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Framework for Effective Utilization of Distributed Scrum in Software Projects

computer Systems Science & engineering 2023年第1期44卷 407-422页

作者： Basit Shahzad Wardah Naeem Awan Fazal-e-Amin Ahsanullah Abro Muhammad Shoaib Sultan Alyahya Department of Software Engineering National University of Modern LanguagesIslamabad44000Pakistan Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Science Sukkur IBA UniversitySindh65200Pakistan Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

There is an emerging interest in using agile methodologies in Global Software Development(GSD)to get the mutual benefits of both *** is currently admired by many development teams as an agile most known meth-odology and considered adequate for collocated *** the same time,stake-holders in GSD are dispersed by geographical,temporal,and socio-cultural *** to the controversial nature of Scrum and GSD,many significant challenges arise that might restrict the use of Scrum in *** conducted a Sys-tematic Literature Review(SLR)by following Kitchenham guidelines to identify the challenges that limit the use of Scrum in GSD and to explore the mitigation strategies adopted by practitioners to resolve the *** validate our reviewfindings,we conducted an industrial survey of 305 *** results of our study are consolidated into a research *** framework represents current best practices and recommendations to mitigate the identified distributed scrum challenges and is validated byfive experts of distributed *** of the expert review were found supportive,reflecting that the framework will help the stakeholders deliver sustainable products by effectively mitigating the identified challenges.

关键词： Global software development distributed Scrum sustainable development challenges mitigation strategies

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Real-Time Safety Monitoring for Construction Sites Using RFID and Visual Recognition Technologies 1

Real-Time Safety Monitoring for Construction Sites Using RFI...

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1st International Conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Thaleeparambil, Noeal Rajeev Biju, Abiya Krishna, Deva Prathap, Boppuru Rudra Rekha, V. Reddy, Vandana Department of Computer Science and Engineering Bengaluru India M. S. Ramaiah University of Applied Sciences Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350355611

The integrated automated safety monitoring system for construction sites utilizes RFID, Wi-Fi, and vision-based recognition systems to enhance worker safety and ensure adherence to safety regulations. This system combines sophisticated components such as RFID tags and Raspberry Pi, solenoid locks, servo motors, and PIR sensors to provide an exhaustive solution. RFID technology is applied to assign unique tags to each worker, facilitating accurate tracking and identification The Wi-Fi and visual recognition components improve the system's functionalities, enabling wireless connectivity instantaneous data transmission, and verification of appropriate safety gear application. Solenoid locks and servo motors ensure regulated access to hazardous areas, responding to authenticated safety compliance records. PIR sensors sense motion, differentiating between authentic presence and mere nearness. The methodology outlines the necessary hardware and software criteria, procedures for system initialization, evaluation phases, server connectivity setup, access control enactment, and session closure protocols. It details the seamless integration and verification of hardware components, backend connectivity, identity and safety adherence verification, data encoding, and session termination processes. This research aims to upgrade safety surveillance in construction environments, boosting productivity, accuracy, and security. It also underscores the need for further adaptability to various construction settings to advance greater uptake and continuous improvement in workplace safety protocols. © 2025 IEEE.

关键词： Radio frequency identification (RFID)

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Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

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computers, Materials & Continua 2024年第1期78卷 357-374页

作者： Ch Avais Hanif Muhammad Ali Mughal Muhammad Attique Khan Nouf Abdullah Almujally Taerang Kim Jae-Hyuk Cha Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

The demand for a non-contact biometric approach for candidate identification has grown over the past ten *** on the most important biometric application,human gait analysis is a significant research topic in computer *** have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far *** recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access *** systems require a complex combination of technical,operational,and definitional *** employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked *** proposes a novel deep learning-based framework for human gait classification in video *** framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing *** proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer ***,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PSO)***,the best features are selected from both trained models using the Harris Hawks controlled Sine-Cosine optimization *** algorithm chooses the best features,combined in a novel correlation-based fusion ***,the fused best features are categorized using medium,bi-layer,and tri-layered neural *** the publicly accessible dataset known as the CASIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was *** achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this wor

关键词： Gait recognition covariant factors biometric deep learning fusion feature selection

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Holistic Analysis and Development of a Pregnancy Risk Detection Framework: Unveiling Predictive Insights Beyond Random Forest

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SN computer Science 2024年第8期5卷 1074页

作者： Irfan, Neha Zafar, Sherin Hussain, Imran Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India

