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Project Assessment in Offshore Software Maintenance Outsourcing Using Deep Extreme Learning Machines

computers, Materials & Continua 2023年第1期74卷 1871-1886页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Saqib Raza Ahmad Salman Khan Yasir Mahmood Nazri Kama Azri Azmi Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala NerusMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyahKuwait Department of Computer Science Sharif College of Engineering&TechnologyLahore54000Pakistan

Software maintenance is the process of fixing,modifying,and improving software deliverables after they are delivered to the *** can benefit from offshore software maintenance outsourcing(OSMO)in different ways,including time savings,cost savings,and improving the software quality and *** of the hardest challenges for the OSMO vendor is to choose a suitable project among several clients’*** goal of the current study is to recommend a machine learning-based decision support system that OSMO vendors can utilize to forecast or assess the project of OSMO *** projects belong to OSMO vendors,having offices in developing countries while providing services to developed *** the current study,Extreme Learning Machine’s(ELM’s)variant called Deep Extreme Learning Machines(DELMs)is used.A novel dataset consisting of 195 projects data is proposed to train the model and to evaluate the overall efficiency of the proposed *** proposed DELM’s based model evaluations achieved 90.017%training accuracy having a value with 1.412×10^(-3) Root Mean Square Error(RMSE)and 85.772%testing accuracy with 1.569×10^(-3) RMSE with five DELMs hidden *** results express that the suggested model has gained a notable recognition rate in comparison to any previous *** current study also concludes DELMs as the most applicable and useful technique for OSMO client’s project assessment.

关键词： Software outsourcing deep extreme learning machine(DELM) machine learning(ML) extreme learning machine assessment

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Transient events during photic driving in single-trial EEG within the second harmonics 46

Transient events during photic driving in single-trial EEG w...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Oppermann, Hannes Haueisen, Jens Technische Universität Ilmenau Insititute of Biomedical Engineering and Informatics Department of Computer Science and Automation Ilmenau Germany

ISBN: (纸本)9798350371499

Intermittent photic stimulation (IPS) is a commonly used activation method in clinical applications, e.g. epilepsy, but also used in research for investigating excitability states in the brain. Effects in the brain followed by IPS are also known as photic driving response. These effects are usually characterized using averaged data. Here, we used single-trial analysis to determine photic driving effects at the second harmonics of the stimulation *** rest and auditory-visual stimulation, 64-channel EEG data were recorded with eyes closed. The visual stimulation included eight stimulation frequencies within the alpha and beta bands. A complex Morlet wavelet was used for time-frequency (TF) analysis. Bursts within the TF representations were then detected and characterized by number, frequency, and power near the second *** observed bursts close to the second harmonic of each stimulation frequency. The number of these events increased during stimulation and the main frequencies were shifted towards the second harmonics. Similarly, the power increased at all but one *** new single-trial analysis during IPS could lead to a better understanding of the photic driving effects in the brain and, in particular, the generation mechanisms with regard to the occurrence of effects in the harmonics and sub-harmonics. © 2024 IEEE.

关键词： Harmonic analysis

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Factors influencing the adoption of awareness-raising activities in SMEs 10

Factors influencing the adoption of awareness-raising activi...

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10th International Conference on Socio-Technical Perspectives in Information Systems, STPIS 2024

作者： Bergström, Erik Kävrestad, Joakim Gustafsson, Johannes Hou Jonsson, Hannes Department of Computer Science and Informatics School of Engineering Jönköping University Jönköping Sweden

Information security incidents are most commonly caused by user behaviour, placing the user in focus. In order to mitigate information security threats and thereby protect the organisation, more and more are adopting a socio-technical viewpoint, which implies adopting the belief that information security cannot be solved with technology alone. A common way to address the user is by adopting awareness-raising activities. All types of organisations struggle to raise awareness. Several studies have pointed out small and medium-sized enterprises (SMEs) as being extra vulnerable and, in addition, having more issues adopting awareness-raising activities. There are few studies investigating factors influencing the adoption of awareness-raising activities in general, and the body of literature is even more scarce when focusing on the factors from an SME perspective. This study targets the gap by investigating what factors influence the adoption of awareness-raising activities in SMEs. We did this by conducting a semi-structured interview study in 10 organisations. Five factors with a total of seven sub-factors were found: Resources (with the sub-factors time and cost), implementation, content (with the sub-factors quality, adaptability, and comprehensibility), compliance, management (with the sub-factors management support and motivation of the employees). © 2024 Copyright for this paper by its authors.

