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AIMS Electronics and Electrical engineering 2023年第3期7卷 217-230页

作者： Alhakeem, Zaineb M. Hakim, Heba Hasan, Ola A. Laghari, Asif Ali Jumani, Awais Khan Jasm, Mohammed Nabil Chemical Engineering and Oil Refining Department Oil and Gas Engineering College Basrah University for Oil and Gas Basrah Iraq Computer Engineering Department Engineering College University of Basrah Basrah Iraq Real Estate Bank of Iraq Basrah Iraq Software college Shenyang Normal University Shenyang China School of Electronic and Information Engineering South China University of Technology Guangdong Guangzhou China Department of Computer Science ILMA University Karachi Sindh Pakistan Basra Oil Company Basrah Iraq Computer Technology Engineering Department Iraq University College Basrah Iraq

Over the past 20 years, there has been a surge of diabetes cases in Iraq. Blood tests administered in the absence of professional medical judgment have allowed for the early detection of diabetes, which will fasten disease detection and lower medical costs. This work focuses on the use of a Long-Short Term Memory (LSTM) neural network for diabetes classification in Iraq. Some medical tests and body features were used as classification features. The most relevant features were selected using the Binary Dragon Fly Algorithm (BDA) Binary version of the selection method because the features either selected or not. To reduce the number of features that are used in prediction,features without effects will be eliminated. This effects the classification accuracy, which is very important in both the computation time of the method and the cost of medical test that the individual will take during annual check *** work found out that among 11 features, only five features are most relevant to the disease. These features provide a classification accuracy up to 98% among three classes: diabetic, non diabetic and pre-diabetic. © 2023 the Author(s)

关键词： Long short-term memory

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DeepOCL:A deep neural network for Object Constraint Language generation from unrestricted nature language

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 250-263页

作者： Yilong Yang Yibo Liu Tianshu Bao Weiru Wang Nan Niu Yongfeng Yin School of Software Beihang UniversityBeijingChina College of Computer Science and Technology Guizhou UniversityGuiyangGuizhouChina Faculty of Information Technology Beijing University of TechnologyBeijingChina Department of Electrical Engineering and Computer Sciences University of CincinnatiCincinnatiOhioUSA

Object Constraint Language(OCL)is one kind of lightweight formal specification,which is widely used for software verification and validation in NASA and Object Management Group *** OCL provides a simple expressive syntax,it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first-order logic,which is approximately half accurate at the first stage of devel-opment.A deep neural network named DeepOCL is proposed,which takes the unre-stricted natural language as inputs and automatically outputs the best-scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule-based generation *** demonstrate the validity of our proposed approach,ablation experiments were conducted on a new sentence-aligned dataset named *** experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation,scored 74.30 on BLEU,and greatly outperformed experienced developers by 35.19%.The proposed approach is the first deep learning approach to generate the OCL expression from the natural *** can be further developed as a CASE tool for the software industry.

关键词： deep learning OCL software engineering

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Integrating Quantum Computing and Blockchain: Building the Foundations of Secure, Efficient 6G Technology 1

Integrating Quantum Computing and Blockchain: Building the F...

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1st ACM International Workshop on Quantum software engineering: The Next Evolution, QSE-NE 2024

作者： Zohaib, Muhammad Altuwaijri, Fahad S. Hyrynsalmi, Sami Department of Software Engineering LUT University Lahti Finland Department of Information Technology College of Computer Qassim University Buraydah Saudi Arabia

