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4th International Conference on Advancements in Computing, ICAC 2022

作者： Attanayaka, Buddhima Nawinna, Dasuni Manathunga, Kalpani Abeygunawardhana, Pradeep K.W. Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Systems & Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

Requirement elicitation (RE) is a cognitively challenging and time-consuming task in software development due to the numerous challenges associated with it including conflicting requirements, unspoken, or assumed requirements, difficulty meeting with relevant stakeholders, stakeholder resistance to change, and not enough time set aside for meetings with all stakeholders. The prime causes of software implementation failure have been identified as inadequacies in the treatment of requirements. Without collecting the quality requirement, cannot achieve the goal of a quality software product. Through identifying the success factors affecting requirement elicitation, the paths to the quality requirements can be identified. The success factors identify through this research are experience, business analyst skills, stakeholder relationship, organizational elicitation process. This study aims to identify the factors affecting requirement elicitation based on the data collected from business analysts and similar positions in the software industry through a survey, interviews, and analyzed data to provide the initial validation for the identified factors. Through the analysis, we identified the main factors affecting successful requirement elicitation with a perfect significance value of less than 0.05 for all factors. © 2022 IEEE.

关键词： Requirements engineering

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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling

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Environment International 2025年 199卷 109496页

作者： Ahmed, Maqsood Zhang, Xiang Shen, Yonglin Ahmed, Tanveer Ali, Shahid Ali, Ayaz Gulakhmadov, Aminjon Nam, Won-Ho Chen, Nengcheng National Engineering Research Center of Geographic Information System School of Geography and Information Engineering China University of Geosciences Wuhan430074 China Department of Computer Science School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan Software College Northeastern University Shenyang110169 China Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Research Center of Ecology and Environment in Central Asia Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi830011 China Institute of Water Problems Hydropower and Ecology of the National Academy of Sciences of Tajikistan Dushanbe734042 Tajikistan School of Social Safety and Systems Engineering Institute of Agricultural Environmental Science National Agricultural Water Research Center Hankyong National University Anseong Korea Republic of

Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. However, existing research primarily focuses on single static image analysis, which does not account for the dynamic and temporal nature of air pollution. Meanwhile, research on video-based air quality estimation remains limited, particularly in achieving accurate multi-pollutant outputs. This study proposes Air Quality Prediction-Mamba (AQP-Mamba), a video-based deep learning model that integrates a structured Selective State Space Model (SSM) with a selective scan mechanism and a hybrid predictor (HP) to estimate air quality. The spatiotemporal forward and backward SSM dynamically adjusts parameters based on input, ensures linear complexity, and effectively captures long-range dependencies by bidirectional processing of spatiotemporal features through four scanning techniques (row-wise, column-wise, and their vertical reversals), which allows the model to accurately track pollutant concentrations and air quality variations over time. Thus, the model efficiently extracts spatiotemporal features from video and simultaneously performs regression (PM2.5, PM10, and AQI), and classification (AQI) tasks, respectively. A high-quality outdoor hourly air quality dataset (LMSAQV) with 13,176 videos collected from six monitoring stations in Lahore, Pakistan, was utilized as the case study. The experimental results demonstrate that the AQP-Mamba significantly outperforms several state-of-the-art models, including VideoSwin-T, VideoMAE, I3D, VTHCL, and TimeSformer. The proposed model achieves strong regression performance (PM2.5: R2 = 0.91, PM10: R2 = 0.90, AQI: R2 = 0.92) and excellent classification metrics: accuracy (94.57 %), precision (93.86 %), recall (94.20 %), and F1-score (93.44 %), respectively. The proposed model delivers consistent, real-time performance with a latency

关键词： Air quality

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PS2Way: An efficient pairwise search approach for test data generation

PS2Way: An efficient pairwise search approach for test data ...

