检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Ahmad, Johanna Saedudin, Rd. Rohmat Jie, Lim Jing Hassan, Rohayanti binti Kasim, Shahreen binti Telkom University Telekomunikasi Terusan Buah Batu Indonesia Bandung40257 Indonesia Department of Software Engineering Faculty of Computing Universiti Teknologi Malaysia UTM Skudai Johor81310 Malaysia Department of Information Security and Web Technology Faculty of Computing Science and Information Technology Universiti Tun Hussein Onn Malaysia UTHM Parit Raja Johor86400 Malaysia

This study is conducted in software testing based on the problem arising from mutation testing in Android applications. Although researchers show massive interest in searching for better Android testing approaches, there is still an insufficiency of usable and practical techniques to deliver a reasonable number of effective tests, especially in Android applications. Mutation testing injects code changes to check whether tests can identify the differences. Due to the challenges of the Android application, this research aimed to propose a set of mutation operators that can discover more faults and simulate more categories during the mutation testing processes. This study suggested an Android-based code annotation that combined Java code annotation and Android code annotation to generate more variety of mutant operators. These mutant operators were then merged with the mutant operators that had been developed earlier using the standard Android code testing. This improved set of mutant operators was tested using three different groups of Android applications: Insta Material, Telecine, and Leafpic. The proposed method generated fewer non-compliable mutants in the Leafpic application, with an average mutation score of 97.1% and more mutants in the Telecine application, with an average mutation score of 98.6%. In conclusion, the effectiveness of the improved mutation testing performance in Android applications was encouraging. The proposed method is likely to discover more bugs in Android applications and improve the overall effectiveness of mutation testing. © 2023, The Authors. All rights reserved.

关键词： software testing

来源：评论

学校读者我要写书评

暂无评论

A New Multi-Agent Feature Wrapper Machine Learning Approach for Heart Disease Diagnosis

引用

Computers, Materials & Continua 2021年第4期67卷 51-71页

作者： Mohamed Elhoseny Mazin Abed Mohammed Salama A.Mostafa Karrar Hameed Abdulkareem Mashael S.Maashi Begonya Garcia-Zapirain Ammar Awad Mutlag Marwah Suliman Maashi Department of Computer Science College of Computer Information TechnologyAmerican University in the Emirates503000United Arab Emirates College of Computer Science and Information Technology University of AnbarRamadi31001Iraq Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia College of Agriculture Al-Muthanna UniversitySamawah66001Iraq Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia eVIDA Lab University of DeustoBilbao48007Spain Department of Pure Science Ministry of EducationGeneral Directorate of CurriculaBaghdadIraq Department of Medical Laboratory Science Faculty of Applied Medical ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia

Heart disease(HD)is a serious widespread life-threatening *** heart of patients with HD fails to pump sufcient amounts of blood to the entire *** the occurrence of HD early and efciently may prevent the manifestation of the debilitating effects of this disease and aid in its effective *** methods for diagnosing HD are sometimes unreliable and insufcient in analyzing the related *** an alternative,noninvasive medical procedures based on machine learning(ML)methods provide reliable HD diagnosis and efcient prediction of HD ***,the existing models of automated ML-based HD diagnostic methods cannot satisfy clinical evaluation criteria because of their inability to recognize anomalies in extracted symptoms represented as classication features from patients with *** this study,we propose an automated heart disease diagnosis(AHDD)system that integrates a binary convolutional neural network(CNN)with a new multi-agent feature wrapper(MAFW)*** MAFW model consists of four software agents that operate a genetic algorithm(GA),a support vector machine(SVM),and Naïve Bayes(NB).The agents instruct the GA to perform a global search on HD features and adjust the weights of SVM and BN during initial classication.A nal tuning to CNN is then performed to ensure that the best set of features are included in HD *** CNN consists of ve layers that categorize patients as healthy or with HD according to the analysis of optimized HD *** evaluate the classication performance of the proposed AHDD system via 12 common ML techniques and conventional CNN models by using across-validation technique and by assessing six evaluation *** AHDD system achieves the highest accuracy of 90.1%,whereas the other ML and conventional CNN models attain only 72.3%–83.8%accuracy on ***,the AHDD system proposed herein has the highest capability to identify patients with *** system can be used by medical

关键词： Heart disease machine learning multi-agent feature wrapper model heart disease diagnosis HD cleveland datasets convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

ENCL: Empirical Evaluation of Consumer Behaviour Analysis Model Using Internet of Things (IoT) Based Enhanced Neural Classification Logic

ENCL: Empirical Evaluation of Consumer Behaviour Analysis Mo...