关键词： Information hiding

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PartSeg v2: Bioimage Segmentation Using Advanced Deep Learning Techniques 4th

PartSeg v2: Bioimage Segmentation Using Advanced Deep Learni...

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4th International Conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Bokota, Grzegorz Basu, Subhadip Sroka, Jacek Insititute of Informatics University of Warsaw Warsaw Poland Department of Computer Science and Engineering Jadavpur University Kolkata India

ISBN: (纸本)9789819726134

In this paper, we present a new version of our bioimaging tool PartSeg. It allows integration of deep learning models from the Bioimage Model Zoo, which is a community-driven AI model repository. We also show how PartSeg’s power users can train such models, for example, to increase automatization of their data processing workflows. Then, we present further new features of PartSeg that make it easier to publish datasets in a durable and referencable way with version tracking. We also describe good practices related to data publishing and how adding metadata can allow for easier data discovery. Availability of such published datasets enables development of even better machine learning models. Publishing of the data is also a requirement for verifiable and repeatable science, leads to greater visibility of the results and enables cooperation and cross-domain exchange of ideas. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bioimaging

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The Threshold of Existence of δ-Temporal Cliques in Random Simple Temporal Graphs 20th

The Threshold of Existence of δ-Temporal Cliques in Rand...

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20th International Symposium on Algorithmics of Wireless Networks, ALGOWIN 2024

作者： Mertzios, George B. Nikoletseas, Sotiris Raptopoulos, Christoforos Spirakis, Paul G. Department of Computer Science Durham University Durham United Kingdom Computer Engineering and Informatics Department University of Patras Patras Greece Department of Mathematics University of Patras Patras Greece Department of Computer Science University of Liverpool Liverpool United Kingdom

ISBN: (纸本)9783031745799

We consider random simple temporal graphs in which every edge of the complete graph Kn appears once within the time interval [0, 1] independently and uniformly at random. Our main result is a sharp threshold on the size of any maximum δ-clique (namely a clique with edges appearing at most δ apart within [0, 1]) in random instances of this model, for any constant δ. In particular, using the probabilistic method, we prove that the size of a maximum δ-clique is approximately 2lognlog1δ with high probability (whp). We note that, even though the random simple temporal graph contains Θ(n2) overlapping δ-windows, which (when viewed separately) correspond to different random instances of the Erdős-Rényi random graphs model, the size of the maximum δ-clique in the former model and the maximum clique size of the latter are approximately the same. Furthermore, we show that the minimum interval containing a δ-clique is δ-o(δ) whp. We use this result to show that any polynomial time algorithm for δ-Temporal Clique is unlikely to have very large probability of success. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： probabilistic method Simple random temporal graph δ-temporal clique

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Disease Classification in the Cotton Using Convolution Neural Networks

Disease Classification in the Cotton Using Convolution Neura...

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International Conference on Advances in Data science and Computing Technologies, ASDC 2022

作者： Sharma, Aviral Chhabra, Gunjan School of Computer Science Department of Informatics UPES Uttarakhand Dehradun India Department of Computer Science and Engineering GEHU Uttarakhand Dehradun India

ISBN: (纸本)9789819936557

The present research focuses on an integrated architecture for extraction and identification of disease in the cotton plants. The deep learning architecture provided in the paper is capable of extracting the features from the cotton images and then create feature map of the same. The methods provide an automated approach for disease detection using image parts of various plant parts. The proposed methodology provides a unified approach for detection of major cotton diseases, namely bacterial blight, cotton leaf curl virus and wilt. The model can implemented in mobile applications for mass deployments and timely intervention be provided for protection of crops. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cotton

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Assessing students' awareness and education of web accessibility in web development and interface design programs 10

Assessing students' awareness and education of web accessibi...

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10th International Conference on Socio-Technical Perspectives in Information Systems, STPIS 2024

作者： Henriksson, Elin Uddstrom, Anna van Bree, Lotte Department of Computer Science and Informatics School of Engineering Jönköping University Jönköping Sweden

In an era of growing digitization, technology is essential for communication and daily life. However, inaccessible websites, including in Sweden, create barriers for individuals with disabilities, often due to insufficient education and awareness among web developers. Our quantitative study aimed to assess the status of web accessibility education within Swedish web development and interface design programs. We analyzed curricula and surveyed 63 final-year students across 23 programs. Findings show that while most programs (18 out of 23) include web accessibility, integration levels vary. Only 2% of courses offered standalone accessibility objectives, and 7% incorporated it within other courses, leaving 91% without any. Student knowledge varied;69.8% were aware of accessibility guidelines and laws, but 30.2% were not. Additionally, only 26.2% of students reported acquiring knowledge about accessibility guidelines and laws from their current education. This underscores the need for better web accessibility education. © 2024 Copyright for this paper by its authors.