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2nd International Conference on software engineering and computer systems, ICSECS 2011

作者： Khatun, Sabira Rabbi, Khandakar Fazley Yaakub, Che Yahaya Klaib, M.F.J. Masroor Ahmed, Mohammad Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia Faculty of Science and Information Technology Jadara University Jordan

ISBN: (纸本)9783642222023

Testing is a very important task to build error free software. Usually, the resources and time to market a software product is limited, hence, it is impossible to perform exhaustive test i.e., to test all combinations of input data. Pairwise (2way) test data generation approach supports higher reduction of exhaustive numbers as well as low cost and effective. In pairwise approach, most of the software faults are caused by unusual combination of input data. Hence, optimization in terms of number of generated test-cases and execution time is in demand. This paper proposes an enhanced pairwise search approach (PS2Way) of input values for optimum test data generation. This approach searches the most coverable pairs by pairing parameters and adopts one-test-at-a-time strategy to construct final test suites. PS2Way is effective in terms of number of generated test cases and execution time compared to other existing strategies. © 2011 Springer-Verlag.

关键词： software testing

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A Random search based effective algorithm for pairwise test data generation

A Random search based effective algorithm for pairwise test ...

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International Conference on Electrical, Control and computer engineering

作者： Khatun, S. Rabbi, K.F. Yaakub, C.Y. Klaib, M.F.J. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia Faculty of Science and Information Technology Jadara University Jordan

ISBN: (纸本)9781612842288

Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input data. To reduce the number of test cases in an acceptable level, it is preferable to use higher interaction level (t way, where t ≥ 2). Pairwise (2-way or t = 2) interaction can find most of the software faults. This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. Java program has been used to test the performance of the algorithm. The algorithm is able to support both uniform and non-uniform values effectively with performance better than the existing algorithms/tools in terms of number of generated test cases and time consumption. © 2011 IEEE.

关键词： software testing

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Weather Data Analysis Using Hadoop: Applications and Challenges

Weather Data Analysis Using Hadoop: Applications and Challen...

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International Conference on Green engineering Technology and Applied Computing 2019, IConGETech2 019 and International Conference on Applied Computing 2019, ICAC 2019

作者： Adam Ibrahim Fakherldin, Mohammed Adam, Khalid Akma Abu Bakar, Noor Abdul Majid, Mazlina Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Malaysia Faculty of Electric and Electronic Engineering Universiti Malaysia Pahang Malaysia Faculty of Computer Science and Information Systems Jazan University Malaysia

Weather data is very crucial in every aspect of human daily life. It plays an important role in many sectors such as agriculture, tourism, government planning, industry and so on. Weather has a variety of parameters like temperature, pressure, humidity and wind speed. The meteorological department deployed sensors for each weather parameter at different geographical locations to collect data. This data is stored mostly in the unstructured format. Thus, a big amount of data has been collected and archived. Therefore, storage and processing of this big data for accurate weather prediction is a huge challenge. Hadoop an apache product it used to support big data sets in a distributed environment. Hadoop has greatest advantages over scalable and fault-tolerant distributed processing technologies. This paper explains a system that uses the historical weather data of a region and apply the MapReduce and Hadoop techniques to analysis these historical data. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Digital storage

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Corrections to “An Ensemble Hybrid Framework: A Comparative Analysis of Metaheuristic Algorithms for Ensemble Hybrid CNN Features for Plants Disease Classification”

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IEEE Access 2025年 13卷 31659-31659页

作者： Khaoula Taji Ali Sohail Tariq Shahzad Bilal Shoaib Khan Muhammad Adnan Khan Khmaies Ouahada Electronic Systems Information Processing Mechanics and Energy Laboratory Kenitra Faculty of Sciences Ibn Tofail University Kenitra Morocco Department of Computer Science Minhaj University Lahore Lahore Pakistan Department of Electrical and Electronic Engineering Science University of Johannesburg Johannesburg South Africa Department of Computer Science Green International University Lahore Pakistan Department of Software Faculty of Artificial Intelligence and Software Gachon University Seongnam-si Republic of Korea

Presents corrections to the paper, Corrections to “An Ensemble Hybrid Framework: A Comparative Analysis of Metaheuristic Algorithms for Ensemble Hybrid CNN Features for Plants Disease Classification”.

