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Green Measurements for Software Product Based on Sustainability Dimensions

computer Systems Science & engineering 2022年第4期41卷 271-288页

作者： Komeil Raisian Jamaiah Yahaya Aziz Deraman Department of Computer Isfahan(Khorasgan)BranchIslamic Azad UniversityIsfahanIran Faculty of Information Science and Technology Universiti Kebangsaan MalaysiaBangi43600SelangorMalaysia Faculty of Ocean Technology Engineering&Informatics Universiti Malaysia Terengganu21030TerengganuMalaysia

Software is a central component in the modern world and vastly affects the environment’s *** demand for energy and resource require-ments is rising when producing hardware and software *** study reveals that many studies focused on green hardware;however,limited efforts were made in the greenness of software *** software products are necessary to solve the issues and problems related to the long-term use of soft-ware,especially from a sustainability *** a proper mechanism for measuring the greenness of a particular software product executed in a speciﬁc environment,the mentioned beneﬁts will not be ***,there are not enough works to address this problem,and the green status of software products is uncertain and *** paper aims to identify the green measurements based on sustainable dimensions in a software *** second objective is to reveal the relationships between the elements and measurements through empirical *** study is conducted in two ***ﬁrst phase is the theoretical phase,where the main components,measurements and practices that inﬂuence the sustainability of a software product are identiﬁ*** second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achiev-ing green software *** study has revealed seven green measurements of software product:Productivity,Usability,Cost Reduction,Employee Support,Energy Efﬁciency,Resource Efﬁciency and Tool *** relationships are statistically signiﬁcant,with a signiﬁcance level of less than 0.01(p=0.000).Thus,the hypothesised relationships were all *** contributions of this study revolve around the research perspectives of the measurements to attain a green software product.

关键词： Green software product sustainability dimension empirical study green measurements

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Data Driven Traffic Density Monitoring: A UAV and ResNet50 Deep Learning Framework 21

Data Driven Traffic Density Monitoring: A UAV and ResNet50 D...

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21st IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2025

作者： Rubab, Saddaf Dahri, Fida Hussain Mustafa Abro, Ghulam E Tahir, Nooritawati Md Javed, Muhammad University of Sharjah College of Computing and Informatics Department of Computer Engineering Sharjah27272 United Arab Emirates Southeast University School of Computer Science and Engineering Nanjing China Interdisciplinary Research Centre for Aviation and Space Exploration Saudi Arabia College of Engineering Universiti Teknologi Mara School of Electrical Engineering Selangor Shah Alam Malaysia International Information Technology University Department of Cybersecurity Alamty Kazakhstan Donghua University College of Computer Science Department of Computer Science and Technology Shanghai200022 China

ISBN: (纸本)9798331522193

Urban traffic congestion necessitates innovative monitoring and control solutions. This study leverages UAV footage and deep learning techniques to classify and analyze traffic density levels autonomously. By employing a pre-trained ResN et50 model enhanced with additional layers, the research optimizes traffic density classification using UAV-captured data. A custom dataset of traffic scenarios in Dammam, Saudi Arabia, was developed, incorporating diverse conditions through advanced normalization and data augmentation techniques to improve resilience and robustness. The modified ResN et50 model demonstrated high classification accuracy across varied traffic scenarios, validating its reliability and scalability for real-world applications. Key findings include the superior adaptability of UAV-based monitoring for real-time urban traffic assessment and the enhanced classification precision achieved through model optimization. This research underscores the potential of integrating UAV technology with deep learning to advance urban traffic management and foster more efficient urban planning strategies. © 2025 IEEE.

关键词： Traffic congestion

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Dual-Band Planar Microstrip Monopole Antenna Design Using Multi-Objective Hybrid Optimization Algorithm

Dual-Band Planar Microstrip Monopole Antenna Design Using Mu...

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2023 Photonics and Electromagnetics Research Symposium, PIERS 2023

作者： Hosseini, V. Shapour, F. Pinho, P. Farhang, Y. Majidzadeh, K. Ghobadi, Ch. Nourinia, J. Barshandeh, S. Shokri, M. Amiri, Zh. Jalilirad, M. Kaboutari, K. Payame Noor University Department of Computer Engineering and Information Technology Tehran Iran Islamic Azad University Urmia Branch Computer Engineering Department Urmia Iran Instituto de Telecomunicações Aveiro Portugal University of Aveiro Department of Electronics Telecommunications and Informatics Aveiro Portugal Islamic Azad University Khoy Branch Department of Computer Engineering Khoy Iran Urmia University Department of Electrical Engineering Urmia Iran School of Engineering Department of Computer Science Afagh Higher Education Institute Urmia Iran

