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Keyword: AttentionMRI Semantic Segmentation based on Optimize V-net with 2D Attention
Over the past ten years, deep learning models have considerably advanced research in artificial intelligence, particularly in the segmentation of medical images. One of the key benefits of medical picture segmentation is that it allows for a more accurate analysis of anatomical data by separating only pertinent areas. Numerous studies revealed that these models could…
Read MorePersonalized Serious Games for Improving Attention Skills among Palestinian Adolescents
Serious games (SGs) are interactive and entertaining digital games with a special educational purpose. Studies have shown that SGs are effective in enhancing educational skills. Cognitive skills training through serious games have been used in improving students learning outcomes. In this article, we introduce the ‘plants kingdom’ serious game for improving adolescents’ cognitive skills, mainly…
Read MoreSelection of Rotor Slot Number in 3-phase and 5-phase Squirrel Cage Induction Motor; Analytic Calculation
With the spread of inverters, the attention of designers naturally turned to 5-phase motors, due to their advantageous properties. In this regard, perhaps the most important issue in the design of such machines is the selection of the correct rotor slot number. Many articles have been published on multiphase machines, however, only few of them…
Read MoreEfficient Deep Learning-Based Viewport Estimation for 360-Degree Video Streaming
While Virtual reality is becoming more popular, 360-degree video transmission over the Internet is challenging due to the video bandwidth. Viewport Adaptive Streaming (VAS) was proposed to reduce the network capacity demand of 360-degree video by transmitting lower quality video for the parts of the video that are not in the current viewport. Understanding how…
Read MoreDouble-Enhanced Convolutional Neural Network for Multi-Stage Classification of Alzheimer’s Disease
Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…
Read MoreTracing the Evolution of Machine Translation: A Journey through the Myanmar (Burmese)-Wa (sub-group of the Austro-Asiatic language) Corpus
Machine Translation (MT) has come a long way toward reducing linguistic gaps. However, its progress in efficiently handling low-resource languages—such as the Wa language in the Myanmar-Wa corpus—has not received enough attention. This study begins with a thorough investigation of the historical development of MT systems, painstakingly following their development against the complex background of…
Read MoreForecasting Bitcoin Prices: An LSTM Deep-Learning Approach Using On-Chain Data
Over the past decade, Bitcoin’s unprecedented performance has underscored its po-sition as the premier asset class. Starting from an insignificant value and reaching an astounding high of around 65,000 U.S dollars in 2021 – all without a central con-trolling authority – Bitcoin’s trajectory is undoubtedly a historical feat. Its intangible nature, initially a subject of…
Read MoreThe First Application of the Multistage One-Shot Decision-Making Approach to Reevaluate a Technology Project Decision Problem
Decision-makers must make a suitable sequence of decisions under uncertainty in a relatively long period for particular projects and situations. Conventional decision-making approaches under uncertainty are based on expected utility theory and do not sufficiently reflect the one-time nature of decisions. Similarly, the conventional approaches do not adequately incorporate the decision-maker’s intuitions in the decision-analysis…
Read MoreNorthern Leaf Blight and Gray Leaf Spot Detection using Optimized YOLOv3
Corn is one of the most important agricultural products in the world. However, climate change greatly threatens corn yield, further increasing already prevalent diseases. Northern corn leaf blight (NLB) and Gray Leaf Spot are two major corn diseases with lesion symptoms that look very similar to each other, and can lead to devastating loss if…
Read MoreA Unified Visual Saliency Model for Automatic Image Description Generation for General and Medical Images
An enduring vision of Artificial Intelligence is to build robots that can recognize and learn the visual world and who can speak about it in natural language. Automatic image description generation is a demanding problem in Computer Vision and Natural Language Processing. The applications of image description generation systems are in biomedicine, military, commerce, digital…
Read MoreControl and Monitoring Systems in Medium Voltage Distribution Networks in Poland – Current Status and Directions of Development
The paper describes the control and monitoring systems installed in medium voltage networks by Polish distribution network operators. It also outlines the expected directions of development of these systems, specifies the functions of the individual system components and describes the requirements applicable to them. In particular, attention is paid to the implementation of functions to…
Read MoreExtraction of Psychological Symptoms and Instantaneous Respiratory Frequency as Indicators of Internet Addiction Using Rule-Based Machine Learning
Internet addiction (IA) has adverse effects on psychophysiological responses, interpersonal relationships, and academic and occupational performance. IA detection has received increasing attention. Although questionnaires enable long-term assessment (over 6 months) and physiological measurements to aid the short-term evaluation (over 2 min) of IA, the lack of algorithms results in an inability to detect IA in…
Read MoreExploiting Domain-Aware Aspect Similarity for Multi-Source Cross-Domain Sentiment Classification
We propose a novel framework exploiting domain-aware aspect similarity for solving the multi- source cross-domain sentiment classification problem under the constraint of little labeled data. Existing works mainly focus on identifying the common sentiment features from all domains with weighting based on the coarse-grained domain similarity. We argue that it might not provide an accurate…
Read MoreEffect of Smooth Transition and Hybrid Reality on Virtual Realism: A Case of Virtual Art Gallery
Virtual reality (VR) is finding applications in a wide range of industries; however, a significant number of users find VR experience considerably different from the real-world experience. To match the real-world experience, the VR experience should look real, should be immersive, and be in line with the users’ anticipation. Achieving realism in the virtual representation…
Read MoreA Review of Plastic Waste Management Practices: What Can South Africa Learn?