ISBN: (纸本)9798400706738

This research presents a modern framework that combine quantum computing and blockchain technologies to transform city management in provision for the 6G era. Quantum computing is recognized for its extraordinary processing power, while blockchain is known for its security, privacy, and transparency. these modern technologies can leverage from the 6G technologies capabilities like high speed, low latency, high bandwidth with giant connectivity. The idea of the study comes due to the few comprehensive standards and frameworks that facilitate the effective employment of these advanced technologies in the context of 6G. The proposed Quantum-Blockchain-6G (QBG) Framework main objective to leverage these emerging technologies with 6G capabilities to bridge the gap by providing the proper guidelines and framework to manage city management infrastructure with the help of efficient delivery of the required services. we used mixed method as interviews with expert, systematic literature review and case studies for this study to explore the challenges for integration of blockchain and quantum computing in 6g technology context and developed strategic framework for these challenges and evaluate its impact in the management activities in city management. This research will highlight critical challenges, relate to the quantum computing such as the complexity and cost and blockchain scalability. Furthermore, the study will investigate the integration the threads of advanced cryptographic measurement to mitigate quantum threats. This framework is precisely designed to empower cities management by utilizing the power of these emerging technologies that use 6G to meet the future connectivity demands in city management to make it smarter, faster, secure and trustworthy for the society. © 2024 Copyright held by the owner/author(s).

关键词： Blockchain

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A Pragmatic Decision Making Mechanism for Reusable Source Code Snippets Retrieval using Semantic Approach 19

A Pragmatic Decision Making Mechanism for Reusable Source Co...

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19th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2022

作者： Bibi, Nazia Rana, Tauseef Maqbool, Ayesha Qurat-Ul-Ain Department of Computer Software Engineering National University of Sciences and Technology Islamabad Pakistan Department of Computer Software Engineering NBC University of Sciences and Technology Islamabad Pakistan Air University Department of Computer Software Engineering Islamabad Pakistan

ISBN: (数字)9781665460514

ISBN: (纸本)9781665460514

Programmers frequently reuse exiting code available on internet sources like GitHub and Stack Overflow. Usually, programmers search for relevant/desired code by using natural language queries through search engines. However, the reusable code is very different from the normal textual searches. The main aim of code retrieval is to search for the most relevant snippet from a corpus of code snippets. The only way to efficiently retrieve the most relevant results is to eliminate the semantic gap between the code snippets and the user's query (Natural language description) search in the repository. Bridging this gap is an immense challenge. The primary objective of the research is to retrieve code snippets that are semantically relevant to the user query and to provide programmers with the ability to locate source code that they can use when developing new applications. The proposed approach is implemented using a web platform through which users can search source code. In this research, a semantic model for code retrieval is used which generates meanings or synonyms of the words. The proposed model integrates Ontologies and Natural Language Processing. The proposed approach is evaluated on the dataset extracted from Stack Overflow. The performance measures and classification accuracy are computed using Mean Average Precision. The retrieved results are ranked using Levenshtein similarity, demonstrating that our approach outperforms a robust component matching significantly. Our evaluation shows that the use of semantic matching leads to improve retrieval effectiveness. This study marks a substantial advancement in the integration of programming expertise with code retrieval techniques. Moreover, this system enables users to know when and how it is used for successful semantic searching. © 2022 IEEE.

关键词： Search engines

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Exploring the Impact of Data Augmentation Techniques on Emotional Speech Recognition 32

Exploring the Impact of Data Augmentation Techniques on Emot...

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32nd Telecommunications Forum, TELFOR 2024

作者： Galic, Jovan Sajic, Slavko Markovic, Branko University of Banja Luka Faculty of Electrical Engineering Department of Telecommunications Banja Luka Bosnia and Herzegovina University of Kragujevac Faculty of Technical Sciences Department of Computer and Software Engineering Čačak Serbia

ISBN: (纸本)9798350391053

Automatic Speech Recognition (ASR) systems are known to perform poorly in recognition of atypical speech, which certainly includes emotional speech. The labor-intensive nature of developing comprehensive speech databases for training purposes has led to the widespread adoption of synthetic speech data generation, utilizing existing natural speech, in numerous research studies. This paper examines the impact of standard data augmentation techniques, including pitch shifting, time stretching and volume adjustment on the accuracy of isolated-word recognizer of emotional speech. The experiments carried out indicate a significant increase in accuracy achieved through a single augmentation based on pitch-shifting for all emotional states. © 2024 IEEE.