ISBN: (纸本)9798350312843

This research uses a new proposed multi-objective optimization algorithm that utilizes an untested combined chaotic map to integrate Customized Mutated PSO (CM-PSO) with a Modified Genetic Algorithm (MGA) to design an antenna with specific electromagnetic characteristics. The hybrid approach achieves preferred outcomes faster than PSO, CM-PSO, GA, and MGA by avoiding being trapped in local minimums. The proposed Metaheuristic Algorithm (MA) functionality has been authenticated successfully using Benchmark Functions (BFs) like Rastrigin Function (RaF), Ackley Function (AF), Rosenbrock Function (RoF), and Booth Function (BoF). Finally, the validity of the offered approach for electromagnetic applications is demonstrated by optimizing a dual-band planar microstrip monopole antenna with a simple structure, such that its optimized S11 be less than -10 dB at two frequency bands encompasses 2.4 to 2.484 and 5.15 to 5.825 GHz for Wireless Local Area Network (WLAN) with IEEE 802.11 standards. The proposed algorithm allows the optimization criteria to be customized. The optimization algorithm developed in MATLAB is used to determine the necessary parameter adjustments in order to achieve expected frequency bands using CM-PSO or an innovative MGA, while high-frequency and electromagnetic simulations are performed using computer Simulation technology (CST) Studio Suite. The dimensions of the proposed antenna's elements are critical input parameters of the algorithm, named decision variables. © 2023 IEEE.

关键词： Monopole antennas

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Crude Palm Oil Price Forecasting Based on ECoS-MARS: in Data Science Models 11

Crude Palm Oil Price Forecasting Based on ECoS-MARS: in Data...

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11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Al-Khowarizmi Ramlan, Fitria Wulandari Efendi, Syahril Lubis, Arif Ridho Riza, Ferdy Amrullah Sary, Yoshida Universitas Muhammadiyah Sumatera Utara Department of Information Technology Medan Indonesia National University Ireland College of Engineering and Informatics Galway Ireland Universitas Sumatera Utara Department of Computer Science Medan Indonesia Politeknik Negeri Medan Department of Computer Engineering & Informatics Medan Indonesia Universitas Muhammadiyah Sumatera Utara Department of Information System Medan Indonesia

ISBN: (纸本)9798350305968

The crude palm oil (CPO) industry is highly competitive due to fluctuating and unpredictable prices. To accurately predict future CPO prices, a forecasting technique is necessary. This can be achieved through various regression techniques and data mining approaches. This paper proposes a Multivariate Adaptive Regression Splines (MARS) model, which utilizes the ECoS machine learning algorithm to obtain optimal forecasting values. This research mainly focuses on forecasting CPO prices using the ECoS-MARS approach. The functional basis (BF) validation has yielded an accuracy of 0.0532%. Furthermore, validation has been conducted to achieve accurate forecasting values, resulting in an accuracy of 0.11714%. The best parameter combination for this forecasting model consists of a learning rate of 0.6 for both learning rates 1 and 2, a sensitivity threshold of 0.3, and an error threshold of 0.05. © 2023 IEEE.

关键词： Forecasting

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Sensitive Content Detection in Social Networks Using Deep Learning Models and Explainability Techniques

Sensitive Content Detection in Social Networks Using Deep Le...

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Big Data, Cloud Computing, Data Science & engineering (BCD)

作者： Isidoros Perikos Computer Engineering and Informatics Department University of Patras Patras Greece Electrical and Computer Engineering Dept. Computer Technology Institute and Press “Diophantus” University of Peloponnese Patras Greece

ISBN: (数字)9798350394191

ISBN: (纸本)9798350394207

In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this study explores new dimensions and methodologies for detecting sensitive content. We examine the temporal evolution of sensitive content, revealing how patterns shift over time, and address cross-linguistic challenges, emphasizing cultural and contextual nuances in detection. We employ advanced machine learning techniques, including deep learning models and BERT that improve the accuracy and robustness of the detection procedure. In the experimental study, BERT transformer reported the best performance in detecting sensitive content in text. Additionally, we incorporate explainability techniques such as LIME and SHAP to provide deeper insights into the model's decision-making processes, ensuring predictions are interpretable and reliable. Our work enhances the theoretical framework of sensitive content detection in social networks and provide methods that are accurate and scalable and can facilitate the creation of user-centric interaction that prioritize privacy and user experience.

