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检索条件"任意字段=Israel Conference on Computer Systems and Software Engineering"

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API Adapter for Payment Gateway Variation Development in software Product Line engineering 13

API Adapter for Payment Gateway Variation Development in Sof...

引用

13th International conference on Advanced computer Science and Information systems (ICACSIS)

作者： Febrian, Samuel Tupa Komarudin, Oman Azurat, Ade Univ Indonesia Fac Comp Sci Depok Indonesia

ISBN: (纸本)9781665442640

A payment gateway is an e-commerce service that automatically processes and verifies money transactions. Many payment gateways can be integrated as a software feature, where each software product have their preferences. To accommodate that, we can use the software Product Line engineering (SPLE) paradigm, which maximizes the reusability and composition to develop a family of products with less production cost than conventional methods. We try to develop the payment gateway feature using SPLE-based development tools, which is ABS-Microservices Framework. We also develop the API Adapter during the development process, which is required to enable communication with the payment gateway provider. We then analyze our development by redeveloping the same features using the conventional method as a comparison. The analysis shows that the SPLE paradigm develops fewer lines of code than the conventional method, proving the production cost reduction, which is the benefit of the SPLE paradigm.

关键词： payment gateway software product line engineering effort API adapter

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Designing Internet of Behaviors systems 19

Designing Internet of Behaviors Systems

引用

19th IEEE International conference on software Architecture (ICSA)

作者： Moghaddam, Mahyar T. Muccini, Henry Dugdale, Julie Kjagaard, Mikkel Baun Univ Southern Denmark Odense Denmark Univ Aquila Laquila Italy Univ Grenoble Alps Grenoble France

ISBN: (纸本)9781665417280

The Internet of Behaviors (IoB) puts human behavior at the core of engineering intelligent connected systems. IoB links the digital world to human behavior to integrate human driven design, development, and adaptation processes. This paper defines the novel IoB concept with a constructed model based on a collective effort interacting with software engineers, human-computer interaction scientists, social scientists, and cognitive science communities. The model for IoB is created based on an exploratory study that synthesizes state-of-the-art analysis and experts interviews. The architecture of a real industry 4.0 manufacturing infrastructure helps to explain the IoB model and its application. The conceptual model was used to successfully implement a socio-technical infrastructure for a crowd monitoring and queue management system for the Uffizi Galleries, Florence, Italy. The experiment, which started in the fall of 2016 and was operational in the fall of 2018, used a data-driven approach to feed the system with real-time sensory data. It also incorporated prediction models on visitors' mobility behavior. The system's main objective was to capture human behavior, model it, and build a mechanism that considers changes, adapts in real-time, and continuously learns from repetitive behaviors. In addition to the conceptual model and the real-life evaluation, this paper provides recommendations from experts and gives future directions for IoB to become a significant technological advancement in the coming years.

关键词： IoB Intelligent systems IoT Human Behavior Modeling software engineering HCI HITL Cultural Heritage Crowd Management

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I-V Lissajous Pattern: a Promising Condition Monitoring Technique for High Voltage Assets 4

I-V Lissajous Pattern: a Promising Condition Monitoring Tech...

引用

4th International conference on High Voltage engineering and Power systems, ICHVEPS 2023

作者： Abu-Siada, Ahmed Suwarno, Suwarno Curtin University Electrical and Computer Engineering Discipline Perth Australia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350318678

The current-voltage (I-V) characteristics of critical high voltage assets such as power transformers, overhead transmission lines and underground cables are affected by various factors including the asset's health state along with other operating and environmental conditions. Understanding the current-voltage characteristics of such assets is essential for reliable and efficient operation of power transmission and distribution networks. The measurement of such parameters does not call for additional hardware as it utilises easily accessible voltage and current data at both terminals of the asset. The I-V characteristic can be considered as a unique fingerprint for the asset during its normal operation. variations in the fingerprint can be easily detected using a proper software code. The variation can be observed in real time and analysed using digital image processing and artificial intelligence-based techniques to identify and quantify any abnormal event or a fault at early stage. This paper discusses the potential of using the I-V Lissajous pattern to detect incipient faults and abnormal events of high voltage assets. Some case studies on power transformer and overhead transmission line are presented. Results show that I-V Lissajous pattern is a promising technique for real time asset management of high voltage critical equipment. © 2023 IEEE.

关键词： Power transformers

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Integrating Optimization Techniques in software Development Life Cycle - SLR

Integrating Optimization Techniques in Software Development ...

