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12th International Workshop on Quantitative Approaches to Software Quality, QuASoQ 2024

作者： Minhas, Nasir Mehmood Iqbal, Javed Khan, Saif Ur Rehman School of Innovation Design and Engineering Mälardalen University Västerås Sweden Department of Computer Science COMSATS University Islamabad Pakistan Department of Computing Shifa Tameer-e-Millat University Islamabad Pakistan

Integrating human values into software development, particularly in Requirements Engineering (RE), is essential for ensuring systems' alignment with stakeholder concerns, yet this area has not received due attention in research. To bridge this gap,this study presents a model based on Schwartz's value framework, focusing on incorporating the human value of’Power’ into the RE process. This model addresses five sub-values: preserving public image, social power, social recognition, authority, and wealth. Leveraging two focus-group sessions, the model integrates the sub-values of Power using 53 RE practices, 48 identified through a literature review and five from a survey with practitioners. These practices operationalize the sub-values ensuring that critical aspects like public image, recognition, and authority are addressed within the RE process. Preliminary evaluations by an expert panel indicate that the model is comprehensive, practical, and effective. Further validation through real-world testing will assess its impact on RE practices and outcomes. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Software design

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Detection of Leaf Diseases in Agricultural Plants Using Machine Learning

Detection of Leaf Diseases in Agricultural Plants Using Mach...

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2023 International Conference on computer, Electronics and Electrical Engineering and their Applications, IC2E3 2023

作者： Kholiya, Deepak Mishra, Amit Kumar Dumka, Ankur Pandey, Neeraj Kumar Tripathi, Neha Graphic Era Hill University School of Agriculture Dehradun India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India Women Institute of Technology Uttarakhand Dehradun India Dept. of Computer Science & Engineering Uttarakhand Dehradun India Dit University School of Computing Dehradun India

ISBN: (纸本)9798350338003

Identifying plant leaves early on is key to preventing catastrophic outbreaks. An important study area is automatic disease detection in plants. Fungi, bacteria, and viruses are the main culprits in most plant illnesses. Choosing a classification method is always challenging because the quality of the results can differ depending on the input data. A few examples of several classification techniques include K-Nearest Neighbour Classifier (KNN), Probabilistic Neural Network (PNN), Genetic Algorithm, Support Vector Machine (SVM) and Principal Component Analysis, Artificial Neural Network (ANN), and Fuzzy Logic. Classifications of plant leaf diseases have many uses in various industries, including agriculture and biological research. Pre-symptomatic diagnosis and crop health information can aid in the ability to manage pathogens through proper management approaches. Convolutional neural networks (CNNs) are the most widely used DL models for computer vision issues since they have proven very effective in tasks like picture categorization, object detection, image segmentation, etc. The experimental findings demonstrate the proposed model's superior performance to pre-trained models such as VGG16 and InceptionV3. The range of categorization accuracy is 76% to 100%, based on. © 2023 IEEE.

关键词： Image segmentation

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DC-Instruct: An Effective Framework for Generative Multi-intent Spoken Language Understanding

DC-Instruct: An Effective Framework for Generative Multi-int...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Xing, Bowen Liao, Lizi Huang, Minlie Tsang, Ivor W. Beijing Key Laboratory of Knowledge Engineering for Materials Science School of Computer and Communication Engineering University of Science and Technology Beijing China Singapore Management University Singapore Group Tsinghua University China CFAR and IHPC Agency for Science Technology and Research Singapore College of Computing and Data Science Nanyang Technological University Singapore

ISBN: (纸本)9798891761643

In the realm of multi-intent spoken language understanding, recent advancements have leveraged the potential of prompt learning frameworks. However, critical gaps exist in these frameworks: the lack of explicit modeling of dual-task dependencies and the oversight of task-specific semantic differences among utterances. To address these shortcomings, we propose DC-Instruct, a novel generative framework based on Dual-task Inter-dependent Instructions (DII) and Supervised Contrastive Instructions (SCI). Specifically, DII guides large language models (LLMs) to generate labels for one task based on the other task's labels, thereby explicitly capturing dual-task inter-dependencies. Moreover, SCI leverages utterance semantics differences by guiding LLMs to determine whether a pair of utterances share the same or similar labels. This can improve LLMs on extracting and discriminating task-specific semantics, thus enhancing their SLU reasoning abilities. Extensive experiments on public benchmark datasets show that DC-Instruct markedly outperforms current generative models and state-of-the-art methods, demonstrating its effectiveness in enhancing dialogue language understanding and reasoning. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Smart Health Diagnosis:Harnessing Data Mining for Predictive Healthcare

Smart Health Diagnosis:Harnessing Data Mining for Predictive...