关键词： Deep learning Privacy Sensitivity Accuracy Social networking (online) Decision making Predictive models Transformers User experience Cultural differences

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Machine Learning as the Shield: Mitigating ARP Poisoning Attacks in Software Defined Networks 25

Machine Learning as the Shield: Mitigating ARP Poisoning Att...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Alquran, Rabee Al Jamal, Mahmoud Aljaidi, Mohammad Al-Jamal, Mohammad Khassawneh, Bashar Alsarhan, Ayoub Alidmat, Omar Samara, Ghassan Almatarneh, Sattam The Hashemite University Faculty of Prince Al-Hussien bin Abdullah for It Department of Information Technology Zarqa Jordan Irbid National University Department of Cybersecurity Irbid Jordan Zarqa University Department of Computer Science Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Yarmouk University Department of Statistics Irbid Jordan Amman Arab University Faculty of Computer Science and Informatics Department of Computer Science Amman Jordan Zarqa University Department of Computer Science Zarqa Jordan Zarqa University Department of Artificial Intelligence Zarqa Jordan

ISBN: (纸本)9798331540012

Software-defined networking (SDN) revolutionizes network management by centralizing control, but this centralization also introduces notable vulnerabilities, especially Address Resolution Protocol (ARP) poisoning attacks. These attacks exploit the ARP protocol, redirecting network traffic to malicious destinations. This research provides a deep dive into the nuances of these threats within the SDN context, outlining their mechanisms and potential countermeasures. A significant highlight of this paper is exploring Machine Learning (ML) as a pivotal mitigation approach. By analyzing and distinguishing between benign and malicious traffic patterns in real-time, ML models present a robust solution to enhance SDN security. The findings of our paper underscore the criticality of integrating these advanced predictive techniques in SDNs, paving the way for a safer and more resilient networking future. © 2024 IEEE.

关键词： ARP Poisoning Machine Learning (ML) Software-defined network (SDN)

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Blockchain Solution For SMEs Cybersecurity Threats In E-Commerce 1

Blockchain Solution For SMEs Cybersecurity Threats In E-Comm...

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1st International Conference on computer Science and Emerging Technologies, CSET 2023

作者： Zawaideh, Firas H. Abu-Ulbeh, Waheeb Mjlae, Salameh A. El-Ebiary, Yousef A. Baker Al Moaiad, Yazeed Das, Sunanda Irbid National University Faculty of Science and Informaiton Technology Department of Cyber Security Irbid Jordan Al-Istiqlal University Faculty of Administrative Sciences and Informatics Cybersecurity Department Palestine Palestine Prince Abdullah Bin Ghazi Faculty of Information Technology Cs Department Jordan UniSZA Faculty of Informatics and Computing Malaysia Mediu Faculty of Computer and Information Technology Malaysia School of Computer Science and Engineering Jain University Bangalore India

ISBN: (纸本)9798350341737

The rapid growth of electronic commerce (e-commerce) has revolutionized the way Small and Medium-sized Enterprises (SMEs) conduct business, enabling them to reach global markets and unlock new growth opportunities. However, this digital transformation has also exposed SMEs to an escalating array of cybersecurity threats that could compromise their data, financial integrity, and reputation. Blockchain technology, known for its decentralized and immutable nature, has emerged as a potential solution to enhance the security and resilience of e-commerce operations for SMEs. This research paper aims to investigate the current state of cybersecurity preparedness among SMEs engaged in e-commerce and identify the prevalent threats they face in the digital landscape. To achieve this goal, the study incorporates systematic literature review (SLR) method to examine the best technological solution to address the cybersecurity issues faced by e-commerce organizations in this paper of SMEs operating in e-commerce to gather data on their security practices, incident history, and perceptions of cybersecurity risks. In the context of this research, blockchain technology will be explored as a potential mechanism to enhance the security of e-commerce operations for SMEs. The inherent features of blockchain, such as decentralization, transparency, and immutability, could help protect sensitive data and thwart cyberattacks. By exploring the integration of blockchain into e-commerce systems, the research aims to shed light on the potential benefits and challenges associated with its adoption by SMEs. The research findings will not only shed light on the prevailing cybersecurity practices within SMEs and highlight their vulnerabilities but will also explore how blockchain technology can be leveraged to address these challenges. By understanding these patterns and exploring the feasibility of blockchain integration, the research aims to provide comprehensive recommendations for enhancing cy

关键词： Cybersecurity

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Predicting Carpark Prices Indices in Hong Kong Using AutoML

