploratory and predicting the DNA sequence with the help of a Multinomial Native Bayes Classifier.
Oviposition measurement is one of the widely used methods for monitoring Aedes Aegypti mosquito activity across the globe. This paper proposes the semi- automatic counting of mosquito eggs laid on ovitrap sticks in images obtained by mobiles. We formed a fast semi-automatic counting solution. It helps to focus on the useful image area, shows the confidence of automatic counting numbers, and handles the collection of results.
The first sign of Parkinson’s disease (PD) is an abnormality in voice. PD patients are represented by nonlinear dynamic methods. The usage of such an algorithm will have the greatest influence on the development of an e-healthcare system for patients. The best output is CGradient, which possesses 87.39% of accuracy. A feature significance analysis was implemented to discover the key elements to categorize PD patients.
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Nowadays, Diabetes is one of the alarming diseases. Everyone in 11 of the entire population of adults has Diabetes. This paper proposes a new method based on a learning machine for diabetes prediction based on a data questionnaire. It can give an early alert for users to get medical help and they can prevent late diagnosis.
Rice is playing an important role in the culture & economy of India. This study aimed to form an Internet of Things (IoT) based system to monitor paddy yield. The result established a successful data collection & visualization through the IoT system. This work provides a promising solution for augmenting paddy cultivation practices & decision-making processes through IoT.
Deep Learning is a part of AI. This paper introduced 8 sets of different data sets of pet dogs. They are classified into training set & test set. Training sets are set to the established model for training. These results of the experiment show that this paper realizes the detection and classification of pet dogs with high detection speed and accuracy. It can reach 94.91%.
Research in Dolphin communication and cognition needs detailed inspection of audible dolphin signals. We propose an autoencoder that are formed from convolution & recurrent layers. The model from the result places patterns in audible dolphin communication. In various experiments, it is proved that the embeddings can be utilized for clustering, signal detection & classification.
Lately, Water conservation & management is one of the most important things. This paper proposed an autonomous system used for mitigating water wastage using real-time water flow control & monitoring. The designed prototype makes use of IR sensors to cease water discharge from overflowing faucets and taps automatically. This real-time water consumption data can be stored in cloud servers for analytics purposes.
Salt is a mineral used by food industries. Here, sensors such as S1, and S2 have been simulated by using COMSOL MULTIPHYSICS 5.6 software to check the concentration of salt. The result of the experiment matches the results of the simulation. The Gaussian Naïve Bayes-based Machine Learning Algorithm has been implemented to classify salt samples. The machine learning algorithm has attained an accuracy of 93.33%.
Honey bee hive robbery is a general occurrence that happens when nectar sources are scarce. This article shows the result of the analysis carried out on audio & video recordings attained at a hive before & after a robbery. Our research shows that there is enough information on the development & progress of a robbery that might help prevent it.
According to Stereo Planting Technology, the growth of strawberries in the greenhouse was monitored & controlled. The factors such as temperature, CO2, light, humidity, and soil needed for strawberries were assessed. The chemical control system sticks to the environmental factors needed for strawberries. So, it is stated that the growth cycle of strawberries can attain the best growth state.
In the USA, an estimated 700,000 people have been diagnosed with brain tumors. But the majority of these people have benign tumors and 30% of people have malignant tumors. GBM is the common type of malignant brain tumor with an increasing number of cancer patients who are diagnosed with brain metastases, where the cancer has traveled to the brain from other parts of the body.
Poultry production depends on the quality of eggs. The system for determining and grading egg quality is not yet fully developed. This paper introduced the design for automatic visual inspection of chicken fresh egg quality both for internal & external quality. According to the 10 sampled tests made, it generated 95% accuracy of accurately detected fresh poultry chicken eggs quality.
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This study investigates the contribution of green finance to the SDGs and the advancement of sustainable financial practices in businesses. This analysis highlights how green finance contributes to understanding the SDGs and promotes sustainable business practices. Green finance is key in directing funds towards environmentally friendly endeavours, including, sustainable infrastructure, and climate change initiatives.
This study delves into the role of green financing in fostering sustainable economic growth and identifies critical factors for building resilient economies. Analyzing data from 1995 to 2020 demonstrates the significant positive impact of Green Credit and Green Securities on long-term economic growth. Embracing green finance practices can enable policymakers and businesses to construct environmentally sustainable economies.
The transition to a sustainable economic model in China depends on green finance, but data collection is challenging. This study employs the CVM algorithm to establish a regional green financial statistical system and predicts data using MLP neural networks. Results highlight nature conservation and green forestry, offering insights for optimising financial resource allocation and forecasting in green finance.