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International conference on Electrical, Communication, and computer engineering (ICECCE)

作者： Rawan Ali Mohammad Reza Bahrami Cyberphysical Systems Lab. Innopolis University Innopolis Russia Innopolis University Samarkand International University of Technology Samarkand Uzbekistan

ISBN: (数字)9798331529437

ISBN: (纸本)9798331529444

The software development life cycle (SDLC) is a structured process for delivering a high-quality product within a specified timeframe. Developing a cost-effective and efficient software product life cycle has always been a priority in software engineering, which can impact product quality. This study aims to provide an overview of the recent articles that focus on applying optimization techniques, mathematical models, and software cost estimation in the software development process and propose possible future directions. For the selected 29 studies, the development phase of the SDLC is most commonly focused on in studies. This emphasis highlights the pivotal role of optimization and mathematical modeling in enhancing software development efficiency.

关键词： Adaptation models Costs Computational modeling Estimation software Mathematical models software reliability Optimization software development management Systematic literature review

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Deep Learning-based Digital Twin for Human Activity Recognition 29

Deep Learning-based Digital Twin for Human Activity Recognit...

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29th IEEE International conference on Parallel and Distributed systems, ICPADS 2023

作者： Su, Jian Liao, Zhenlong Mao, Qiankun Sheng, Zhengguo Liu, Alex X. Nanjing University of Information Science and Technology The School of Software Nanjing China Zhejiang Wanli University The Hwamei College of Life and Health Sciences Ningbo China Nanjing University of Information Science and Technology The School of Computer Nanjing China University of Sussex The Department of Engineering and Design Brighton United Kingdom Michigan State University The Department of Computer Science and Engineering East Lansing United States

ISBN: (纸本)9798350330717

With the rapid development of the Internet of Things (IoT) related technologies, the application of digital twins (DT) in industry and healthcare becomes possible. Human activity recognition (HAR) is emerging as a hot research area with great potential in healthcare. Activity recognition systems combined with DT will make it easier to monitor human health conditions to improve the quality of life and happiness with individualized healthcare. In this paper, we design an effective HAR system, called HAR-Net, which uses WiFi time series data collected by sensors to train a deep learning network. Deep learning's great learning ability is utilized to extract features of various human activities for activity recognition. We built the DT system with Unity, which is combined with the HAR system. In the DT system, real-world physical activities are mapped onto human models. The results of activity prediction can be evaluated in real-time in DT, and warnings can be issued quickly when dangerous activities occur. To make our human activity recognition system more adaptive, we propose a one-shot recognition method based on meta-learning. Specifically, we design a Bi-path basic network that extracts features in the time-domain and frequency-domain, and a meta-learning framework with a classification module and a WiFi metric module. Using datasets from different environments, we conducted various experiments on HAR-Net, and the results proved that our presented method was superior to the baseline network. © 2023 IEEE.

关键词： Digital Twin Healthcare Human Activity Recognition Meta-Learning WiFi

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Sentiment Analysis of Covid-19 Twitter Data using Deep Learning Algorithm 2

Sentiment Analysis of Covid-19 Twitter Data using Deep Learn...

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2nd International conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Valarmathi, B. Gupta, N. Srinivasa Karthick, V. Chellatamilan, T. Santhi, K. Chalicheemala, Dhanush Department of Software and Systems Engineering School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Assistant Systems Engineer Tata Consultancy Services Chennai India Department of Analytics School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Information Technology School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

A key method used in the study of Natural Language Processing (NLP) is sentiment analysis, or emotion analysis, plays a pivotal role in text analysis. Its primary function is to discern and categorize the underlying emotions within textual content, classifying them as positive, neutral, or negative sentiments. A variety of textual inputs can be used with this process, including entire documents, individual sentences, and more. Understanding the sentiments expressed by individuals is of paramount importance to organizations in today's digital age. Clients and customers now have the means to express their thoughts and emotions with greater ease and immediacy than ever before. This wealth of sentiment data can offer valuable insights that organizations can leverage to enhance their products, services, and overall customer experience. The present study focuses on the sentiment analysis of Twitter data related to the COVID-19 pandemic, employing the Long Short-Term Memory (LSTM) algorithm. To improve the accuracy of sentiment analysis, a pre-processing procedure is introduced, which involves the use of the Neat Text module in Python to clean the tweets. In this research endeavor, a dataset comprising 1,79,107 COVID-19-related tweets is subjected to sentiment analysis using the proposed pre-processing module and LSTM. The results demonstrate an impressive accuracy rate of 96% in accurately determining the sentiments conveyed in these COVID-19 tweets. In contrast, the existing algorithm, based on Artificial Neural Network (ANN), achieved a significantly lower accuracy rate of 76%. This research not only showcases the effectiveness of LSTM and pre-processing in sentiment analysis but also highlights the significance of sentiment analysis in gaining valuable insights from vast amounts of textual data, especially when important events like the COVID-19 pandemic are involved. © 2024 Elsevier B.V.. All rights reserved.

关键词： COVID-19

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A Lightweight Approach for Detection of software Design Smells

A Lightweight Approach for Detection of Software Design Smel...