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computer Modeling in engineering & Sciences 2023年第3期134卷 2247-2282页

作者： Rita YiMan Li Lingxi Song Bo Li M.James C.Crabbe Xiao-Guang Yue Sustainable Real Estate Research Center Hong Kong Shue Yan UniversityHong Kong999077China Chakrabongse Bhuvanarth International Institute for Interdisciplinary Studies Rajamangala University of Technology Tawan-OkBangkok10400Thailand Zhongyuan Region Company Jinke Property Group Co.Ltd.Zhengzhou450000China Wolfson College Oxford UniversityOxfordOX26UDUK Institute of Biomedical and Environmental Science&Technology University of BedfordshireLutonLU13JUUK School of Life Sciences Shanxi UniversityTaiyuan030006China Department of Computer Science and Engineering European University CyprusNicosia1516Cyprus

The aims of this study were threefold:1)study the research gap in carpark and price index via big data and natural language processing,2)examine the research gap of carpark indices,and 3)construct carpark price indices via repeat sales methods and predict carpark indices via the *** researching the keyword“carpark”in Google Scholar,the largest electronic academic database that coversWeb of Science and Scopus indexed articles,this study obtained 999 articles and book chapters from 1910 to *** confirmed that most carpark research threw light on multi-storey carparks,management and ventilation systems,and reinforced concrete *** most common research method was case *** price index research,many previous studies focused on consumer,stock,press and futures,with many keywords being related to finance and *** indicated that there is no research predicting carpark price indices based on an AutoML *** study constructed repeat sales indices for 18 districts in Hong Kong by using 34,562 carpark transaction records from December 2009 to June ***’s carpark price was about four times that of Yuen Long’s carpark price,indicating the considerable carpark price differences inHong *** research evidenced the features that affected the carpark price indices models most:gold price ranked the first in all 19 models;oil price or Link stock price ranked second depending on the district,and carpark affordability ranked third.

关键词： Carpark repeat sales index AutoML Hong Kong natural language processing tokenization

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Correlation Mitigation Schemes for Index-Modulated Fluid Antenna Systems

Correlation Mitigation Schemes for Index-Modulated Fluid Ant...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Elio Faddoul Yuan Guo Ghassan M. Kraidy Constantinos Psomas Ioannis Krikidis Department of Electrical and Computer Engineering University of Cyprus Cyprus Department of Electronic Systems Norwegian University of Science and Technology Gjøvik Norway

In this paper, we investigate the use of index-modulated (IM) transmissions within the framework of fluid antenna (FA) systems, where an FA port is activated during each transmission interval. The adoption of this approach is motivated by the common physical characteristic exhibited by both FAs and IM transmissions, which entails the use of a single radio-frequency (RF) chain. From this perspective, we derive a closed-form expression for the bit error rate (BER) of IM-FA systems in the presence of spatial correlation. Our results demonstrate that IM-FAs outperform conventional IM systems. Since the FA ports are relatively close to each other, we focus on correlation mitigation techniques to improve performance. Specifically, we first investigate two port selection strategies, namely the maximum norm-based and the Euclidean distance-based selection schemes, assuming full channel knowledge. Then, we introduce the concept of spatial set partition coding for IM-FAs to spatially separate the FA ports. Numerical results demonstrate that the performance of IM-FAs is further improved in the case of high correlation whenever we apply the proposed correlation mitigation strategies.

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Video Streaming QoS Analysis with TIPHON Standard NDNts 9

Video Streaming QoS Analysis with TIPHON Standard NDNts

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： J.d, I Made Aditya Putra Alifa, Lisdatul Fawwaz, Muhammad Hilmi Mauren Sibayak, Nissha Kinaya Mayasari, Ratna Arifin, Hasan Nur Ahdan, Syaiful Negara, Ridha Muldina Syambas, Nana Rachmana Bandung Institute of Technology Dept. of Telecommunication Engineering Bandung40132 Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung40132 Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia

ISBN: (纸本)9798350305029

Named data networks are a new concept in network architecture that can process data transmission by name. This concept can be utilized in the case of video streaming. TIPHON is a standard used to support streaming multimedia activities. According to TIPHON, three factors-delay, packet loss, and throughput-can influence how a stream behaves. This study's goal is to evaluate the quality of service (QoS) of video streaming services using an NDN network that adheres to the TIPHON NDN standard. Several things can affect throughput, such as bottlenecks on the computer or network device used. © 2023 IEEE.

关键词： Quality control

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