引用

Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： S. Sudha Merlin K. Malathy Ravi S Arun M Raut S.P H. Fawareh Department of Electrical and Electronics Engineering DMI College of Engineering Palanchur Chennai Department of MCA S.A. Engineering College Chennai Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai Dept of Computer Science and Engineering Kings College of Engineering Punalkulam Thanjavur Department of Civil Engineering Yeshwantrao Chavan College of Engineering Nagpur India Software Engineering Dept Faculty of Information Technology Zarqa University Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

The proliferation of consumer data can be attributed to “the Internet of Things (IoT),” which makes it easier to access and more detailed than before. In this research our purpose is to evaluate the effectiveness of a consumer behavior analysis model using data from IoT. The quality of the model is evaluated on multiple parameters - accuracy, predictability and business sense for marketing. It uses the analytics of huge amounts for data from IoT devices to predict patterns, customer preferences and trends. The proposed method called as Enhanced Neural Classification Logic (ENCL) is cross-validated with the already existing method, which is termed as Consumer behavior Forecasting Strategy (CBFS), and helps users to share gather or process information in a fast and cost-effective way through the proposed method. The results are useful to grasp the promise of IoT in more effective consumer behavior analysis. The research portrays the strengths, weaknesses and possible areas of improvement in this model which will be beneficial for both academic and industry practitioners. As such, the objective of this study is to show how an IoT-based consumer behavior analysis can increase business growth and customer satisfaction. The experimental evaluations demonstrate significant improvements in predictive performance over traditional methods, providing actionable insights for targeted marketing and strategic decision-making. The results highlight ENCL's potential to transform consumer behavior analysis by delivering more precise and nuanced understandings of market dynamics.

关键词： Analytical models Consumer behavior Accuracy Computational modeling Neural networks Predictive models Data models Internet of Things Logic Business

来源：评论

学校读者我要写书评

暂无评论

Design and Simulation of a Network Infrastructure for a Multi-Branch Organization Using Cisco Packet Tracer

Design and Simulation of a Network Infrastructure for a Mult...

引用

information technology (ACIT)

作者： Osama S AlJamal Mahmoud AlJamal Ayoub Alsarhan Mohammad Aljaidi Saif Okour Issa Al-Aiash Ahmad Al-Qerem Essam Al Daoud Ali Elrashidi Department of Computer Science Al Hussein Technical University Amman Jordan Department of Cybersecurity Faculty of Science and Information Technology Irbid National University Irbid Jordan Department of Information Technology The Hashemite University Zarqa Jordan Department of Computer Science Zarqa University Zarqa Jordan Department of Software Engineering Irbid National University Irbid Jordan Department of Cybersecurity Zarqa University Zarqa Jordan Department of Electrical Engineering University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Designing and simulating a network infrastructure for multi-branch organizations is essential for ensuring seamless connectivity and efficient operations. This paper addresses the challenges faced by organizations in maintaining consistent and reliable network connectivity across multiple locations, including managing network traffic, ensuring security, and optimizing resource allocation while keeping costs under control. The study presents a comprehensive methodology involving the conceptualization of network ideas, designing the network architecture, adding necessary devices and tools, configuring these devices according to the network topology, and troubleshooting to ensure optimal performance. Key elements such as VLANs, routers, switches, and routing protocols like RIP, OSPF, and EIGRP are incorporated, with the entire design and simulation conducted using Cisco Packet Tracer. The findings demonstrate that full connectivity between headquarters and branch sites can be achieved within a budget of $40,000. This paper provides a practical guide for implementing similar network projects, emphasizing the importance of detailed configurations and troubleshooting steps, and recommends adopting this methodology to enhance network infrastructure efficiently and cost-effectively.

关键词： Performance evaluation Costs Organizations Telecommunication traffic Network architecture Routing protocols Security Resource management Reliability information technology

来源：评论

学校读者我要写书评

暂无评论

Quantum-Computing for Corrosion Simulation and Prevention: Workflow and Resource Analysis

arXiv

引用

arXiv 2024年

作者： Nguyen, Nam Watts, Thomas W. Link, Benjamin Williams, Kristen S. Sanders, Yuval R. Elman, J. Kieferova, Maria Bremner, Michael J. Morrell, Kaitlyn J. Elenewski, Justin Isaacs, Eric B. Johnson, Samuel D. Mathieson, Luke Obenland, Kevin M. Otten, Matthew Sundareswara, Rashmi Holmes, Adam Centre for Quantum Computation and Communication Technology University of Technology SydneyNSW2007 Australia Applied Mathematics Boeing Research & Technology United States HRL Laboratories LLC MalibuCA United States Centre for Quantum Software and Information School of Computer Science Faculty of Engineering & Information Technology University of Technology SydneyNSW2007 Australia MIT Lincoln Laboratory LexingtonMA United States Department of Physics University of Wisconsin – Madison MadisonWI United States

