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Bug Prioritization Using Average One Dependence Estimator

Intelligent Automation & Soft Computing 2023年第6期36卷 3517-3533页

作者： Kashif Saleem Rashid Naseem Khalil Khan Siraj Muhammad Ikram Syed Jaehyuk Choi Department of IT and Computer Science Institute of Applied Sciences and TechnologyPakAustriaFochhshuleHaripurPakistan Faculty of Computer Sciences and Information Technology Superior UniversityLahore54660Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper DirKhyber PakhtunkhwaPakitan School of Computing Gachon University1342Seongnam-daeroSujeong-guSeongnam-si13120Korea

Automation software need to be continuously updated by addressing software bugs contained in their ***,bugs have different levels of importance;hence,it is essential to prioritize bug reports based on their sever-ity and *** managing the deluge of incoming bug reports faces time and resource constraints from the development team and delays the resolu-tion of critical ***,bug report prioritization is *** study pro-poses a new model for bug prioritization based on average one dependence estimator;it prioritizes bug reports based on severity,which is determined by the number of *** more the number of attributes,the more the *** proposed model is evaluated using precision,recall,F1-Score,accuracy,G-Measure,and Matthew’s correlation *** of the proposed model are compared with those of the support vector machine(SVM)and Naive Bayes(NB)*** and Mozilla datasetswere used as the sources of bug *** proposed model improved the bug repository management and out-performed the SVM and NB ***,the proposed model used a weaker attribute independence supposition than the former models,thereby improving prediction accuracy with minimal computational cost.

关键词： Bug report triaging prioritization support vector machine Naive Bayes

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Factors influencing the intention to share knowledge in citizen media with stimulus-organismic-response framework

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International Journal of Web Based Communities 2016年第4期12卷 419-438页

作者： Fitriani, Hana Hidayanto, Achmad Nizar Budiardjo, Eko K. Meyliana Phusavat, Kongkiti Faculty of Computer Science Universitas Indonesia Kampus UI Depok16424 Indonesia School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Center for Advanced Studies in Industrial Technology Faculty of Engineering Kasetsart University Bangkok10900 Thailand

The trend of citizen journalism enables people to actively share knowledge. This research aimed to analyse which factors influence the individual to share knowledge in citizen media. Our research model was organised using stimulus-organismic-response (SOR) framework by focusing stimulus from social and technological environment. The five points Likert scale questionnaire was developed and distributed to 850 Kompasiana's contributors (the largest citizen media platform in Indonesia) via message feature, thus obtaining 295 valid respondents who fill the questionnaire completely. Those data then were analysed by structural equation modelling method using AMOS 22.0. The result shows that both social and technological environment significantly influences the intention to share knowledge. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Surveys

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Structure Function Based Transform Features for Behavior-Oriented Social Media Image Classification 5th

Structure Function Based Transform Features for Behavior-Ori...

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5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Krishnani, Divya Shivakumara, Palaiahnakote Lu, Tong Pal, Umapada Ramachandra, Raghavendra International Institute of Information Technology Naya Raipur Naya RaipurChhattisgarh India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia National Key Lab for Novel Software Technology Nanjing University Nanjing China Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9783030414030

Social media has become an essential part of people to reflect their day to day activities including emotions, feelings, threatening and so on. This paper presents a new method for the automatic classification of behavior-oriented images like Bullying, Threatening, Neuroticism-Depression, Neuroticism-Sarcastic, Psychopath and Extraversion of a person from social media images. The proposed method first finds facial key points for extracting features based on a face detection algorithm. Then the proposed method labels face regions as foreground and other than face region as background to define context between foreground and background information. To extract context, the proposed method explores Structural Function based Transform (SFBT) features, which study variations on pixel values. To increase discriminating power of the context features, the proposed method performs clustering to integrate the strength of the features. The extracted features are then fed to Support Vector Machines (SVM) for classification. Experimental results on a dataset of six classes show that the proposed method outperforms the existing methods in terms of confusion matrix and classification rate. © Springer Nature Switzerland AG 2020.

关键词： Classification (of information)

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Investigation of bypassing malware defences and malware detections

Investigation of bypassing malware defences and malware dete...