The need to enhance access to financial resources for green developers is a pressing matter for developing economies. Green financing shortfall of $2.5 trillion annually. This article investigates barriers and strategies for green finance in India using literature review and modified Delphi method. It identifies policy, economic, and knowledge barriers as the main obstacles to green finance adoption.
This article examines the progress of the green financial system by analysing annual data from 2008 to 2018. It uses methods like entropy analysis, data envelopment analysis (DEA), and obstacle analysis to measure the efficiency of the system. The study analyses three subsystems significantly impacting the green financial system and suggests improvements for each subsystem.
Green finance has become an essential tool for addressing climate change and environmental degradation. This study delves into the complexities of green finance, examining its theoretical foundations, legislative measures, and international trends and explores the importance of green finance in supporting sustainable development, encouraging environmental stewardship, and speeding up the change to a low-carbon and resilient economy.
This study investigated a green supply chain that included a single supplier with financial constraints and a single retailer. A supplier-retailer Stackelberg game model was fixed under different financing situations, especially, bank financing and retailer's advance payment, and optimal decisions derived for the supplier and the retailer. The results showed that high supplier risk aversion is not conducive to the supply chain green development.
This study investigates financing options for carbon-emitting enterprises under carbon emission reduction measures in the supply chain. Using game theory, in-house factoring financing is analysed. It is found that the price sensitivity of commodities and carbon emission reduction percentage have a U-shaped relationship with optimal profit. These findings assist supply chain managers in selecting appropriate financing methods and promoting green supply chains.
Our work aims to develop an Auto-speech recognition system for English Lectures. In this research, we employ the DNN-HMM-based speech recognition system, we accomplished an 88% word accuracy to recognize TED lecture speeches. Likewise, speech summarization has proved the robustness to speech recognition errors. It is also the same in the summarization of text process.
Green sustainable energy slows down the issue of meteorological anomalies and climate changes. This paper analyses several energy indicators calculated for 12 years with statistics and machine learning techniques, with Self-Organizing Maps (SOM). The results can be further used to assess the efficiency of stimuli for green energy generation and improve the policymakers’ strategies.
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Simulators are widely used in robotics research. Depending on the research area there will be a range of suitable physics simulators. This study compiles a broad review of physics simulators for use within the robotics field. The review provides a global index of the leading physics simulators designed to assist in choosing the best simulator for a use case.
Various robot platforms exist for swarm robotics, but morphogenetic engineering introduces new requirements. This study presents Morphobot, designed for morphogenetic engineering. With coreless motors, it offers robust support and enhanced physical interactions. Each Morphobot has a changeable shell for programming local interactions. Mobility testing and experiments demonstrate its effectiveness in forming patterns via interactions and communications.
Soft robotic manipulators offer flexibility in unstructured environments and safe interactions with humans and delicate objects. Traditional designs lack simultaneous bending and twisting capabilities. This study proposes a soft robotic joint with a central vertebra, enabling twisting along with rotations, enhances payload and stiffness variability. Prototype testing demonstrates significant force and torque outputs with improved control accuracy.
Shape memory alloy (SMA) presents advantages for medical robotics. This study presents a SMA actuator for real-time medical robotics. Tunable SMA spring pre-displacements and compact packaging enable seamless integration. Constitutive and heat transfer models aid parameter selection. Implemented in a steerable endoscope manipulator, it showcases real-time surgical robotics applications.
Microrobots, with their small size and wireless actuation, hold promise for minimally invasive medical applications. Swarm control poses a key challenge in advancing these robots for clinical use, control of multiple units. This article reviews actuation systems, swarm behaviour modelling, control strategies, and biomedical applications. It emphasizes unique challenges and provides insights for future research in swarm micro-robotics.
Manipulation in confined spaces presents challenges in vision-guided robotics due to limited feedback. This study proposes a novel online robot-camera calibration method for environments with minimal feedback. The research introduces the interactive feature plane (IFP) and a depth-free adaptive controller using image feedback. This avoids external calibration objects and demonstrates accuracy and consistency in simulations and experiments. .
Learning-enabled control systems exhibit strong empirical performance in challenging robotics tasks. New techniques integrate learning certificates with control policies, offering concise proofs of safety and stability. These methods enhance training by incorporating safety requirements and providing both verification and supervision. This article introduce certificate learning theory and practice to robotics researchers interested in learning for control.