Corrosion is a pervasive issue that impacts the structural integrity and performance of materials across various industries, imposing a significant economic impact globally. In fields like aerospace and defense, developing corrosion-resistant materials is critical, but progress is often hindered by the complexities of material-environment interactions. While computational methods have advanced in designing corrosion inhibitors and corrosion-resistant materials, they fall short in understanding the fundamental corrosion mechanisms due to the highly correlated nature of the systems involved. This paper explores the potential of leveraging quantum computing to accelerate the design of corrosion inhibitors and corrosion-resistant materials, with a particular focus on magnesium and niobium alloys. We investigate the quantum computing resources required for high-fidelity electronic ground-state energy estimation (GSEE), which will be used in our hybrid classical-quantum workflow. Representative computational models for magnesium and niobium alloys show that 2292 to 38598 logical qubits and (1.04 to 1962) × 1013 T-gates are required for simulating the ground-state energy of these systems under the first quantization encoding using plane waves basis. © 2024, CC BY.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

Classification of Depression Audio Data by Deep Learning

Classification of Depression Audio Data by Deep Learning

引用

Biomedical engineering International Conference (BMEiCON)

作者： Phanomkorn Homsiang Treesukon Treebupachatsakul Komsan Kiatrungrit Suvit Poomrittigul Department of Biomedical Engineering School of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand Department of Psychiatry Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Department of Software Engineering and Information System Faculty of Science and Technology Pathumwan Institute of Technology Bangkok Thailand

ISBN: (纸本)9781665489041

Due to many factors such as anxiety from contracting the disease and concern about the socioeconomic impacts, Thai people have accumulated stress and are at risk of depression. The diagnosis of depression can be primarily assessed by testing the assessments such as PHQ8, PHQ-9, and CES-D. The applied deep learning technology in medicine has received research interest and has been developing. In this research, we tried the classification of depression and non-depression audio datasets with the implementation of 4 model architectures: 1D CNN, 2D CNN, LSTM, and GRU. By converting wave audio format (WAV) of Daic-woz database to the Melfrequency cepstrum (MFC). We have done the training and evaluated the 4 model architectures and compared the results between non-augmented and augmented datasets. The highest accuracy was obtained from 1D CNN with a non-data augmentation of 95%, and a 2D CNN with a data augmentation of 75%. These results confirm that human voices can differentiate between depression and non-depression.

关键词： Deep learning Training Databases Anxiety disorders Cepstrum Depression Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial AI-Generated Content Empowered Healthcare Electronics

引用

IEEE Transactions on Consumer Electronics 2025年第1期71卷 1319-1321页

作者： Gwanggil Jeon Joel Rodrigues Shiping Wen Junxin Chen Nan Ji Abdellah Chehri Department of Embedded Systems Engineering Incheon National University Incheon South Korea Post-Graduation Program in Electrical Engineering Federal University of Piauí Teresina Brazil Instituto de Telecomunicações Universidade de Aveiro Aveiro Portugal Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia School of Software Dalian University of Technology Dalian China Hong Kong Centre for Cerebro-Cardiovascular Health Engineering City University of Hong Kong Hong Kong China Department of Mathematics and Computer Science Military College of Canada Kingston ON Canada

The rapid advancements in AI-Generated Content (AIGC) have revolutionized various domains, including consumer electronics and healthcare technologies. AIGC’s ability to generate high-quality text, images, and videos within seconds has reshaped human-computer interactions, from intelligent customer service to immersive virtual experiences. More importantly, its application in Healthcare Electronics (HE) has opened new frontiers, facilitating automated diagnostics, medical data synthesis, and intelligent healthcare predictions.

关键词： Special issues and sections Generative AI Medical services Artificial intelligence Medical diagnostic imaging Brain modeling Knowledge graphs Electroencephalography Wearable devices Electronic medical records

来源：评论

学校读者我要写书评

暂无评论

Conventional/Phase Shift Dual Drive Mach-Zehnder Modulation Measured Type Based Radio over Fiber Systems

引用

Journal of Optical Communications 2024年第s1期45卷 s123-s131页

作者： Amiri, I.S. Rashed, Ahmed Nabih Zaki Rahman, Ziaur Paul, Bikash Kumar Ahmed, Kawsar Computational Optics Research Group Advanced Institute of Materials Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City Viet Nam Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt School of Computer Science and Software Engineering RMIT University 414-418 Swanston Street MelbourneVIC3000 Australia Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Santosh Tangail1902 Bangladesh Group of Bio-photomatiχ Mawlana Bhashani Science and Technology University Santosh Tangail1902 Bangladesh Department of Software Engineering Daffodil International University Sukrabad Dhanmondi Dhaka1207 Bangladesh

