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Genetic Algorithm Augmented Inception-Net based Image Classifier Accelerated on FPGA

Multimedia Tools and Applications 2023年第29期82卷 45097-45125页

作者： Kaziha, Omar Bonny, Talal Jarndal, Anwar Department of Electrical Engineering College of Engineering University of Sharjah Sharjah United Arab Emirates Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates

Deep learning models for computer vision applications specifically and for machine learning generally are now the state of the art. The growth of size and complexity of neural networks has made them more and more reliable, yet in greater need of computational power and memory as is evident from the heavy reliance on graphical processing units and cloud computing for training them. As the complexity of deep neural networks increases, the need for fast processing neural networks in real-time embedded applications at the edge also increases and accelerating them using reconfigurable hardware suggests a solution. In this work, a convolutional neural network based on the inception net architecture is first optimized in software and then accelerated by taking advantage of field programmable gate array (FPGA) parallelism. Genetic algorithm augmented training is proposed and used on the neural network to produce an optimum model from the first training run without re-training iterations. Quantization of the network parameters is performed according to the weights of the network. The resulting neural network is then transformed into hardware by writing the register transfer level (RTL) code for FPGAs with exploitation of layer parallelism and a simple trial-and-error allocation of resources with the help of the roofline model. The approach is simple and easy to use as compared to many complex existing methods in literature and relies on trial and error to customize the FPGA design to the model needed to work on any computer vision or multimedia application deep learning model. Simulation and synthesis are performed. The results prove that the genetic algorithm reduces the number of back-propagation epochs in software and brings the network closer to the global optimum in terms of performance. Quantization to 16 bits also shows a reduction in network size by almost half with no performance drop. The synthesis of our design also shows that the Inception-based classifier is cap

关键词： Genetic algorithms

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TCP Variants for Internet of Things: A Survey 4

TCP Variants for Internet of Things: A Survey

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4th International Conference on Distributed Sensing and Intelligent Systems, ICDSIS 2023

作者： Mansour, Youssef Alfalasi, Hamad Abbas, Sohail Talib, Manar Abu Department of Computer Science College of Computing and Informatics University of Sharjah United Arab Emirates

ISBN: (纸本)9781839539954

Due to its broad usage and predominance, TCP (Transmission Control Protocol) serves as the core of all Internet traffic. TCP is widely used because of its reliable connection-oriented architecture and capacity to manage congestion using different congestion control algorithms across a range of network loads and circumstances. The three phases of these congestion control algorithms—Slow Start, Congestion Avoidance, and Congestion Detection (Fast Recovery and Fast Retransmit)—are generally how they work. However, different TCP variants, such as Reno, New Reno, Tahoe, and more recent versions like FAST TCP, Cubic TCP, and Elastic TCP, implement these phases quite differently. Ever since these protocols were developed, the Internet environment has changed significantly, and they now have to deal with diverse set of challenges like high bandwidth demand problem and the requirement of fairness among various TCP flows. In this paper, we will review the most recent literature considering TCP variants for Internet of Things (IoT). Furthermore, we will analyze these techniques based on various factors, such as technology used, evaluation methodology and metrics, nodes type and mobility. © The Institution of Engineering & Technology 2023.

关键词： Internet of things

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Detecting Routing Attacks in WSN: A Novel Cartesian Product-Based Method

Detecting Routing Attacks in WSN: A Novel Cartesian Product-...

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2024 Arab ICT Conference, AICTC 2024

作者： Ahmed, Saad Salman Alansari, Zainab Belgaum, Mohammad Riyaz College of Computing and Information Sciences University of Technology and Applied Sciences Muscat Oman G. Pullaiah College of Engineering and Technology Kurnool India Multimedia University Faculty of Computing and Informatics Cyberjaya Malaysia

ISBN: (纸本)9798350342086

Routing attacks pose a substantial security risk in Wireless Sensor Networks (WSNs), compromising network performance and reliability. Utilizing the Cartesian product concept to identify these routing attacks in WSNs is an emerging and promising approach. This strategy involves generating a Cartesian product graph from the original network graph and subsequently extracting relevant features to detect potential threats. The success of this approach is dependent on several factors, such as feature selection, the detection algorithm employed, and the prevailing network conditions. This research presents an innovative framework that leverages the Cartesian product approach to identify routing attacks in WSNs. The performance of this framework is evaluated using the Cooja simulator, yielding results that indicate high detection accuracy, low energy usage, and minimal overhead. A comparative analysis with contemporary studies illustrates the superior ability of this framework to handle a wide range of attack scenarios and network conditions. The introduced framework significantly advances the field of routing attack detection in WSNs and provides an actionable solution for easy integration into existing WSNs. © 2024 IEEE.