关键词： Accessibility accessibility guidelines education interface design WCAG web accessibility web development

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Performance Evaluation of Wearable Internet of Things Devices for Indoor Positioning 10

Performance Evaluation of Wearable Internet of Things Device...

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Papadopoulos, George Spachos, Petros University of Thessaly Department of Computer Science and Biomedical Informatics Greece University of Guelph School of Engineering GuelphON Canada

ISBN: (纸本)9798350373011

Indoor localization and tracking services are necessary for several popular applications from asset monitoring to location-based marketing. The use of Internet of Things (IoT) devices in those services has increased due to their low cost and ease of deployment. However, indoor services pose significant challenges due to the lack of GPS signals as well as the complexity of the indoor environment. Alternative approaches, mainly including wireless technologies, should be considered. In this work, we examine the feasibility of using wearable IoT devices for indoor tracking. Specifically, we use smartwatches and we examine the performance of Wi-Fi and Bluetooth Low Energy (BLE) for indoor tracking. According to experimental results, BLE outperformed Wi-Fi in terms of energy efficiency while Wi-Fi, on the other hand, demonstrated a slightly better accuracy in Line of Sight conditions. © 2024 IEEE.

关键词： Bluetooth

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A Terramechanics-based Dynamic Model for Motion Control of Unmanned Tracked Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Zhang, Ruizeng Zhou, Wei Liu, Haiou Gong, Jianwei Chen, Huiyan Khajepour, Amir School of Mechanical Engineering Beijing Institute of Technology Beijing China School of Computer Science and Informatics Cardiff University Cardiff U.K Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo Canada

Existing terramechanics-based dynamic models for tracked vehicles (TRVs) are widely used in dynamics analysis. However, these models are incompatible with model-based controller design due to their high complexity and computational costs. This study presents a novel and simplified terramechanics-based dynamic model for TRVs that can be used in optimization-based real-time motion controller design. To this end, we approximated the track-ground interactions with an averaged term of the track-ground shear stresses to make the model computationally efficient and linearizable. By introducing the concepts of slip ratio and slip angle in the field of wheeled vehicles, the terramechanics-based dynamic model was finally simplified into a compact and practical single-track dynamic model reducing the demand for precise slip ratio measurements. The single-track model enables us to design an efficient motion control scheme by considering lateral and longitudinal dynamics separately. Finally, the proposed dynamic model was verified and validated under various road conditions using a real TRV. Additionally, the performance of different models was compared in simulation as an example to demonstrate that the proposed model outperforms the existing ones in TRV path-following tasks. IEEE

关键词： Model predictive control

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Fine-Tuning Deep Learning Model for Detecting Indonesian Traffic Accident Tweet 6

Fine-Tuning Deep Learning Model for Detecting Indonesian Tra...

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6th International Conference on computer and informatics engineering, IC2IE 2023

作者： Adi, Rizky Fukumoto, Fumiyo Irnawan, Bassamtiano Renaufalgi Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia University of Yamanashi Department of Computer Science and Engineering Yamanashi Japan

ISBN: (纸本)9798350345162

Twitter is one of Indonesia's most used social media, with total visits reaching 192 million visits per month, making it the fifth most-visited website in Indonesia. Twitter users exchange information with each other daily. One of them is a traffic accident event. With over 100,000 cases every year from 2017-2021, it is not usual to see a tweet that contains traffic accident information. By implementing text classification, traffic accidents can be detected through tweets and used to send alert messages to emergency responders to respond as quickly as possible. Previous research used a machine learning approach to solve this text classification problem. The study resulted in the best accuracy of 85% from the SVM model, which leaves room for improvement using state-of-the-art deep learning models. This research proposes a transfer learning method using two BERT-based and two RoBERTa-based pre-trained models, namely IndoBERT, IndoBERTweet, Indonesian RoBERTa Base Wiki, and Indonesian RoBERTa Base OSCAR to create the best model to classify tweets that contain traffic accident information. We used two kinds of fine-tuning architecture: the vanilla version fine-tuning architecture and the modified version, which combines the pre-trained model with CNN. This study used 1,002 manually labeled tweets, where 360 were labeled as traffic accident tweets. The experiment found that transfer learning from a pre-trained model Indonesian RoBERTa OSCAR provided the best result with an f1-score of 88.73 % and an accuracy of 92%, which means a 7% accuracy improvement over the previous research's best model. © 2023 IEEE.

关键词： BERT RoBERTa Text Classification Traffic Accident Transfer Learning Tweet

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