Soft material devices for control and computation are scarce despite advancements in soft matter sensing and actuation. The Soft Matter Computer offers analogue and digital computations limiting untethered operation. Introducing the liquid metal Soft Matter Computer with Galinstan reduces resistance, enabling operation at low DC voltages. This advancement facilitates fully soft computation and control, powering untethered soft machines.
Robotics engineering generates Big Data, requiring substantial computation due to sensor diversity. Cloud computing addresses this, but existing architectures lack a unified model, limiting adaptability. Heterogeneous platforms must meet Industry 4.0 and Society 5.0 benchmarks. Surveying cloud robotics architectures, this study proposes a top-down design approach and a reference architecture for next-gen platforms, addressing complex challenges systematically.
In agriculture, integrating robotics can enhance productivity, but reliable human localisation is crucial. We propose a topological particle filter to track workers using diverse sensors and active perception. Our approach combines local active sensing with global localisation, validated in real farm environments. By integrating multi-sensor data and active perception, we improve picker localisation accuracy compared to previous methods.
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Yoga's integration into academic settings aims to address rising student mental health issues. This study introduces an Android app utilizing human pose estimation for real-time evaluation of students' pose execution. Inter-rater reliability tests demonstrate substantial agreement between system and instructor evaluations. The app aids objective assessment, potentially influencing students' final grades and advancing research and training in yoga.
Amidst COVID-19, yoga has emerged as a popular practice for fitness and wellness. Online platforms have surged during lockdowns, with numerous yoga apps available. Artificial intelligence (AI) is now integrated into the fitness industry, offering personalized experiences. This paper explores AI-enhanced yoga apps, introducing an AI-based Yoga Trainer for guidance and motivation during yoga practice.
Yoga offers diverse health benefits for conditions like cancer, depression, and heart disease. Proper yoga postural alignment is crucial for safe practice. Computer vision and machine learning advancements enable accurate yoga posture prediction. This research study examines yoga posture identification systems using these techniques, facilitating safe and effective yoga practice through automated movement analysis.
Utilizing motion sensors simplifies the study of physical activities, including yoga. This article introduces a system leveraging motion sensors to assist beginners in learning correct yoga execution independently. During pandemics, such systems become vital when trainer supervision isn't feasible. It recognises 12 sun salutation steps and provides feedback on correctness using deep learning models, enhancing practice effectiveness and safety.
For practising yoga a trainer is vital, to guide and monitor the perfectness of different yoga poses. This paper proposes a system which aims to assist yoga with different yoga poses and correctness. By Integrating computer vision techniques, the proposed system analyses the human pose. In this system, the Human Pose Estimation technique based on computer vision is used.
This study examines the material properties of six complex electroids used in electro-homoeopathy remedies, typically administered orally for therapeutic purposes. While the clinical properties of Red electricity are well-documented, their material properties remain unexplored. In this study, Fourier Transform infrared spectroscopy and energy-dispersive X-ray fluorescence are employed to analyse these properties and their correlations.
Although homoeopathy lacks scientific evidence beyond the placebo effect, it is still widely used. Its presence in healthcare systems raises ethical and medical concerns, as it contradicts natural laws and lacks efficacy beyond placebo. This article addresses homoeopathy's pseudoscientific nature and its problematic role in contemporary medicine, highlighting the need for critical evaluation and public awareness.
This systematic review assessed homoeopathy's efficacy in oncological treatment from 1800 to 2020. This study included 18 studies with 2016 patients, primarily with breast cancer. Results showed varied effects on treatment toxicity, quality of life, and survival. However, the majority of studies had low methodological quality. Overall, there is insufficient evidence to support homeopathy's effectiveness in cancer care.
To evaluate the efficiency of standardized homoeopathic treatments compared to placebo for seasonal allergic rhinitis. Conducted across two university hospitals and 12 homoeopathic practices in Germany, 270 SAR patients received treatment for four weeks during the pollen season. The primary outcome is the Rhinitis Quality of Life Questionnaire score. Results inform on homoeopathic therapy effectiveness.
This paper addresses whether medicine qualifies as a science by proposing a Deflated Approach, recognizing science as a varied concept. Drawing from Hoyningen-Huene and Bird, it argues for medicine's systematicity, countering objections related to its duality and criticism like Oreskes'. Using homoeopathy as an example it demonstrates the success of systematicity as a demarcation criterion.
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This work introduces personas for AI, adapting classical user interface techniques to accommodate the unique challenges of human-AI interactions. It offers guidelines and materials for persona development, along with templates and visuals, using a freely available toolbox. An example in medical AI demonstrates practical application, aiming to support the development of future human-AI interfaces.