关键词： Speech recognition

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Automatic Anomaly Monitoring in Public Surveillance Areas

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Intelligent Automation & Soft Computing 2023年第3期35卷 2655-2671页

作者： Mohammed Alarfaj Mahwish Pervaiz Yazeed Yasin Ghadi Tamara al Shloul Suliman A.Alsuhibany Ahmad Jalal Jeongmin Park Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Bahria UniversityIslamabadPakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Air UniversityIslamabadPakistan Department of Computer Engineering Korea Polytechnic University237 Sangidaehak-ro Siheung-siGyeonggi-do15073Korea

With the dramatic increase in video surveillance applications and public safety measures,the need for an accurate and effective system for abnormal/sus-picious activity classiﬁcation also *** it has multiple applications,the problem is very *** this paper,a novel approach for detecting nor-mal/abnormal activity has been *** used the Gaussian Mixture Model(GMM)and Kalmanﬁlter to detect and track the objects,*** that,we performed shadow removal to segment an object and its *** object segmentation we performed occlusion detection method to detect occlusion between multiple human silhouettes and we implemented a novel method for region shrinking to isolate occluded *** c-mean is utilized to verify human silhouettes and motion based features including velocity and opticalﬂow are extracted for each identiﬁed *** Wolf Optimizer(GWO)is used to optimize feature set followed by abnormal event classiﬁcation that is performed using the XG-Boost classiﬁ*** system is applicable in any surveillance appli-cation used for event detection or anomaly *** of proposed system is evaluated using University of Minnesota(UMN)dataset and UBI(Uni-versity of Beira Interior)-Fight dataset,each having different type of *** mean accuracy for the UMN and UBI-Fight datasets is 90.14%and 76.9%*** results are more accurate as compared to other existing methods.

关键词： Abnormal event classiﬁcation gray wolf optimizer region shrinking xg-boost classiﬁer

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Adaptive Climbing Strategy of Snake Robot Based on Compliance Control 4

Adaptive Climbing Strategy of Snake Robot Based on Complianc...

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4th International Symposium on Intelligent Robotics and Systems, ISoIRS 2024

作者： Yang, Huizhuo Dong, Jiyuan Wang, Meng Meng, Shiyong Yang, Lei Xue, Jiashuo Tiangong University School of Electronic and Information Engineering Tianjin China Tiangong University Department of Computer Science and Technology Tianjin China Tiangong University Department of Software Engineering Tianjin China

ISBN: (纸本)9798350364798

Snake robots, exhibiting a high degree of redundancy, are a class of biomimetic robots capable of forming a helical rolling gait for climbing trees and pipes. The surface structure of naturally grown trees is irregular, which may hinder the snake robots from achieving optimal surface conformation. Additionally, the presence of numerous branching structures in pipes introduces unpredictability in pipe climbing. To address these challenges, we propose an adaptive climbing strategy for snake robots based on compliant control. By adjusting a pre-set elasticity coefficient, the snake robot modulates the output torque of each joint, thereby altering the target angle of the joint. This adjustment enables the snake robot to adapt to unstructured environments. We conducted an experiment on climbing curved pipes to verify the effectiveness of this method. The result demonstrate that under unknown conditions, the robustness of the snake robot's climbing motion is enhanced by modifying the pre-set elasticity coefficient based on compliant control. This finding underscores the potential of compliant control in improving the adaptability and performance of Snake robots in complex environments. © 2024 IEEE.

关键词： Microrobots

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WIP: An Engaging Undergraduate Intro to Model Checking in software engineering Using TLA+ 54

WIP: An Engaging Undergraduate Intro to Model Checking in So...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Loyola University Software and Systems Laboratory Department of Computer Science Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

ISBN: (纸本)9798350351507

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive 'failuresy' through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and

关键词： Students

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Accuracy and Interpretability: Developing a computer-Aided Diagnosis System for Pneumonia Detection in Chest X-Ray Images 2

Accuracy and Interpretability: Developing a Computer-Aided D...