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Advances in computing, Communication and Networking (ICAC2N), International Conference on

作者： R. Indrakumari Vishal Pandey Ashish Kumar Sinha Ankesh Kumar School of Computer Science & Engineering Galgotias University India School of Computing Application & Technology Galgotias University India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

The use of Smart Health Diagnosis: Data Mining for Predictive Healthcare is to provide a user- friendly and easily accessible platform where individuals can get instant health advice through an intelligent online healthcare system. By the analysis of the reported symptoms, the system can predict potential future diseases and provide relevant recommendations to healthcare providers on courses of action. Intelligent methods accurately determine potential interferences based on patient symptoms. Medical record database was used and symptoms were assigned to underlying diseases using Naive Bayesian calculations. Fast, reliable access to health care is a cornerstone of individual and social health but many people face barriers in receiving timely care. We are trying to solve these problems by introducing Health Prediction System, a revolutionary online healthcare solution that uses data mining for quick support and customized recommendations.

关键词： Databases Smart healthcare Prediction algorithms Bayes methods Data mining Reliability Medical diagnostic imaging Faces Diseases

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Bluetooth-based Voice-Activated Smart Home System using Arduino Uno for Cost-Effective Automation

Bluetooth-based Voice-Activated Smart Home System using Ardu...

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Trends in Material science and Inventive Materials (ICTMIM), International Conference on

作者： GuruPriya M Aravind S Gayathri R Department. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

The research introduces a cost-efficient voice-controlled home automation system based on products such as Arduino Uno and Bluetooth (HC-06) module. The main purpose of the system focuses on making home appliances accessible through voice commands for people who are elderly or physically challenged. The application proceeds by capturing audio from Android which converts voice to text command transmissions through Bluetooth to the Arduino for processing and appliance control procedures. The experimental tests proved the device’s capability to operate various devices reliably after receiving pre-defined instructions such as “ON”, “RED” and “OFF”. The research has confirmed that the operating system enables uninterrupted control along with restrained hardware necessities in confined systems. The main value of this work depends on its basic design requirements together with affordable cost and immediate functionality that operates independently of internet access or complex systems which support applications in regions with few resources. The presented solution fills the gap between hand-operated control systems and complete smart home integration by using voice detection and Bluetooth connections.

关键词： Home appliances Bluetooth Automation Operating systems Smart homes Speech recognition Control systems Security Reliability Older adults

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Security Defect Detection via Code Review: A Study of the OpenStack and Qt Communities 17

Security Defect Detection via Code Review: A Study of the Op...

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17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023

作者： Yu, Jiaxin Fu, Liming Liang, Peng Tahir, Amjed Shahin, Mojtaba School of Computer Science Wuhan University Wuhan China Hubei Luojia Laboratory Wuhan China School of Mathematical and Computational Sciences Massey University Palmerston North New Zealand School of Computing Technologies Rmit University Melbourne Australia

ISBN: (纸本)9781665452236

Background: Despite the widespread use of automated security defect detection tools, software projects still contain many security defects that could result in serious damage. Such tools are largely context-insensitive and may not cover all possible scenarios in testing potential issues, which makes them susceptible to missing complex security defects. Hence, thorough detection entails a synergistic cooperation between these tools and human-intensive detection techniques, including code review. Code review is widely recognized as a crucial and effective practice for identifying security defects. Aim: This work aims to empirically investigate security defect detection through code review. Method: To this end, we conducted an empirical study by analyzing code review comments derived from four projects in the OpenStack and Qt communities. Through manually checking 20,995 review comments obtained by keyword-based search, we identified 614 comments as security-related. Results: Our results show that (1) security defects are not prevalently discussed in code review, (2) more than half of the reviewers provided explicit fixing strategies/solutions to help developers fix security defects, (3) developers tend to follow reviewers' suggestions and action the changes, (4) Not worth fixing the defect now and Disagreement between the developer and the reviewer are the main causes for not resolving security defects. Conclusions: Our research results demonstrate that (1) software security practices should combine manual code review with automated detection tools, achieving a more comprehensive coverage to identifying and addressing security defects, and (2) promoting appropriate standardization of practitioners' behaviors during code review remains necessary for enhancing software security. © 2023 IEEE.

关键词： Defects

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DPTraj-PM: Differentially Private Trajectory Synthesis Using Prefix Tree and Markov Process

arXiv

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arXiv 2024年

作者： Wang, Nana Kankanhalli, Mohan Jiangsu Normal University School of Computer Science and Technology China National University of Singapore School of Computing Singapore

The increasing use of GPS-enabled devices has generated a large amount of trajectory data. These data offer us vital insights to understand the movements of individuals and populations, benefiting a broad range of applications from transportation planning to epidemic modeling. However, improper release of trajectory data is increasing concerns on individual privacy. Previous attempts either lack strong privacy guarantees, or fail to preserve sufficient basic characteristics of the original data. In this paper, we propose DPTraj-PM, a method to synthesize trajectory dataset under the differential privacy (DP) framework while ensures high data utility. Based on the assumption that an individual's trajectory could be mainly determined by the initial trajectory segment (which depicts the starting point and the initial direction) and the next location point, DPTraj-PM discretizes the raw trajectories into neighboring cells, and models them by combining a prefix tree structure and an m-order Markov process. After adding noise to the model under differential privacy, DPTraj-PM generates a synthetic dataset from the noisy model to enable a wider spectrum of data mining and modeling tasks. The output traces crafted by DPTraj-PM not only preserves the patterns and variability in individuals' mobility behaviors, but also protects individual privacy. Experiments on two real-world datasets demonstrate that DPTraj-PM substantially outperforms the state-of-the-art techniques in terms of data utility. Our code is available at https://***/wnn5/DP-PrefixTreeMarkov. Copyright © 2024, The Authors. All rights reserved.

