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Automatic GUI Test by Using SIFT Matching

China Communications 2016年第9期13卷 227-236页

作者： Xiaoxin Fang Bin Sheng Ping Li Dan Wu Enhua Wu Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China The State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Department of Mathematics and Information Technology The Education University of Hong KongHong KongChina China Southern Power Grid GuangzhouChina Faculty of Science and Technology University of MacaoMacaoChina

In software development process, the last step is usually the Graphic User In- terface（GUI） test, which is part of the final user experience （UE） test. Traditionally, there exist some GUI test tools in the market, such as Abbot Java GUI Test Framework and Pounder, in which testers pre-configure in the script all desired actions and instructions for the computer, nonetheless requiring too much of invariance of GUI environment; and they require reconfiguration in case of GUI changes, therefore still to be done mostly manually and hard for non-programmer testers to. Consequently, we proposed GUI tests by image recognition to automate the last process; we managed to innovate upon current algorithms such as SIFT and Random Fern, from which we develop the new algorithm scheme retrieving most efficient feature and dispelling inefficient part of each algorithm. computers then apply the algorithm, to search for target patterns themselves and take subsequent actions such as manual mouse, keyboard and screen I/O automatically to test the GUI without any manual instructions. Test results showed that the proposed approach can accelerate GU! test largely compared to current benchmarks.

关键词： GUI test image recognition SIFT random fern.

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Exploring the Usage of Mobile Phones in the Assessment Process: A Case Study 47

Exploring the Usage of Mobile Phones in the Assessment Proce...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Kovačević, Željko Bubnic, Bostjan Kosar, Tomaž Zagreb University Of Applied Sciences Department Of Computer Science And Information Technology Zagreb Croatia University Of Maribor Faculty Of Electrical Engineering And Computer Science Maribor Slovenia

ISBN: (纸本)9798350382495

technology is changing how students learn in the 21st century significantly. Integrating mobile devices in teaching, learning, and assessment processes has emerged as an important strategy for improving teaching methodologies and students' learning. However, adopting mobile devices presents several challenges, including understanding the students' performance, impact on time, and efficiency in the assessment process. This study explores this area with an empirical study of using mobile devices and compares the results to those using traditional desktop computers. In the educational environment, we investigated students' effective use while interacting with mobile and desktop versions of the Second Introductory programming summative assessment. Multinational/multi-institutional research involved a comparative analysis between two student groups undertaking identical tasks on mobile phones and desktop computers. Our results suggest that the students' results are not affected significantly by using the mobile version of the assessment application. These results highlight the usability of mobile devices as a flexible and effective tool for various educational applications, strengthening their role in the modern learning environment. © 2024 IEEE.

关键词： Object oriented programming

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Exploring the Role of Sleep Quality, Obsessive–Compulsive Disorder, Fear of Missing Out, and Psychological Resilience on Problematic Instagram Use

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Journal of technology in Behavioral science 2024年 1-11页

作者： Yilmaz, Ramazan Avci, Ummuhan Karaoglan Yilmaz, Fatma Gizem Department of Computer Technology & Information Systems Faculty of Science Bartin University Bartin Turkey Department of Management Information Systems Faculty of Economics and Administrative Sciences Bartin University Bartin Turkey

This study addresses a gap in the literature regarding the relationships between sleep quality, obsessive–compulsive disorder (OCD), fear of missing out (FoMO), psychological resilience, and problematic Instagram use (PIU) among university students. By examining these interrelated factors, the research aims to clarify the mechanisms behind Instagram addiction, support effective interventions, and contribute to academic knowledge. This study examined university students’ sleep quality, PIU, OCD, FoMO, and psychological resilience, as well as the structural relationships between these variables. The study encompassed a sample of 407 Turkish university students with an average age of 21.78. The age range of the participants was between 18 and 35 years;43% of them were female, and 57% were male. This study was conducted according to the correlational research method, and pathway analysis was used to conduct the research. Research findings show that OCD and FoMO positively affect PIU. In other words, as OCD and FoMO increase, Instagram addiction also increases. Psychological resilience has an indirect effect on PIU. OCD plays a mediating role between psychological resilience and PIU and between psychological resilience and FoMO. Therefore, as psychological resilience increases, PIU and FoMO decrease. A positive correlation was found between OCD and FoMO. As the OCD level increases, the FoMO level of the individuals also increases. Another study finding was that OCD, FoMO, psychological resilience, and PIU did not significantly affect sleep quality. Future research may focus on exploring cause-effect relationships among these variables alongside implementing school-based programs to enhance students’ psychological resilience through training, planning, and follow-up studies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Fear of missing out (FoMO) Obsessive–compulsive disorder Problematic Instagram use Psychological resilience Sleep quality