Municipal Solid Waste (MSW) is composed of items that are discarded or disposed of daily including paper, plastics, glass, metals, used gadgets, paint and old furniture. The plastic waste stream has proven to be problematic to manage sustainably on a global scale. Various researchers are trying to come up with innovative ways of alleviating the…
Read MoreAdvanced Multiple Linear Regression Based Dark Channel Prior Applied on Dehazing Image and Generating Synthetic Haze
Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…
Read MoreA Hybrid NMF-AttLSTM Method for Short-term Traffic Flow Prediction
In view of the current short-term traffic flow prediction methods that fail to fully consider the spatial correlation of traffic flow, and fail to make full use of historical data features, resulting in low prediction accuracy and poor robustness. Therefore, in paper, combining Non-negative Matrix Factorization (NMF) and LSTM model Based on Attention Mechanism (AttLSTM),…
Read MoreVisual Saliency Detection using Seam and Color Cues
Human have the god gifted ability to focus on the essential part of a visual scenery irrespective of its background. This important area is called the salient region of an image. Computationally achieving this natural human quality is an attractive goal of today’s scientific world. Saliency detection is the technique of finding the salient region…
Read MoreMethod of Technological Forecasting of Market Behaviour of R&D Products
The current concept of open innovation corresponds to the R&D products transfer model – “role changes”. One of the fundamental provisions of the model is that R&D products are considered for commercialization not only at the final stage of technological readiness, but at any of them. In today’s changing market environment, special attention is paid…
Read MoreA Proposed Framework to Improve Containerization from Asia to North America
The constant market change and the critical role of the logistics process in the supply chain need to have special attention because it is an essential piece for the global business strategy. This paper presents an assessment of the processes of handling material from Asia suppliers to North America. The data utilized for the analysis…
Read MoreAn Evaluation of some Machine Learning Algorithms for the detection of Android Applications Malware
Android Operating system (OS) has been used much more than all other mobile phone’s OS turning android OS to a major point of attack. Android Application installation serves as a major avenue through which attacks can be perpetrated. Permissions must be first granted by the users seeking to install these third-party applications. Some permissions can…
Read MoreA Framework for Adoption and Diffusion of Mobile Applications in Africa
The adoption and diffusion of mobile applications (mobile apps) has become the base of modern activities in Africa owing to the services and values that are obtained through mobile apps innovations. More emphasis has been on the development of mobile apps whereas the adoption and diffusion process as well as their predictors are ignored or…
Read MoreLEACH Based Protocols: A Survey
Advances in the world of communications and information technology, as well as the urgent necessity to monitor particular areas and regions, have led to a considerable and influential development in the world of wireless sensor nodes. As they are small, low-cost multi-purpose nodes with limited energy and capabilities. The most important points that deserve research…
Read More5G, Vehicle to Everything Communication: Opportunities, Constraints and Future Directions
The 5G, as a new source of telecommunication infrastructure technology, has attracted many stakeholders to promote the progress of its standards and the development of its technology industry. The 5G reinforces new technologies and delivers vehicles for everything services (V2X) to drivers and passengers. It also offers several advantages. On the other hand, due to…
Read MoreFeature Gate Computational Top-Down Model for Target Detection
Computer vision is a technique used for processing images and videos which are increasingly becoming ubiquitous day by day. Technologies developed are revolving around human needs and demands high computational power as volume of data increases. The extraction of the necessary information for processing, that is independent of various scene complexity is a challenging task.…
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