关键词： Markov processes

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Harnessing Meta-Heuristic Algorithms to Optimize Travelling Salesman Problem

Harnessing Meta-Heuristic Algorithms to Optimize Travelling ...

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International Conference on computing and Networking Technology (ICCNT)

作者： Aryan Kothari V. R. N. S. Nikhil Namana Rohit Apurvanand Sahay Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India Department of Computer Science Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The Traveling Salesman Problem (TSP) is a challenging combinatorial optimization problem classified as NP-hard. This paper investigates the performance of various meta-heuristic algorithms, including Brute Force, Greedy, Dynamic Programming, Divide and Conquer, Simulated Annealing, Christofides, Lin-Kernighan-Helsgaun (LKH), Optimized LKH, Ant Colony Optimization, and Particle Swarm Optimization. The goal is to determine their effectiveness in solving large-scale TSP instances by focusing on solution quality and computational efficiency. Using a dataset of 256 cities, each algorithm was evaluated based on execution time and the cost of the final path. The Christofides algorithm proved the most balanced, with a time of 0.5027 seconds and a cost of 1321, making it the best in terms of cost efficiency. Simulated Annealing emerged as the fastest, completing in 0.095 seconds, while the Brute Force method, despite guaranteeing optimal solutions, was impractical for large datasets due to its exponential time complexity. The Greedy algorithm, although faster than some, often resulted in suboptimal solutions. This study underscores the importance of selecting the appropriate algorithm based on specific problem parameters and highlights the potential for future research in hybrid algorithms and parallel computing to further enhance performance.

关键词： Costs Heuristic algorithms Metaheuristics Force Urban areas Simulated annealing Traveling salesman problems Parallel processing Time complexity Particle swarm optimization

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RSMR: A Reliable and Sustainable Multi-Path Routing Scheme for Vehicle Electronics in Edge computing Networks

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IEEE Transactions on Consumer Electronics 2024年 1-1页

作者： Wang, Ye Gao, Honghao Xiang, Zhengzhe Zhu, Zhongzhi Al-Dulaimi, Anwer School of Computer Engineering and Science Shanghai University Shanghai China School of Computer and Computing Science Hangzhou City University Hangzhou China Senior Manager of Emerging technologies and Innovations and Distinguished Member of Technical Canada

Consumer electronic devices used to support data communication are integral components of vehicular networks. However, due to factors such as the limited reliability and failure of electronic devices, vehicle communication data may fail to be uploaded and downloaded in a timely manner, potentially leading to serious traffic accidents. With the emergence of edge computing technology, computing tasks are distributed from traditional centralized cloud computing to the network edge, thereby enabling faster response to the processing demands of vehicle data. However, even though edge computing offers faster data processing capabilities, the issue of effective routing of data within vehicular edge computing (VEC) networks remains to be addressed. Therefore, this paper proposes a two-phase multi-path routing scheme for VEC networks. In the route decision phase, the scheme introduces an integrated adaptive function, that plans the route reasonably by considering the transmission latency, energy balance and communication quality. On this basis, different routing requirements (e.g., maximizing network lifetime or transmission reliability) can be achieved by setting the weights of the proposed function. In the route maintenance phase, the scheme implements real-time multi-path adjustment based on the route maintenance mechanism to support data routing. The simulation results show that the proposed scheme has significant advantages over three baseline schemes in terms of routing reliability and energy balance. In addition, we explore the impacts of the weights and initial network configuration on the routing performance. The obtained results can provide guidance for planning reliable and sustainable routes. IEEE

关键词： Wireless sensor networks

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Creating a Virtual Literary Hub: Leveraging AWS for Deploying an Application in the Cloud

Creating a Virtual Literary Hub: Leveraging AWS for Deployin...

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Smart Systems for applications in Electrical sciences (ICSSES), International Conference on

作者： Mayank Pandey Naga Sai Shreya Kunda Pranave KC K Dinesh Kumar Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

Cloud computing has changed the way web applications work, making it easier to deploy them, scale them up or down, and keep them flexible, cost-effective, and available over the Internet. Because of this, many applications and services are moving from traditional physical servers to the cloud. Amazon Web Services (AWS) is a leading provider in the cloud computing space, offering various services that let users pay only for what they use. With AWS services such as EC2 (Elastic Cloud computing), S3 (Simple Storage Service), and CloudFront, users can easily build, launch, and manage web applications without spending much. This study will examine how to set up a fully functional web application in the cloud, focusing on efficiency, scalability, and flexibility.

关键词： Cloud computing Technological innovation Scalability Serverless computing Memory computer architecture Logic gates Smart systems Maintenance Service-oriented architecture

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