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Optimal Logistics Activities Based Deep Learning Enabled Traffic Flow Prediction Model

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computers, Materials & Continua 2022年第12期73卷 5269-5282页

作者： Basim Aljabhan Mahmoud Ragab Sultanah M.Alshammari Abdullah S.Al-Malaise Al-Ghamdi Ports and Maritime Transportation Department Faculty of Maritime StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Center of Excellence in Smart Environment Research King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia S 7Information Systems Department HECI SchoolDar Alhekma UniversityJeddahSaudi Arabia

Traffic flow prediction becomes an essential process for intelligent transportation systems(ITS).Though traffic sensor devices are manually controllable,traffic flow data with distinct length,uneven sampling,and missing data finds challenging for effective *** traffic data has been considerably increased in recent times which cannot be handled by traditional mathematical *** recent developments of statistic and deep learning(DL)models pave a way for the effectual design of traffic flow prediction(TFP)*** this view,this study designs optimal attentionbased deep learning with statistical analysis for TFP(OADLSA-TFP)*** presentedOADLSA-TFP model intends to effectually forecast the level of traffic in the *** attain this,the OADLSA-TFP model employs attention-based bidirectional long short-term memory(ABLSTM)model for predicting traffic *** order to enhance the performance of the ABLSTM model,the hyperparameter optimization process is performed using artificial fish swarm algorithm(AFSA).A wide-ranging experimental analysis is carried out on benchmark dataset and the obtained values reported the enhancements of the OADLSA-TFP model over the recent approaches mean square error(MSE),root mean square error(RMSE),and mean absolute percentage error(MAPE)of 120.342%,10.970%,and 8.146%respectively.

关键词： Traffic flow prediction deep learning artificial fish swarm algorithm mass gatherings statistical analysis logistics

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TinyML-Based Gait Recognition for User Detection on an STM32L4 IoT Node 9

TinyML-Based Gait Recognition for User Detection on an STM32...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Hassan, Hateem Abdullah, M. Hussain, Muhammad Zunnurain Hasan, Muhammad Zulkifl Mustafa, Muzzamil Khalid, Aqsa Awan, Rimsha Hussain, Usman Khan, Zohaib Ahmed Javaid, Arslan University Lahore Department of Computer Engineering Information Technology Punjab Pakistan Bahria University Lahore Campus Dept. of Computer Science Pakistan University of Central Punjab Lahore Pakistan Faculty of Information Technology Department of Computer Science Pakistan National College of Business Administration And Economics Department of Computer Science Lahore Pakistan Information Technology University Lahore Pakistan University of Home Economics Pakistan

ISBN: (纸本)9798350394474

Gait recognition stands out as a robust biometric tool for discerning users. Yet, adapting it to devices with limited resources, such as the STM32L4 microcontroller, demands cutting-edge strategies. This research unveils an innovative TinyML methodology, leveraging a specially-designed Convolutional Neural Network (CNN). Notably, our bespoke CNN model showcased a remarkable 97.3% accuracy in pinpointing users on the STM32L4 system. © 2024 IEEE.