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2011 7th International Conference on information Assurance and Security, IAS 2011

作者： Daryabar, Farid Dehghantanha, Ali Udzir, Nur Izura Asia Pacific University College of Technology and Innovation Technology Park Malaysia Kuala Lumpur Malaysia Faculty of Computer Science and Information Technology University Putra Malaysia Malaysia

ISBN: (纸本)9781457721533

Nowadays, malware incident is one of the most expensive damages caused by attackers. Malwares are caused different attacks, so considerations and implementations of malware defences for internal networks are important. In this papers, different techniques such as repacking, reverse engineering and hex editing for bypassing host-based Anti Virus (AV) signatures are illustrated, and the description and comparison of different channels and methods when malware might reach the host from outside the networks are demonstrated. After that, bypassing HTTP/SSL and SMTP malware defences as channels are discussed. Finally, as it is important to find and detect new and unknown malware before the malware gets in to the victims, a new malware detection technique base on honeynet systems is surveyed. © 2011 IEEE.

关键词： Reverse engineering

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Binary Morphological Model in Refining Local Fitting Active Contour in Segmenting Weak/Missing Edges

Binary Morphological Model in Refining Local Fitting Active ...

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International Conference on Advanced computer science Applications and Technologies (ACSAT)

作者： Norshaliza Kamaruddin Hamid A. Jalab Roziati Zainuddin Nor Aniza Abdullah Faculty of Science Computer & Information Technology Department of Computer System and Technology Faculty of Computer Science and Information Technology University Malaya Malaysia

Medical images are known to have poor quality which leads to difficulty in vision and segmentation process. Mainly, noise and intensity in homogeneity are two main characteristics that lead to gaps (missing at edges) at the boundary of the desired object. This paper investigated method that managed to smooth the image texture in order to overcome the gaps problem. Our method adopts the morphological closing operations using the diamond-shape structuring elements to overcome the above-mentioned problem. We applied the dilation and erosion operation to expand and later smooth the regions with gaps. Our method shows satisfaction results when dealing with binary image rather than working with gradient. The results obtained shows better accuracy as the evolving curve is following the pixels value in the binary image. The method proposed is executed based on the output from Local binary fitting energy.

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Anaphora resolution of Malay text: Issues and proposed solution model

Anaphora resolution of Malay text: Issues and proposed solut...

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International Conference on Asian Language Processing

作者： Noor, Noorhuzaimi Karimah Mohd. Noah, Shahrul Azman Aziz, Mohd Juzaidin Ab. Hamzah, Mohd Pouzi Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Pahang Malaysia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Computer Science Department FST Universiti Malaysia Terengganu Terengganu Malaysia

ISBN: (纸本)9780769542881

Anaphora resolution (AR) is a process to identify the appropriate antecedent with its anaphor which occur before the anaphor. AR able to improve most of the NLP applications such as question answering, short answer examination system and information extraction. Most of AR systems are deal with English language. Thus, in 1990's the research on AR has been applied for other language, such as Arabic, Chinese, Hindi and Norwegian. There are however limited or no effort in dealing with Malay text. The AR systems for one language cannot be simply adapted to use in other languages. This is due to the fact that different languages have different set of rules relating to syntax and semantic to respective language. This paper proposed a model for resolving anaphora phenomena in Malay text. The model consists of three elements consisting of anaphora resolution process, syntactic knowledge process and semantic-world knowledge process. The elements are defined based on the observable fact occurring in Malay language. © 2010 IEEE.

关键词： Semantics

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Recognition of maximal speed limit traffic signs for use in advanced ADAS algorithms

Recognition of maximal speed limit traffic signs for use in ...

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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Striskovic, Barbara Vranjes, Mario Vranjes, Denis Popovic, Miroslav Institute RT-RK Osijek Llc for Information Technology Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Osijek Croatia University of Novi Sad Faculty of Technical Sciences Novi Sad Serbia

ISBN: (纸本)9781665404174

Advanced Driver Assistance Systems (ADAS) have been increasingly developing, specifically in the last decade. One of such ADAS is that intended for traffic signs recognition. This paper deals with the recognition of a specific subset of traffic signs, i.e. speed limit traffic signs. The complete solution is based on the usage of machine learning and finally implemented in the C programming language. After the optimization process, the final solution is implemented on the real ADAS board, to check its performance in a real operational environment. Due to the limited resources of the ADAS board itself, a simple Convolutional Neural Network (CNN) was created to recognize speed limit traffic signs. For CNN training a large database of 6891 training images is used. When testing the solution, 731 test images from the real traffic are used, as well as 123 real video sequences. The test results show that in certain situations the proposed solution is capable of achieving high performance in terms of precision, while in some cases additional improvements of the solution should be investigated. It is capable of processing 12 frames per second when operating with state-of-the-art automotive camera resolution, i.e. 1280x720 pixels. © 2021 IEEE.