Game AI competitions are crucial for advancing research and development in both Game AI and AI in general. They offer challenging problems applicable to various contexts, virtual or real while providing frameworks and tools for research. The Geometry Friends competition focuses on a cooperative physics-based puzzle platformer game, addressing AI-related issues like planning and motion control in real time.
Rapidly increasing network intrusions prompt the exploration of AI techniques for intrusion detection systems (IDS). This work introduces an end-to-end framework for assessing black-box XAI methods in network IDS, evaluating global and local scopes. Using six metrics, this study analyses two popular XAI techniques, SHAP and LIME, across various network intrusion datasets and AI methods.
Table2 Text systems leverage machine learning to convert structured data into natural language, vital for interactions with virtual assistants, can yield misleading outputs. Generation Negotiation Interface offers an interactive visual platform for human-AI collaboration, integrating deep learning with explicit control states. Through a Refine-Forecast paradigm, users refine and forecast outputs, ensuring suitability and improving upon uncontrolled generation approaches.
A novel IoT-based approach, XAI-LCS, employs eXtreme gradient boosting to detect sensor faults efficiently, including bias, drift, complete failure, and precision degradation. It mitigates computational burdens and addresses the black-box nature of AI methods, achieving 99.8% accuracy. With explainable AI, it enhances trust in the model by interpreting prediction outcomes, crucial for high-risk industrial applications.
Digital Transformation integrates information technology across industries. Industrial Cyber-Physical Systems (ICPS) streamline machinery, production, and societal needs. This article explores using industrial artificial intelligence to enhance ICPS design. It surveys AICPS components, proposes design considerations, and investigates cutting-edge AI techniques' applications, aiming to advance understanding and integration into ICPS. .
Reinforcement learning with deep neural networks excels in various games but struggles with modern fighting games. Overcoming these challenges, this study developed one-on-one match battle AI agents for Blade and Soul, achieving a 62% win rate against professional gamers. It incorporates a novel self-play curriculum and data-skipping techniques, applicable to competitive games for game development improvements.
This survey delves into Conversational AI's surge in interest across government, research, and industry sectors. It provides a thorough analysis of large language models, notably ChatGPT, covering architecture, training, and challenges like bias and ethics. It explores ChatGPT's applications and future directions, serving as a roadmap for researchers, practitioners, and policymakers keen on leveraging these models.
This empirical study surveys AI practitioners and lawmakers globally, exploring the significance of AI ethics principles and challenges. Transparency, accountability, and privacy emerge as crucial principles while lacking ethical knowledge and legal frameworks pose significant challenges. Differences between practitioners and lawmakers are noted, emphasizing the need for enhanced capability maturity models to support ethics-aware AI system development.
This paper introduces vPred-RC, an algorithm enabling an AI to selectively provide reliance calibration cues (RCCs) to users. Tested in a collaborative task, vPred-RC dynamically selects RCCs, enhancing users' task assignments to AI agents with reduced communication costs. The approach aims to optimize reliance on AI systems by presenting RCCs judiciously, improving collaboration efficiency between humans and AI.
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Forecasting cloud prices are crucial for cloud service providers (CSP) and consumers. Value-based pricing considers both service cost and customer willingness to pay, addressing the subjectivity of consumer experiences. This hedonic pricing model captures non-marketable features' value, enhancing competitive advantages and profit margins for CSPs. This research aims to offer less biased pricing models for cloud decision-makers.
This study explores the integration of e-learning with cloud computing, examining their synergies and impact. Analyzing 154 papers, it investigates factors like architecture, software, performance, and cloud service models . Findings reveal prevalent topics such as architecture and software, with a focus on public cloud services. Limitations include gaps in hybrid and private clouds and infrastructure offerings.
The rise of IoT applications has led to Fog computing, blending mobile-edge and cloud resources. Task scheduling in this context faces challenges. This study proposes an asynchronous-advantage-actor-critic scheduler for Edge-Cloud environments, leveraging residual recurrent neural networks for efficient, decentralised learning. It shows significant improvements in energy consumption, response time, and cost compared to existing algorithms.
This article tackles active user detection (AUD) and channel estimation (CE) challenges in cell-free massive multi-input multi-output (MIMO)-based IoT. It proposes a frame structure design for reduced access latency and investigates cloud and edge computing paradigms for processing. It introduces a reliable joint AUD and CE algorithm, leading to improved performance over baseline schemes in simulations.