关键词： Plant diseases Metaheuristics

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A new hybrid teaching learning based Optimization -Extreme learning Machine model based Intrusion-Detection system

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Materials Today: Proceedings 2023年 80卷 2701-2705页

作者： Qahatan Alsudani, Mustafa Abbdal Reflish, Salah H. Moorthy, Kohbalan Mundher Adnan, Myasar Computer Techniques Engineering Department Faculty of Information Technology Imam Ja'afar Al-sadiq University Najaf Iraq Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Kuantan Malaysia Islamic University Najaf Iraq Faculty of Engineering School of Computing Universiti Teknologi Malaysia Johor Bahru81310 Malaysia

Currently, effective Intrusion-detection systems (IDS) still represent one of the important security tools. However, hybrid models based on the IDS achieve better results compared with intrusion detection based on a single algorithm. But even so, the hybrid models based on traditional algorithms still face different limitations. This work is focused on providing two main goals;firstly, analysis based on the main methods and limitations of the most-recent hybrid model-based on intrusion detection, secondly, to propose a novel hybrid IDS model called TLBO-ELM based on the Firefly algorithm and Fast Learning Network. © 2021

关键词： Optimization

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Challenge-Response Emotion Authentication Algorithm Using Modified Horizontal Deep Learning

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Intelligent Automation & Soft Computing 2023年第3期35卷 3659-3675页

作者： Mohamed Ezz Ayman Mohamed Mostafa Ayman Elshenawy College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia Systems and Computers Engineering DEPT Faculty of EngineeringAl-Azhar UniversityCairo11651Egypt Software Engineering&Information Technology Faculty of Engineering&TechnologyEgyptian Chinese UniversityEgypt

Face authentication is an important biometric authentication method commonly used in security *** is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social media to perform spooﬁng attacks and dynamic movements for penetrating secur-ity *** paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble *** proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a speciﬁc response for every authentication trial with a different sequence of *** proposed model is applied to the KDEF dataset using 10-fold *** improvements are made to the proposed ***,the VGG16 model is applied to the seven common ***,the system usability is enhanced by analyzing and selecting only the four common and easy-to-use ***,the horizontal ensemble technique is applied to enhance the emotion recognition accuracy and minimize the error during authen-tication ***,the Horizontal Ensemble Best N-Losses(HEBNL)is applied using challenge-response emotion to improve the authentication efﬁ-ciency and minimize the computational *** successive improvements implemented on the proposed model led to an improvement in the accuracy from 92.1%to 99.27%.

关键词： Face authentication challenge-response authentication transfer learning and horizontal ensemble technique

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EasyA: Easy and effective way to generate pairwise test data

EasyA: Easy and effective way to generate pairwise test data

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International Conference on Computational Intelligence, Communication systems and Networks

作者： Rabbi, K.F. Khatun, S. Yaakub, C.Y. Klaib, M.F.J. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia Faculty of Science and Information Technology Jadara University Jordan

ISBN: (纸本)9780769544823

Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input data. To reduce the number of test cases in an acceptable level, it is preferable to use higher interaction level (t way, where t ≥ 2). Pairwise (2- way or t = 2) interaction can find most of the software faults. This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. Java program has been used to test the performance of the algorithm. The performance is better than the existing algorithms/tools in terms of number of generated test cases and time consumption. © 2011 IEEE.

关键词： software testing

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Cloud computing: Architecture for efficient provision of services

Cloud computing: Architecture for efficient provision of ser...

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2012 15th International Conference on Network-Based Information systems, NBIS 2012

作者： Khan, Nawsher Noraziah, A. Herawan, Tutut Ismail, Elrasheed Inayat, Zakira Faculty of Computer Systems and Software Engineering University Malaysia Pahang Kuantan Pahang Malaysia Faculty of Computer Science and Information Technology University of Engineering and Technology Peshawar Khyber Pakhtunkhwa Pakistan

ISBN: (纸本)9780769547794

Reliability, efficiency (in term of time consumption) and effectiveness in resources utilization are the desired quality attributes of Cloud Scheduling System, the main purpose of which is to execute jobs optimally, i.e. with minimum average waiting, turnaround and response time. Replication provides improved availability, decreased bandwidth use, increased fault tolerance, and improved scalability. To speed up access, file can be replicated so a user can access a nearby replica. In this paper, we propose architecture to convert Globally One Cloud to Locally Many Clouds. By combining replication and scheduling, this architecture will improve efficiency, accessibility and reliability. In the case of failure of one sub cloud or one cloud service, clients can start using another cloud under "failover" techniques. As a result, no one cloud service will go down. © 2012 IEEE.

关键词： Scheduling

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