关键词： Traffic signs

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SOLAS: Superpositioning an Optical Lens in Automotive Simulation

arXiv

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arXiv 2025年

作者： Jakab, Daniel Barthel, Julian Braun, Alexander Mohandas, Reenu Deegan, Brian Michael Kumbham, Mahendar Molloy, Dara Collins, Fiachra Scanlan, Anthony Eising, Ciarán Dept. of Electronic and Computer Engineering University of Limerick Castletroy Co. Limerick V94 T9PX Ireland Faculty of Electrical Engineering & Information Technology University of Applied Sciences Düsseldorf40476 Germany Dept. of Electrical and Electronic Engineering University of Galway GalwayH91 TK33 Ireland Valeo Vision Systems Tuam GalwayDY1 22DJ Ireland Lero the Science Foundation Ireland Research Centre for Software University of Limerick LimerickV94 T9PX Ireland

Automotive Simulation is a potentially cost-effective strategy to identify and test corner case scenarios in automotive perception. Recent work has shown a significant shift in creating realistic synthetic data for road traffic scenarios using a video graphics engine. However, a gap exists in modeling realistic optical aberrations associated with cameras in automotive simulation. This paper builds on the concept from existing literature to model optical degradations in simulated environments using the Python-based ray-tracing library KrakenOS. As a novel pipeline, we degrade automotive fisheye simulation using an optical doublet with +/-2◦ Field of View(FOV), introducing realistic optical artifacts into two simulation images from SynWoodscape and Parallel Domain Woodscape. We evaluate KrakenOS by calculating the Root Mean Square Error (RMSE), which averaged around 0.023 across the RGB light spectrum compared to Ansys Zemax OpticStudio, an industrial benchmark for optical design and simulation. Lastly, we measure the image sharpness of the degraded simulation using the ISO12233:2023 Slanted Edge Method and show how both qualitative and measured results indicate the extent of the spatial variation in image sharpness from the periphery to the center of the degradations. © 2025, CC BY.

关键词： Ray tracing

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Intelligent Models for Forecasting Repair Timing of Leakage Water Pipelines 3

Intelligent Models for Forecasting Repair Timing of Leakage ...

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3rd International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2023

作者： Mohamed Warad, Ahmed Ali Wassif, Khaled Darwish, Nagy Ramadan Faculty of Graduate Studies for Statistical Research Department of Information Systems and Technology Cairo Egypt Faculty of Computers and Artificial Intelligence Department of Computer Science Cairo Egypt

ISBN: (纸本)9798350306231

Machine Learning (ML) is a branch of artificial intelligent field, which has great capability to achieve improvements in real industries. On the other side, water leakage is a major problem for water utilities;it can waste water and damage infrastructure, during long repair times. There is no previous research using ML algorithms to forecast the repair time of water pipe leakage. This paper investigates seven ML algorithms for repair time forecasting in water pipe leakage. The paper uses data from a water utility in Alexandria, Egypt. Results exposed that all seven models were able to forecast the time of repair;in particular, AdaBoost, is the best, has an RMSE of 0.057. This study highlights the ML approaches for predicting the time needed to repair a water pipe leakage and the need for further research to improve the comprehension of the relation between repair time and pipe features. © 2023 IEEE.

关键词： Adaptive boosting

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Bridging the Digital Gap: A Systematic Review on UI/UX Design Considerations for Elderly-friendly Digital Wallets 6

Bridging the Digital Gap: A Systematic Review on UI/UX Desig...

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6th International Conference on Applied Computational Intelligence in information Systems, ACIIS 2023

作者： Alfie, Nur Alfreeana Sidi, Jonathan Junaini, Syahrul Nizam Chai, Wang Yin Mit, Edwin Gedat, Remmy University of Malaysia Sarawak Faculty of Computer Science & Information Technology Kota Samarahan Malaysia University of Malaysia Sarawak Faculty of Language and Communication Kota Samarahan Malaysia

ISBN: (纸本)9798350317428

In an era defined by rapid technological innovation, inclusivity in digital design emerges as a critical yet often overlooked aspect. However, seniors and older citizens often grapple with complex interfaces and sophisticated technology, leading to their digital marginalization. This paper offers a detailed systematic literature review of research trends spanning 2018 - 2023. Sourcing from the renowned SCOPUS database, this review identified a limited 13 journal articles conforming to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. These scholarly publications were thoroughly examined and divided into five core themes encapsulating the focal points of this research: gerontechnology, user experience, user interface design, usability testing, and the advantages mobile apps can offer to the elderly. Further, this synthesized review, aiming to enhance the UI/UX design of digital wallets for seniors, could offer substantial insights to researchers and educators while highlighting potential directions for ensuing research. © 2023 IEEE.

关键词： User interfaces

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