Artificial intelligence (AI) has revolutionized various fields. Its integration with cloud computing is crucial for enhancing efficiency and reliability. This paper explores AI's application in assessing cloud service reliability, aiming to develop a verification method for infrastructure-as-a-service. By implementing this method, users can efficiently gauge service reliability and ensure adherence to service level agreements.
Federated cloud systems enhance reliability and cost efficiency by integrating private and public clouds. This paper proposes a probabilistic flow-sensitive security model, assigning security levels to clouds and entities. It introduces the notion of opacity to measure information flow security and presents quantitative opacity analysis variants. This enables tracking information flow and analyzing the impact of resource allocation strategies.
In public blockchain systems utilising Proof of Work (PoW), resource competition poses challenges for resource-limited devices. Mobile blockchain proposes leveraging cloud computing resources for mining. However, cloud providers lack insight into user preferences. This article introduces a contract model addressing resource allocation and pricing, featuring an adverse selection solution to overcome information asymmetry. Resource pooling enhances user reward stability.
The rise of the Internet of Everything and deep learning incite the proliferation of AI applications. Cloud and edge computing offer diverse solutions to meet growing AI service demands but face challenges like underutilization and inefficient management. This proposes AI-Bazaar, a blockchain-based computing-power trading framework. A Stackelberg game approach and PB-MARL algorithm achieve balanced profits for consumers and providers.
The collaborative edge and cloud computing system addresses 5G application demands but faces challenges like hardware management and data processing bottlenecks. To mitigate these issues, a software-defined edge and cloud computing (SD-ECC) framework is proposed, integrating erasure-coded storage. A joint data access and task processing (JDATP) algorithm minimises task response time and increases storage space.
Edge computing minimizes service latency by deploying computing resources close to end users. Cooperative edge-cloud computing leverages geographically distributed edge and cloud data centres to enhance efficiency. We model VM placement and workload assignment to meet application latency constraints, minimizing IT infrastructure consumption. Preliminary results suggest optimizing edge datacenter resource efficiency through cross-site VM placement and workload redirection.
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AI plays a vital role in cybersecurity by enhancing threat understanding, anticipation, and risk mitigation. Its complexity makes cybersecurity controls challenging to grasp and implement. AI aids in educating both academics and practitioners by demonstrating its efficacy in creating policies and enhancing awareness. This study examines AI's efficiency in strengthening cybersecurity education and awareness throughout the entire lifecycle.
This article introduces the Integrated cross-platform security assessment framework, developed as part of the Security Technologies Project, focusing on Research, Development, and Innovation in Security Assessment in Brazil. With technology-specific focuses, this aims to address the heterogeneous technological landscape by integrating various security assessment methodologies. It serves as a foundational tool for the project's objectives.
Cyber assurance is crucial for organizations facing constant security threats. Employing cybersecurity standards and certifications aids in risk management and ensuring secure ICT products. A survey of 258 participants reveals adoption barriers to the Common Criteria. Recommendations for promoting cybersecurity standards are provided, along with insights into additional risk management strategies for enhancing cyber assurance in organizations.
Modbus, a widely used industrial communication protocol, lacks security due to its development in closed environments. To address security concerns, this study proposes a cyber-physical system using Modbus/TCP for real-time security testing. Our architecture integrates a process simulator, PLC, and human-machine interface via Modbus/TCP, enabling the modelling of industrial processes, cyber-attacks, and protection mechanism development.
Global geopolitical tensions are driving towards Internet nationalism, risking fragmentation into a 'Splinternet.' This paper contends that the software security crisis worsens this trend. It explores existing moves towards Internet fragmentation, trends in online threats, and the role of software vulnerabilities. Urging a 'zero tolerance' stance on software security, it discusses necessary measures to address this issue.
The cryptocurrency market's growth prompts the optimisation of trading websites. Balancing customer satisfaction and low digital ad costs is crucial. This study outlines a digital marketing strategy for cryptocurrency trade websites, leveraging web analytics and modelling techniques. Enhancing digital engagement can improve SEO and SEM campaigns. Insights highlight key metrics for cost-effective marketing and traffic generation. .
This study aims to integrate big data analytics and AI into digital marketing for sustainable practices. It analyses big data characteristics, develops an AI random forest model, and applies it to a real-world case study. Findings reveal prevalent demographics and price patterns. The AI-driven model outperforms logistic regression in predicting customer volumes, laying the groundwork for advanced marketing strategies.
This paper addresses the need to define competencies crucial for leveraging technology to sustain humanity and ecosystems. Employing a mixed methods approach, it combines literature review insights with interviews with practitioners and industry leaders. Through expert workshops and focus groups, a robust definition of digital excellence is established, informing educational policies and workforce development strategies.