This paper presents a cutting-edge framework for predicting psychological health risks in pregnant women, supported by robust analytics and a user-friendly application interface. Utilizing a dataset of 1504 postpartum women, state-of-the-art machine learning algorithms, particularly Random Forest, achieved an impressive accuracy score of 0.7508. This underscores the framework's effectiveness in identifying psychological health risks with high precision. Beyond traditional accuracy metrics, the study adopts a comprehensive approach to performance evaluation, incorporating precision, recall, and F1 score to provide a nuanced understanding of classifier performance, essential for informed decision-making in healthcare settings. The primary goal is to establish a seamless computerized prediction pathway, enabling healthcare providers to proactively address mental well-being in pregnant women. The framework encompasses several key stages, including meticulous data collection, rigorous preprocessing, strategic feature selection, and algorithmic selection. Advanced data preprocessing techniques, such as outlier removal and null value elimination, were employed to enhance data quality and reliability. Feature selection focused on identifying pivotal attributes for precise prediction of psychological health risks, optimizing model efficacy. A distinguishing aspect of this research is its emphasis on user-centric application development. The bespoke Women's Mental Health Tracker, crafted using Python's Tkinter library, boasts a user-friendly interface with personalized recommendations, weekly progress tracking, access to a rich resource library, community support, reminders, and notifications. This empowers pregnant women to manage their mental well-being proactively with ease and confidence. Attribute analysis highlights critical psychological health indicators, including feelings of sadness, irritability, sleep disturbances, concentration issues, overeating, and anxiety. Wh

关键词： Feature selection Maternal mental health Predictive analytics Pregnancy risk detection Proactive mental health management Psychological health risks User- friendly application interface Women’s Mental Health Tracker

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IoT Smart Devices Risk Assessment Model Using Fuzzy Logic and PSO

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computers, Materials & Continua 2024年第2期78卷 2245-2267页

作者： Ashraf S.Mashaleh Noor Farizah Binti Ibrahim Mohammad Alauthman Mohammad Almseidin Amjad Gawanmeh School of Computer Sciences Universiti Sains MalaysiaPenangMalaysia Department Computer Center Al-Balqa Applied UniversitySaltJordan Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan Department of Computer Science Tafila Technical UniversityTafilaJordan College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Increasing Internet of Things(IoT)device connectivity makes botnet attacks more dangerous,carrying catastrophic *** IoT botnets evolve,their dynamic and multifaceted nature hampers conventional detection *** paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization(PSO)to address the risks associated with IoT *** logic addresses IoT threat uncertainties and ambiguities *** component settings are optimized using PSO to improve *** methodology allows for more complex thinking by transitioning from binary to continuous *** of expert inputs,PSO data-driven tunes rules and membership *** study presents a complete IoT botnet risk assessment *** methodology helps security teams allocate resources by categorizing threats as high,medium,or low *** study shows how CICIoT2023 can assess cyber *** research has implications beyond detection,as it provides a proactive approach to risk management and promotes the development of more secure IoT environments.

关键词： IoT botnet detection risk assessment fuzzy logic particle swarm optimization(PSO) cybersecurity interconnected devices

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Enhancing Data Aggregation in Cluster-Based Wireless Sensor Networks with LCSS: Longest Common Subsequence Empowerment 8th

Enhancing Data Aggregation in Cluster-Based Wireless Sensor ...

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8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024

作者： Jamil, Muhammad Farooq, Umer Tariq, Noshina Alwakid, Ghadah Humayun, Mamoona Khan, Nadia Department of Computer Science Abdul Wali Khan University Mardan Pakistan Department of Computer Science National University of Computer and Emerging Sciences Islamabad Pakistan Department of Avionics Engineering Air University Islamabad Pakistan Department of Computer Science College of Computer and Information Sciences Jouf University Sakaka Al-Jouf Saudi Arabia Department of Information Systems College of Computer and Information Sciences Jouf University Sakaka Al-Jouf Saudi Arabia Institute of Computer Sciences and Information Technology Faculty of Management and Computer Sciences The University of Agriculture Peshawar Pakistan

ISBN: (纸本)9789819793266

A wireless sensor network (WSN) is a system of interconnected sensors that can gather environmental information. On the other hand, data redundancy is a common source of problems with WSNs. The literature presents a plethora of approaches. Despite these mechanisms’ best efforts, most current systems still need help with difficulties like noise, redundancy, or application specificity. Thus, we proposed an algorithm to overcome all the problems with redundant and highly correlated data. The longest common subsequence (LCSS)-enabled sliding window algorithm can resolve issues in constrained networks related to energy conservation and congestion control. The proposed method exhibits remarkable performance on multiple benchmark datasets. According to the result analysis, the suggested technique can outperform its equivalents for a range of data sets by about 32%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Congestion control (communication)

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Subject–Verb Agreement Error Handling Using RNN Architectures 4th

Subject–Verb Agreement Error Handling Using RNN Architectur...

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4th International Conference on Innovations in Computational Intelligence and computer Vision, ICICV 2024

作者： Gautam, Prakhar Thakur, Jitendra Singh Mishra, Ashish Department of Computer Science Engineering Jabalpur Engineering College Jabalpur India Department of Computer Science Engineering Gyan Ganga Institute of Technology and Sciences Jabalpur India

ISBN: (纸本)9789819769919

The domain of natural language processing has reached to a level where various tools are available for automatically identifying and correcting grammatical errors in a wide range of languages text. Though these tools are productive, it is still difficult to develop an effective and accurate grammatical error handling system. In this paper, we examine the efficacy of several neural network architectures with a particular focus on subject–verb agreement, a rule of English grammar. This work investigates the capabilities and performance of deep learning models using an annotated dataset designed specifically for English language subject–verb agreement issues. The strengths and weaknesses of well-known models, including Support Vector Machine (SVM), Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), and Transformers (BERT), are assessed through testing. The study sheds light on how the performances of these models differ from one another in detecting subject–verb agreement errors in English language sentences. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Mango Disease Detection Using Fused Vision Transformer with ConvNeXt Architecture