This work clarified the conventional/phase shift dual Mach-Zehnder modulation measured technique for upgrading radio over fiber (ROF) systems. Four levels of pulse amplitude modulation and non-return to zero code scheme are employed in different previous studies for upgrading ROF systems. The possible transmission distance is extended to 150 km and a bit rate of 40 Gb/s for achieved acceptable max. Q factor of 13.7498 and minimum bit error rates of 1.82×10-43. The total optical received power is measured at fiber cable length for maximum distance. Also, in the same way, the signal power levels are measured after fiber optic cable and avalanche photo detector optical receiver. The proposed model has presented the enhancement percentage ratio of 13.654% over the previous models in signal quality enhancement. © 2020 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Q factor measurement

来源：评论

学校读者我要写书评

暂无评论

Fused Fuzzy Deep Learning and information Steganography for Privacy Preservation in Medical Consumer Electronics

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Chen, Jingxue Zhao, Pengbiao Deng, Erqiang Khan, Fazlullah Alturki, Ryan Alshawi, Bandar Xiong, Hu School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China the School of Computer Science Faculty of Science and Engineering University of Nottingham Ningbo China Zhejiang Ningbo315104 China the KKR and KSR institute of technology and sciences Andhra Pradesh Guntur India the Division of Research and Development Lovely Professional University Phagwara India the University Centre of Research and Development Chandigarh University Mohali India the Department of Computer and Network Engineering College of Computing Umm Al-Qura University Makkah Saudi Arabia the Department of Software Engineering College of Computing Umm Al-Qura University Makkah Saudi Arabia

—Medical Consumer Electronics (MCE) have greatly facilitated people’s lives, allowing patients to obtain personal medical information including medical images. These medical images obtained from MCE need to be processed using segmentation, diagnosis, recognition to obtain useful information. Deep learning plays an important role in medical image segmentation and recognition. However, other personal information about the patient, such as previous cases, is often required to determine the final diagnosis. However, sending personal information and medical images generated through MCE to the clinic directly exposes patient privacy. Therefore, in this paper, we propose a digital medical image privacy protection framework based on information steganography with fuzzy deep learning. The proposed framework transforms patient privacy information into invisible noise and hides it in the deep covert space of the image. This method plays a crucial role in ensuring patient privacy and data security. Furthermore, this method can ensure a high level of image segmentation accuracy that supports the development of personalized medical services. The experimental results show that the proposed framework can embed patient information in medical images without affecting the segmentation task, and effectively protect privacy. Finally, the proposed framework provides new possibilities and impetus for the popularization of MCE. © 2025 IEEE.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Robust Model Integral Predictive Control Design for Reference Tracking DC Servomechanism

Robust Model Integral Predictive Control Design for Referenc...

引用

IEEE International Conference on Intelligent Computing and information Systems (ICICIS)

作者： Khalil Mohamed Khalil Ayman Elshenawy Faculty of Engineering Al-Azhar University Cairo Egypt Software Engineering and Information Technology Faculty of Engineering and Technology Egyptian Chinese University Cairo Egypt

ISBN: (纸本)9781665411592

Model Predictive Control (MPC) has been very successful in the control industries due to its ability to handle uncertainty in physical systems with some constraints. Due to its higher power density, DC servomechanism is used in control systems of several industrial applications. However, the DC servomechanisms suffer severe throttling loss, leading to low effectiveness, and the uncertainty parameters and distortions caused by the changing system environment harm their performance. In this paper, a Robust Integral MPC (RIMPC) model is designed to enhance the efficiency of the DC servomechanism control system. Uncertainties and nonlinearity of the parameters are taken into consideration. In RIMPC, MPC is incorporated into the integral controller synthesis through an optimization problem subjected to some Linear Matrix Inequality (LMI) constraints to generate the control law of the servomechanism dynamics. The performance of the proposed system is evaluated in two cases: with no disturbances and when disturbances are affecting the system. The obtained results are analyzed and compared with other controllers' design, such as Proportional Integral Derivative (PID) controller and the Monte Carlo (MC) controller. The obtained results prove that the proposed system is more effective in cost function and transient performance (rise time, peak time, maximum overshoot, and settling-time), indicating a much better reference tracking accuracy and proposed method robustness.

关键词： Power system measurements Uncertainty Monte Carlo methods Predictive models Control systems Robustness Linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：