Digital technologies rapidly render products, processes, and business models obsolete, challenging small-medium enterprises (SMEs), especially in manufacturing. This article explores how SMEs can leverage digital servitization to adapt in disrupted markets. Using interpretative research, it proposes a digital servitization model for SMEs and offers research and managerial implications for navigating market disruption through innovation.
This paper analyzes executives' perceptions of digital business transformation (DBT) in pipe extrusion companies in Germany. It investigates disruptions prompting DBT, whether it's viewed as a challenge or crisis, and communication strategies. Qualitative research via semi-structured interviews reveals acknowledgement of disruptions but a lack of crisis perception. Many companies lack strategies for effectively communicating responses to DBT challenges.
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This article explores the intricate relationship between innovation and digital transformation, essential areas in management. Using co-word analysis, it systematically maps the intellectual structure of the field, identifying key themes, concepts, and their connections. The resulting taxonomy informs about controversies, gaps, and areas for further research, facilitating exploration and exploitation of this connection across academia and various sectors.
This paper presents insights from experts on driving Digital Business Transformation (DBT) in organizations. Through primary interviews, six key lessons are derived, focusing on CEO commitment, change leadership, team composition, stakeholder behaviour, digital platform selection, and business ecosystem relationships. These lessons offer valuable guidance for organizations embarking on DBT implementation, serving as a starting point for their transformation journey.
In the working world, digitalization has exasperated fast changes. This article highlights the necessity for tailored strategy formulation in manufacturing supply chains amidst digitalization. Case studies identify three digital strategy typologies, each contingent on factors like supplier count, market demand, and product types. The proposed framework offers a reference point for navigating digital transformation in supply chain operations.
This study investigates digital transformation in secondary schools, addressing research questions on current state-of-the-art, essential indicators, frameworks, and implementation strategies. Six transformation factors are identified: leadership, digital competency, professional development, technology access, school evaluation, and school competency. The study explores research trends and challenges, aiming to facilitate digitalization in education.
This study examines factors influencing digital technology adoption in SMEs. Data from 15,346 European Union and non-EU SMEs reveal that technology context, innovation level, organizational factors, and corporate regulation influence adoption. The study highlights the importance of assessing organizational readiness before investing in digital technology, emphasizing the need for strategic planning and skills development.
This article addresses the evolving landscape of ICT security in banking, particularly in light of the Payment Services Directive (PSD2) and its requirements for multi-factor authentication. It provides an overview of current authentication methods, their compliance with international standards, and their resilience against attacks, offering a comprehensive tool to navigate this complex domain.
Using innovative IT and communication technologies, FinTech provides financial services. The study investigates FinTech's rapid growth and its impact on the Greek banking system. Questionnaires were used to gather data from consumers and banking employees. Consumers generally trust traditional banks over FinTech, with security being a top concern. Education influences bank employees' readiness for new technologies.
The study examines perceived risk, benefit, and trust factors influencing FinTech adoption in India. Data were collected via a structured questionnaire, and validated for reliability and validity. Analysis indicates positive impacts of benefits and negative impacts of risk on FinTech adoption intention. These insights are crucial for service providers and FinTech managers, especially during the pandemic.
This study explores how FinTech impacts Chinese banks' systemic risk. Using bank-level panel data and SYS-GMM, discovered that FinTech amplifies both banks' exposure and their systemic risk contribution, particularly in local commercial banks and regions with underdeveloped FinTech. The study identifies that FinTech expands interbank business and heightens the correlation between banks, increasing risk contagion potential.
This study explores the impact of Fintech adoption on companies using the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA). Surveying 300 companies and Partial Least Squares Structural Equation Modelling, it confirm the robustness of TPB and TRA in Fintech usage. These insights can guide Fintech firms in crafting effective marketing strategies for better organizational performance.
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Based on the OBE concept, the language education of preschool-aged children serves as the foundation for the "Six in One" teaching mode, which forms the "three-dimensional" and "three-stage" objectives, progressive and modular course content gradually, and teaching methods that satisfy the requirements. "Binary and three-segment" intelligent teaching entails adhering to the integration of production and education.
The aim of this study is to suggest indicators for initial education that should be taken into account for educational inclusion. The theoretical assumptions of the cited publications were examined using techniques including analysis and synthesis and inductive deductive reasoning, and expert criteria were used to confirm the proposal's viability.
The tourist sector contributes significantly to the economic and social growth of many nations. The potential of a Digital Local Tourism Management System (DLTMS) to promote the development of sustainable local tourism is investigated in this study. The potential of a DLTMS to promote the development of sustainable local tourism is investigated in this study. The study offers perception and suggestions for marketing and deploying DLTMS in various settings and geographical areas.