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2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Mridha, Krishna Barman, Apu Chandra Biswas, Shekhar Sarkar, Shakil Biswas, Sunanda Priyok, Masrur Ahsan Marwadi University Computer Engineering Rajkot India Marwadi University Department of Pharmacy Rajkot India Brac University Computer Science and Engineering Bangladesh Tianjin University Software Engineering China

ISBN: (纸本)9798350347456

People of all ages can contract pneumonia, a deadly respiratory illness that is more common in underdeveloped countries. For successful treatment and higher survival rates, pneumonia must be accurately and quickly diagnosed. While chest X-ray imaging is a frequently used diagnostic technique for detecting pneumonia, its interpretation can be arbitrary and error-prone. In this study, we used a convolutional neural network (CNN) architecture to construct a computer-aided diagnostic system for pneumonia identification in chest X-ray images. Our dataset comprises 5,863 anterior-posterior view X-ray pictures that have been divided into two categories: normal and pneumonia. The photos were chosen from the Guangzhou Women and Children's Medical Center's pediatric patients between the ages of one and five, and they were first checked for quality control before being judged by two highly qualified doctors. A third expert also reviewed the assessment set to verify correctness. For the test set, our CNN model performed well, with 99% accuracy, 99% precision, 99.25% f1-score, and 98% specificity. To improve the interpretability of our model, we also included explainable AI techniques like Grad-CAM and Grad-CAM++. These approaches offer insights into CNN's decision-making process. Our computer-aided diagnosis system offers a trustworthy and unbiased method for detecting pneumonia in chest X-ray pictures, which can help with the quick identification and treatment of this potentially fatal condition. © 2023 IEEE.

关键词： Convolutional neural networks

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Dynamic Topology Management In Ad-Hoc Networks For Improved Performance 2

Dynamic Topology Management In Ad-Hoc Networks For Improved ...

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2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Anakath, A.S. Kannadasan, R. Margarat, G. Simi Pandian, A. Pasumpon Antony Sibiya Varghese, V. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology VIT University Tamil Nadu Vellore India Department of Computer Science and Engineering New Prince Shri Bhavani College of Engineering and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering CARE College of Engineering Trichy India Department of Artificial Intelligence and Data Science GRT Institute of Engineering and Technology Tamil Nadu Tiruttani India

ISBN: (纸本)9798350383867

Optimization in ad hoc networks is a highly specialized task because the structure of the network is loosely formed, and each node is independently responsible for its operation. In order to obtain a better result from this solely formed networks this report offer extensive Dynamic Topology Management (DTM) method. Dynamic routing protocols lager lines, dividend balancing, Life-saving administration, guarantee of reliability, cross-layer design, security aspects and the on-time monitoring and discovery of topology changes are the main objectives and steps to be accomplished. Real-time Location monitoring and forest structure discovery are made possible by employing adaptive routing protocols, namely Dynamic Source Routing(DSR) and Ad-Hoc On-Demand Distance Vector(AODV). Also, the algorithms are capable of making advance adjustments to routing routes and resource allocations drawn from the mobility patterns forecasting which is vital. Load balancing methods, which distribute traffic in a network evenly, enable the system to run efficiently and avoid problems caused by overloading. Algorithms that are energy-efficient and make the best use of energy resources having their topology's optimized are introduced to the streamlined energy distribution systems. These algorithms are focused on the node's energy level. Through fault tolerance techniques which recognize and handle failures in nodes and partitioned networks, connectedness activity is a continuous one. Through QoS perception, the network topology might automatically be tailored to conform to the given quality criteria, thus not restricting the choice for differing applications. The proposed could have defenses against adversary nodes and their potential DDoS attacks which will enhance network protection. Yet another advantage of an architectural style that promotes cross-layer collaboration is enhanced topology management which is the goal around which the functions of various levels of the protocol stack revolve

关键词： Decision making

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