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computers, Materials & Continua 2025年第4期83卷 1023-1039页

作者： Faten S.Alamri Tariq Sadad Ahmed S.Almasoud Raja Atif Aurangzeb Amjad Khan Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science University of Engineering&TechnologyMardan23200Pakistan AIDA Lab Department of Information SystemsCollege of Computer&Information SciencesPrince Sultan UniversityRiyadh12435Saudi Arabia Department of Computer Science International Islamic UniversityIslamabad44000Pakistan

Mango farming significantly contributes to the economy,particularly in developing ***,mango trees are susceptible to various diseases caused by fungi,viruses,and bacteria,and diagnosing these diseases at an early stage is crucial to prevent their spread,which can lead to substantial *** development of deep learning models for detecting crop diseases is an active area of research in smart *** study focuses on mango plant diseases and employs the ConvNeXt and Vision Transformer(ViT)*** datasets were *** first,MangoLeafBD,contains data for mango leaf diseases such as anthracnose,bacterial canker,gall midge,and powdery *** second,SenMangoFruitDDS,includes data for mango fruit diseases such as Alternaria,Anthracnose,Black Mould Rot,Healthy,and Stem and *** datasets were obtained from publicly available *** proposed model achieved an accuracy of 99.87%on the MangoLeafBD dataset and 98.40%on the MangoFruitDDS *** results demonstrate that ConvNeXt and ViT models can effectively diagnose mango diseases,enabling farmers to identify these conditions more *** system contributes to increased mango production and minimizes economic losses by reducing the time and effort needed for manual ***,the proposed system is integrated into a mobile application that utilizes the model as a backend to detect mango diseases instantly.

关键词： ConvNeXt model fusion mango disease smart agriculture vision transformer

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Development of an Automated Service Level Agreement Negotiation Framework for SaaS Cloud E-Marketplace

Development of an Automated Service Level Agreement Negotiat...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Nnaji, Uche Azubuike, Ezenw Oke Adetiba, Emmanuel Akinola, Damola Department of Computer & Information Sciences Ota Nigeria Covenant University Department of Computer & Information Sciences Ota Nigeria Department of Electrical & Information Engineering Ota Nigeria

ISBN: (纸本)9798350358155

With the increasing number of Software-as-a-Service (SaaS) users, catering to their diverse needs while ensuring Quality of Service (QoS) has become imperative. Although SaaS providers regularly introduce new applications with varying offerings and QoS parameters, the current Cloud e-marketplace may overlook the individual QoS requirements of each user. To tackle this challenge, a Service Level Agreement (SLA) negotiation framework is employed for cloud service selection, ensuring SaaS user satisfaction, often facilitated by brokers. These brokers secure optimal offers from providers, taking into account the user's preferences. To initiate an agreement, brokers rank cloud providers, proceeding to negotiations only if the user rejects the top-rated provider's offer. Given the multitude of users and providers in today's cloud e-marketplace, selecting the most suitable provider and negotiating QoS parameters can be a complex task for brokers. This paper introduces a negotiation framework designed to enhance the customer satisfaction value for SaaS users through a service broker. Our proposed framework employs multi-agent systems (MAS) as the methodology, incorporating the level of competition, current negotiation time, and opportunities to formulate an improved negotiation model for SaaS users in the cloud marketplace. By adopting this proposed negotiation framework, SaaS users can acquire services from providers that precisely meet their requirements. Experimental results from simulations demonstrate that the proposed framework outperforms previous studies in terms of satisfaction level, response time, and negotiation success rate. © 2024 IEEE.

关键词： Marketplaces

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A Review of Spectrum Sharing in 6G for IoT Environment 2

A Review of Spectrum Sharing in 6G for IoT Environment

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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Khan, Andleeb Nand, Parma Bhushan, Bharat Alazzawi, Esraa Mohammed Jamil, Akhtar Sharda School of Engineering & Technology Department of Computer Science & Engineering UP Greater Noida India University of Baghdad Al-Jadriya Department of Computer Engineering Baghdad10071 Iraq National University of Computer and Emerging Sciences Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798331529529

With increase in demand the resources have proven to be limited. Spectrum sharing is a way to use the limited resources to their full potential. These can exceptionally improve the way IoT devices work. The ever-increasing demand in communication can be revolutionized by 6G network as it proves to be superior in terms of latency, reliability, data rates, connectivity and coverage. Hence the concept of spectrum sharing in 6G holds a great prospect for the future. This paper reviews the recent advances in the field of spectrum sharing for 6G in the IoT environment. It lays down the important techniques and the security and privacy concerns in IoT environments. It further lays down the important future prospects in terms of mm Wave, THz and optical spectrum and their most important use cases. © 2024 IEEE.

关键词： Terahertz waves

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