Currently, big data technology and concepts have been applied to numerous industries and have produced many positive outcomes due to their ongoing development and extension. The study focuses on Hubei's all-area tourist management level's smart tourism marketing, smart tourism services, and big data in tourism. The article offers related solutions and recommendations in an effort to contribute to the growth of all-area tourism in Hubei.
Due to e-commerce and the introduction of the Unified Payments Interface (UPI) by the Indian government, which provides a user-friendly service with little to no fees, the use of debit and credit cards for money transfers and purchases has increased dramatically in recent years, as has mobile banking. This article examines the numerous security measures and technological advancements that experts have suggested to ensure the safe and secure usage of internet banking.
This study uses Domain Driven Design to address the issue of multiple linked surrounding systems that perform the same function in various systems. The study concludes that quickly altering the practice of rapidly scaling up the system and application can facilitate the installation of a SOA system for transactional banking activities.
There are now more ways to discreetly and remotely monitor medical issues thanks to wearable and smartphone technologies. We introduce a new method for adaptive sampling based on hidden Markov models with clustered continuous-time features. The work is demonstrated with longitudinal data on mental health symptoms from 49 individuals, which were gathered via the ClinTouch smartphone app, which is intended to track individuals with a diagnosis of schizophrenia.
A fresh viewpoint on the application of Vetiver Grass Technology (VGT) in rural India is presented in this research. The paper examines the established advantages of vetiver grass and evaluates its potential for community-based infrastructure development and riverbed rehabilitation in rural India. Additionally, it explores the co-benefits of vetiver grass cultivation and skill development for women's empowerment and income generation.
Globally, the education sector has benefited from the availability of access to the internet. This paper seeks to assess the effectiveness of education by taking the use of new technology, and the knowledge and professional development that students receive from taking online courses. The results show that online students are more committed than on-campus students. It was found that instructors were able to encourage students successfully.
In drug discovery, one of the primary issues is drug-drug interactions. To predict unobserved drug-drug interactions, we present in this research a Deep Attention Neural Network based Drug-Drug Interaction prediction framework, abbreviated as DANN-DDI. When compared to state-of-the-art techniques, the experimental findings show that our model, DANN-DDI, has enhanced prediction performance.
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India plays a crucial role in the US strategy to rival Beijing globally. Experts emphasise the mutual interest between Washington and New Delhi, this article highlights a political challenge. Since 2014, India has pursued a restorationist vision, leveraging culture and heritage to assert sovereignty. This trend, led by the ruling Bharatiya Janata Party, may prioritise historical grievances over regional sovereignty.
Group consciousness is pivotal in understanding racial and ethnic politics. Originating from African American politics, it’s now a framework for analysing other groups. This study surveyed over 700 Indian Americans to explore group consciousness and its political impact. It correlates with political engagement and opinion, offering insights into American Indian politics and border political behaviour.
This article explores care in decolonial politics, focusing on its role in the politics of refusal. Drawing from William Apess's insights, it examines indigenous reworkings of care and its expression in movements like Idle No More and Standing Rock. Care fosters indigenous community, drives environmental activism, and challenges settler memory, shaping transformative decolonial politics.
Sub-national governments receive varying transfers from the Central government, influenced by partisan politics. Research indicates that politically aligned states receive higher grants. Non-aligned states receive lower grants overall. Favouritism is evident between states ruled by the same party and those supporting the Central government. While drought was once a significant factor, its importance in grant allocation has diminished.
Parry's "Classes of Labour" revives the "labour aristocracy" thesis, showcasing the bifurcation within India's industrial workforce. This case study illustrates how the public privileges distinct classes with varied life chances and political interests. Giddens' "class structuration" concept as a theoretical framework, reveals class dynamics. This approach views class as dynamic, prompting exploration of class restructuring amid jobless growth in India.
In the face of growing student numbers, implementing active teaching methods like Flipped Classrooms and Work-Based Learning becomes challenging for motivated lecturers, especially in engineering and computer science. Digital Peer Assessment offers a scalable feedback solution. This review of 14 papers explores design choices, tool availability, effects on learning outcomes, and implementation challenges, aiding educators in selecting or creating suitable tools.
Social media usage is particularly prevalent in Indonesia. The purpose of this study is to determine whether social media may effectively affect travellers' decisions to book a trip. The study's findings demonstrate that, according to the AIDA model, social media has a significant impact on traveller’s decision-making. The findings of this study will enhance the growth of tourism marketing, particularly social media promotion, as a component of integrated tourism planning.