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International conference on Advancements in Computational Sciences (ICACS)

作者： Sabiyyah Sabir Ghulam Rasool Department of Computer Science COMSATS University Islamabad Lahore Campus Lahore Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

In software engineering, design smells can make software systems harder to maintain and lower their overall quality. Traditional methods, primarily focusing on code-level analysis, often miss design inconsistencies that manifest during the design phase. This paper introduces a light weight approach that leverages the Web Ontology Language (OWL) to detect design smells at the software design level. By incorporating ontological reasoning and automated checks against established design principles, the approach offers a proactive strategy for identifying and addressing design smells before they escalate into more significant issues in the implementation phase. We demonstrate the approach’s effectiveness through its application to several open-source Java projects, achieving notable precision and recall rates.

关键词： Java software maintenance software design OWL software quality software systems Cognition software reliability software engineering software development management

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Energy-saving Processors Two-phases Frequency Reduction Algorithm on Heterogeneous Embedded systems 10

Energy-saving Processors Two-phases Frequency Reduction Algo...

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10th IEEE International conference on Cyber Security and Cloud Computing and 9th IEEE International conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Huang, Weihong Jiang, Kuan Huang, Jing Lisi, Li Xiao, Yufeng Deng, Zihao Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Computer Science and Engineering Xiangtan411201 China The Bilingual Experimental School HNSDFZ Changsha410006 China

ISBN: (纸本)9798350312461

Energy saving has become a key issue for heterogeneous embedded systems. Previous energy-saving methods attempt to minimize the energy consumption of applications in heterogeneous embedded systems subject to deadline constraints by reducing the processor frequency. However, good scheduling strategy can also minimize energy consumption to some extent. This paper proposes a novel energy-saving scheduling algorithm, called the Energy-saving Processors Two-phases Frequency Reduction (EPTFR) Algorithm. In the first stage, within the deadline constraints, the maximum working frequency of each processor is reasonably and synchronously reduced;in the second phase, when running sub-applications on the processor, under the constraints of the earliest start time and latest end time of sub-applications, the actual operating frequency of the processor is reasonably reduced. Finally, the effectiveness of the EPTFR algorithm is verified through numerical experiments, and the results show that the proposed EPTFR algorithm can achieve a significant energy-saving effect. © 2023 IEEE.

关键词： Energy conservation

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Performance Evaluation of ECC based Cryptographic Accumulator on Resource-Constrained Platform

Performance Evaluation of ECC based Cryptographic Accumulato...

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2024 Innovations in Intelligent systems and Applications conference, ASYU 2024

作者： Toros, Armağan Çekiş, İsmet Kaan Korkmaz, Kübra Özçelik, İlker Computer Engineering Eskişehir Osmangazi University Eskişehir Turkey Software Engineering Eskişehir Osmangazi University Eskişehir Turkey

ISBN: (纸本)9798350379433

Cryptographic accumulators are efficient data structures used for membership testing in various applications, including resource-constrained devices like IoT systems. This paper explores the performance of an ECC-based dynamic cryptographic accumulator implemented on a Raspberry Pi. The study focuses on evaluating key functions (verification, witness generation, and insertion) essential for IoT environments with limited computational resources. The research finds that witness generation operates with O(n) complexity, highlighting the importance of considering element ID lengths to maintain efficiency. Batch insertion strategies demonstrate nearly O (1) complexity, significantly reducing overhead compared to individual insertions and crucial for minimizing operational delays in IoT deployments. Verification functions consistently operate in O (1) time, making them suitable for real-time IoT applications with minimal memory requirements. Empirical results demonstrate the feasibility of cryptographic accumulators in low-energy systems, emphasizing their potential to enhance data integrity and confidentiality in IoT environments. Future research should explore additive-based accumulator schemes to further optimize performance and reduce processing demands. This study provides empirical insights into adapting cryptographic accumulators for IoT devices, offering practical guidance on selecting suitable accumulator schemes and optimizing performance metrics critical for deploying secure and efficient IoT applications). © 2024 IEEE.

关键词： Digital storage

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MICSECS 2020 - Proceedings of the 12th Majorov International conference on software engineering and computer systems

MICSECS 2020 - Proceedings of the 12th Majorov International...

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12th Majorov International conference on software engineering and computer systems, MICSECS 2020

The proceedings contain 28 papers. The topics discussed include: inter-cluster redistribution of requests with redundancy depending on their criticality to delays;removal of complex image distortions via solving integral equations using the ‘spectral method’;logic graphs: complete, semantic-oriented and easy to learn visualization method for OWL DL language;two-phase model of information interaction in a heterogeneous internet of things network at the last mile;skin lesion analysis using ensemble of CNN with dermoscopic images and metadata;replication of requests when dividing cluster nodes between threads of different criticality to delays in queues;the effectiveness of using bell inequality test for information retrieval in Arabic texts;and intellectual method of program interactions visualization in Unix-like systems for information security purposes.

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