关键词： Wireless sensor networks

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Addressing Imbalance in Health Datasets: A New Method NR-Clustering SMOTE and Distance Metric Modification

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Computers, Materials & Continua 2025年第2期82卷 2931-2949页

作者： Hairani Hairani Triyanna Widiyaningtyas Didik Dwi Prasetya Afrig Aminuddin Department of Electrical Engineering and Informatics Faculty of EngineeringUniversitas Negeri MalangMalang65145Indonesia Department of Computer Science Universitas BumigoraMataram83127Indonesia Department of Computer Graphic and Multimedia Faculty of ComputingCollege of Computing and Applied SciencesUniversiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia

An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared t

关键词： SMOTE modification Clustering-SMOTE manhattan distance

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Evaluation of STEM digital educational games using an instrument that integrates technology acceptance and player experience factors 23

Evaluation of STEM digital educational games using an instru...

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15th Biannual Conference of the Italian SIGCHI Chapter: Crossing HCI and AI, CHItaly 2023

作者： Azami, Husna Hafiza R. Ibrahim, Roslina Masrom, Suraya Che Mohd Yusoff, Rasimah Yaacob, Suraya Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Malaysia College of Computing Informatics and Media Universiti Teknologi MARA Malaysia

ISBN: (纸本)9798400708060

Digital educational games (DEGs) are gaining a lot of recognition in a variety of educational and training contexts, including science, technology, engineering, and mathematics (STEM). Since modern-day children are accustomed to digital and gaming technologies, DEGs are considered to be a progressive and effective learning strategy that appeals to them. However, despite the enormous efforts and financial investments made by game academics and producers, students' acceptance of this learning tool is still low. There is also a lack of studies that provide an understanding of students' perceptions and acceptance of STEM DEGs. Furthermore, existing research normally conducts the assessment of game acceptance and player experience (PX) separately even though both are crucial assessments that can be integrated and measured simultaneously in a comprehensive manner. Hence, this paper presents the evaluation of three DEGs related to STEM namely RoboCo, Poly Bridge 2, and Moonbase Alpha using a questionnaire that extensively combines important user acceptance and PX components. The proposed DEGAPX instrument which consisted of 13 factors measured by 64 items had passed the reliability and validity testing. The descriptive statistics of the 281 valid responses received from high school students in Malaysia and the interview results with ten survey participants were discussed in this paper. Students' views on the games were generally positive and their intention to use the games was higher when more factors of the DEGAPX instrument received high scores. This paper highlights the design criteria that can be considered by game developers for creating DEGs that satisfy the needs of target users. Educators can also utilize the suggestions discussed in this paper for the selection of games and deployment in classrooms. © 2023 ACM.

关键词： Students

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CT Scan Liver and Liver Tumor 2D Segmentation: A Deep Learning Review and Empirical Analysis 12

CT Scan Liver and Liver Tumor 2D Segmentation: A Deep Learni...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Montalbo, Francis Jesmar P. Palad, Lanie P. Castillo, Ria L. Marasigan, Kimberly I. De Ocampo, Anton Louise P. Batangas State University College of Informatics and Computing Sciences Batangas City Philippines Batangas State University College of Engineering Batangas city Philippines

ISBN: (纸本)9798350391398

Accurate liver tumor segmentation in medical imaging is essential for early diagnosis and improving patient survival, yet it remains a significant challenge. Despite rapid advancements in deep learning (DL), the diverse range of models-convolutional neural networks (CNNs), transformers, and hybrid architectures-has led to fragmented insights regarding their effectiveness in liver tumor segmentation. This review addresses the critical need to systematically evaluate and compare these models, providing valuable guidance for researchers and clinicians in identifying optimal solutions. Our analysis highlights CNNs as more computationally efficient, while transformers demonstrate robustness in performance. Combining both strengths, hybrid models show even more significant potential and balance in cost to performance ratio. Furthermore, CNN-based and hybrid models outperform transformers in data-limited scenarios, particularly when leveraging multiscale feature aggregation. This review charts a path toward advancing liver tumor segmentation in Computed Tomography (CT) scans with cost-efficient, high-performance DL approaches by synthesizing these findings. © 2024 IEEE.

关键词： Convolutional neural networks

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A Dataset of Contractual Events in Court Decisions 39

A Dataset of Contractual Events in Court Decisions

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39th International Conference on Logic Programming Workshops, ICLP Workshops 2023

作者： Paulino-Passos, Guilherme Satoh, Ken Toni, Francesca Department of Computing Imperial College London United Kingdom Principles of Informatics Research Division National Institute of Informatics Tokyo Japan

The promise of automation of legal reasoning is developing technology that reduces human time required for legal tasks or that improves human performance on such tasks. In order to do so, different methods and systems based on logic programming were developed. However, in order to apply such methods on legal data, it is necessary to provide an interface between human users and the legal reasoning system, and the most natural interface in the legal domain is natural language, in particular, written text. In order to perform reasoning in written text using logic programming methods, it is then necessary to map expressions in text to atoms and predicates in the formal language, a task referred generally as information extraction. In this work, we propose a new dataset for the task of information extraction, in particular event extraction, in court decisions, focusing on contracts. Our dataset captures contractual relations and events that affect them in some way, such as negotiations preceding a (possible) contract, the execution of a contract, or its termination. We conducted text annotation with law students and graduates, resulting in a dataset with 207 documents, 3934 sentences, 4440 entities, and 1794 events. We describe here this resource, the annotation process, its evaluation with inter-annotator agreement metrics, and discuss challenges during the development of this resource and for the future. 2023 Copyright for this paper by its authors.