The aim of this research is to create a conceptual framework, grounded on international education standards, for digital culture leadership in smart schools. The researcher's conclusions are applied to develop standards that measure smart school staff members' leadership in digital culture in accordance with global educational norms. The results of this study are utilised to develop standards for assessing the leadership in digital culture.
A country's overall strength is reflected in its higher education system. This study examines the viability and health of the higher education systems in several countries using the CIPP model. To enhance the model, 18 indicators were chosen, mostly using the entropy and cluster analysis methods. This article aims to develop a four-phase approach for the progressive, step-by-step reform of higher education. It serves as a reference for the sustainable implementation of higher education in comparable countries.
A novel coronavirus disease known as COVID-19 is a pandemic that has resulted in 200 million infections and 4 million fatalities. It is essential to diagnose COVID-19 infections quickly and accurately to stop the epidemic from spreading. To prevent the COVID-19 pandemic from spreading, prompt and accurate diagnosis of illnesses is crucial. Our classification accuracy reach 98.31%, and AUC (Area Under Curve) are 98.82%, 97.99%, 98.67%, and 0.989, respectively.
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This study offers a design framework and addresses whether developing a civil airport safety management system with digital twin technology is feasible. According to the research, the use of digital twin technology can enable the spatial marking and display of safety management information for civil airports as well as make it easier to enter, inspect, query, and monitor safety information on facilities, equipment, and dangers. Expert systems have the potential to improve airport convenience by providing emergency command and dispatching, emergency rescue simulation training, and more.
Quartz crystal resonators are some important components of signal processing with a wide range of applications and are largely employed in today's communication devices and systems. To improve the conductive polymer electrodes' performance, it is important to optimise their processing technology. Recently, conductive polymer quartz crystal resonators have achieved considerable improvements in quality factor and lowered impedance, around four times that of metal electrode resonators.
The restructuring of trade networks will not only have a significant impact on international industrial division. In order to assess the evolutionary characteristics of the global commodity trade network, this paper gathers trade data from multiple nations from the CEPII-BACI database from 2000 to 2022, builds a global trade network, and uses Stata analysis software to examine the general features, network stability, network heterogeneity, and other indicators of the trade network.
The natural gas sector faces a technological, financial, and environmental problem in locating and identifying leaks. In order to locate and measure methane leaks, this contribution proposes a wireless sensor network strategy based on a miniaturised, selective, low-cost, low-power photoacoustic methane detector incorporated in a wireless multi-sensor node.
The goal of this research is to create and assess WorkEv, an Electronic Human Resource Management (E-HRM) system that will help with performance monitoring and enhancement. The target user can accept the WorkEv application based on the findings of the UAT using the Delphi approach because the design and development outcomes satisfy the target user's needs. The current features and functions are useful for assisting small and medium-sized enterprises in carrying out human resource management (HR).
The agricultural products are seriously threatened by plant leaf diseases. It is to blame for the economic losses in agriculture. This study presents a straightforward and reliable method for quickly and accurately identifying plant leaf diseases using plant leaf images. This technique The benefits of the suggested approach are corroborated by the experimental findings and analysis performed on a publicly accessible Plant Village dataset.
The goal of the information building of a smart health and senior care village is to integrate intelligent information platforms in the fields of health and senior care through the "Internet +" health and senior care mode, thereby achieving the connectivity of multiple system platforms. Finally, the sustainable development of smart health and senior care in China can be achieved thanks to the effective application of information technology in these fields.
High voltage direct current (HVDC) insulation may use polypropylene (PP), an insulation material with a high operating temperature and capacity for recycling. This work aims to study the impact of TiO2 rutile phase on the dielectric characteristics of PP nanocomposites. The breakdown strength of PP for all systems was considerably reduced by the rutile TiO2. The mechanism pertaining to the reduction in DC breakdown strength is examined.
A drug-drug interaction occurs when two drugs interact with one another. One of the most difficult and comprehensive uses of natural language processing is drug-drug interaction. Well-known benchmark data sets are used to validate our proposed model, and our BERT-based classification has outperformed earlier techniques with 90.69% accuracy and 81.97% f1-score.
The goal of the information building of a smart health and senior care village is to integrate intelligent information platforms in the fields of health and senior care through the "Internet +" health and senior care mode, thereby achieving the connectivity of multiple system platforms. Finally, the sustainable development of smart health and senior care in China can be achieved thanks to the effective application of information technology in these fields.
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