关键词： Logic programming

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Global ranking of the sensitivity of interaction potential contributions within classical molecular dynamics force fields

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npj Computational Materials 2024年第1期10卷 2347-2359页

作者： Wouter Edeling Maxime Vassaux Yiming Yang Shunzhou Wan Serge Guillas Peter V.Coveney Scientific Computing Group Centrum Wiskunde&InformaticaAmsterdamThe Netherlands Universitéde Rennes CNRSInstitut de Physique de RennesUMR 6251Rennes 35000France Department of Statistical Science University College LondonLondonUnited Kingdom Centre for Computational Science University College LondonLondonUnited Kingdom Advanced Research Computing Centre University College LondonLondonUnited Kingdom Informatics Institute University of AmsterdamAmsterdamThe Netherlands

Uncertainty quantification(UQ)is rapidly becoming a sine qua non for all forms of computational science out of which actionable outcomes are *** of the microscopic world of atoms and molecules has remained immune to these developments but due to the fundamental problems of reproducibility and reliability,it is essential that practitioners pay attention to the issues *** aUQstudy is undertaken of classical molecular dynamics with a particular focus on uncertainties in the high-dimensional force-field parameters,which affect key quantities of interest,including material properties and binding free energy predictions in drug discovery and personalized *** scalable UQ methods based on active subspaces that invoke machine learning and Gaussian processes,the sensitivity of the input parameters is *** analyses reveal that the prediction uncertainty is dominated by a small number of the hundreds of interaction potential parameters within the force fields *** ranking highlights what forms of interaction control the prediction uncertainty and enables systematic improvements to be made in future optimizations of such parameters.

关键词： interaction dynamics potential

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Point Biserial Correlation Coefficient on Climate Variables and Dengue Cases Using R Programming 1

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4th International Conference on Mathematics, Statistics, and computing Technology, ICMSCT 2023

作者： Zukarnain, Zuriani Ahmad Muhamad Krishnan, Nor Farisha Jamaludin, Marhainis Rahman, Noorihan Abdul Ahmad, Azlin College of Computing Informatics and Mathematics Universiti Teknologi MARA Cawangan Kelantan Kelantan Machang Malaysia Centre for Research in Data Science Universiti Teknologi PETRONAS Perak Seri Iskandar Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam Malaysia

ISBN: (数字)9789819734504

ISBN: (纸本)9789819734498

The number of people infected with dengue fever is on the increase across the world. Dengue fever is present in urban and semi-urban settings, and rural areas are also affected in certain nations. Dengue fever is affected by rain, relative humidity, temperature, and unplanned fast urbanization. This study focuses on Kota Bharu, aiming to identify whether the climate characteristics, including average temperature, mean relative humidity, and total rainfall, affect dengue cases. This study employed a point biserial correlation coefficient to see if the features correspond to the output. R programming was applied to check whether there was a correlation between dengue cases (yes/no) and climate parameters (average temperature, mean relative humidity, and rainfall). Point biserial correlation was used as the target variable for dichotomous variables. The methodology involved several steps, including data pre-processing, cleaning, and analysis. According to the findings, only mean relative humidity correlates with dengue cases in Kota Bharu. Since there is a negative correlation, dengue fever rises with low humidity. However, different regions might give different results of the correlation. Understanding the factors that lead to a rise in dengue cases and education initiatives can assist in enhancing a region’s early warning system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Rain

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Rielkies Nearby Sales Agents Finder Using Haversine Method

Rielkies Nearby Sales Agents Finder Using Haversine Method

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2023 IEEE International Conference on computing, ICOCO 2023

作者： Sulaiman, Mohd Suffian Aziz, Ahmad Ajad Azmi, Azri Derasit, Zuraidah Ismail, Azlan Nor Abdul Rahim, Siti Khatiiah College of Computing Informatics & Mathematics Universiti Teknologi Mara Malaysia Universiti Teknologi Malaysia Razak Faculty of Technology and Informatics Malaysia

ISBN: (纸本)9798350302684

With their new culinary products, Rielkies Choco jars, which come in a variety of flavors, the chocolate-based company Rielkies, which was created by one of Malaysia's most well-known actors, has been able to gain popularity in Malaysia. A system that enables Rielkies's customers to locate their preferred and reliable sales agents is crucial given the large number of people registered as their product sales agents in each state throughout Malaysia. Due to privacy and security concerns, many customers steer clear of doing business online. Many customers are also concerned with the sales representatives' delivery strategies because they often favor cash on delivery due to its security. The development of a web-based tool to locate salespeople nearby was suggested in this article. The tool would give customers or users access to the contact information of salespeople as well as information on their location and preferred method of delivery. The Haversine technique is chosen as the most appropriate algorithm to employ for this project to calculate the distance. The system's functions include locating local sales representatives for customers and managing sales representatives for admin to confirm the sales representatives to ensure they are reliable and secure. The result demonstrates that the system's functionality has been attained. To make their transactions more secure and simple than before, the project will assist customers in locating their favorite sales representatives. © 2023 IEEE.

关键词： Sales

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