关键词： Convolutional neural networks

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A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1412-1434页

作者： Shoaib Hassan Qianmu Li Khursheed Aurangzeb Affan Yasin Javed Ali Khan Muhammad Shahid Anwar School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingJiangsuChina Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Software Northwestern Polytechnical UniversityXianShaanxiChina Department of Computer Science School of PhysicsEngineering&Computer ScienceUniversity of HertfordshireHatfieldUK Department of AI and Software Gachon University Seongnam-siSeongnamSouth Korea

Over the past few years,the application and usage of Machine Learning(ML)techniques have increased exponentially due to continuously increasing the size of data and computing *** the popularity of ML techniques,only a few research studies have focused on the application of ML especially supervised learning techniques in Requirement Engineering(RE)activities to solve the problems that occur in RE *** authors focus on the systematic mapping of past work to investigate those studies that focused on the application of supervised learning techniques in RE activities between the period of 2002–*** authors aim to investigate the research trends,main RE activities,ML algorithms,and data sources that were studied during this ***-five research studies were selected based on our exclusion and inclusion *** results show that the scientific community used 57 *** those algorithms,researchers mostly used the five following ML algorithms in RE activities:Decision Tree,Support Vector Machine,Naïve Bayes,K-nearest neighbour Classifier,and Random *** results show that researchers used these algorithms in eight major RE *** activities are requirements analysis,failure prediction,effort estimation,quality,traceability,business rules identification,content classification,and detection of problems in requirements written in natural *** selected research studies used 32 private and 41 public data *** most popular data sources that were detected in selected studies are the Metric Data Programme from NASA,Predictor Models in Software Engineering,and iTrust Electronic Health Care system.

关键词： data sources machine learning requirement engineering supervised learning algorithms

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MDLP - The resource allocating policy for multi divisible loads in heterogeneous linear networks

MDLP - The resource allocating policy for multi divisible lo...

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2006 2nd International Conference on Semantics Knowledge and Grid, SKG

作者： Taoliu, Hong Yang, Juan Huang, ZhiXing Bai, Yun Qiu, YuHui SouthWest University Computer and Information Science ChongQing Education College Computer and Modern Education Technology Department

ISBN: (纸本)0769532055

Reasonably allocating the resources to the tasks can effectively improve the concurrency ability of the distributed *** this paper, we propose a resource allocating policy -MDLP, for multi-divisible loads under heterogeneous linear system. MDLP model the optimizing problem of the divisible loads into a linear programming problem. At the same time, the finish time of the previous loads is no longer need to used to compute the current load's distribution. © 2006 IEEE.

关键词： Linear networks

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Adaptive resource allocation for reliable performance in heterogeneous distributed systems

Adaptive resource allocation for reliable performance in het...

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13th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2013

作者： Hussin, Masnida Abdullah, Azizol Subramaniam, Shamala K. Department of Communication Technology and Networks Faculty of Computer Science and Information Technology University of Putra Malaysia 43400 UPM Serdang Selangor Malaysia

ISBN: (纸本)9783319038889

The rapid development of distributed systems has triggered the emergence of many new applications such as Cloud applications. Satisfaction on these systems in regards their services is an important indicator that reflect quality of IT resource management. In this paper, we address a reliability issue in the context of resource allocation that aims to improve performance of the distributed systems. We propose a heuristic scheduling by integrating different mapping and queuing strategies into allocation policy for suitably matching tasks and resources. Dynamic resource discovery and task classification are incorporated into the heuristic scheduling in pursuit of reliable decisions. Simulation experiments show that our approach achieves better response time and utilization compared to other heuristic approaches. © Springer International Publishing Switzerland 2013.

关键词： Resource allocation

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Automated Generation of Multi-tenant Database systems Based upon system Design Diagrams 5th

Automated Generation of Multi-tenant Database Systems Based ...

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5th International Conference on information systems and Management science, ISMS 2022

作者： Camilleri, Rebecca Vella, Joseph G. Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta Msida Malta

ISBN: (纸本)9783031311529

Energetic technological advancements in the past decade, have led to an exponential increase in the amount of data being stored. Consequently, the need for effective Database Management systems (DBMSs) which embody security considerations from the initial stages of database design is imperative in modern information systems development. This prerequisite is further accentuated by the recent transitioning from single tenant information systems to multi-tenant based on public cloud infrastructures. Within this context, this paper proposes a computer-Aided Software Engineering (CASE) tool capable of generating secure database related structures and processes. A comprehensive overview of a specific information system design is provided to the CASE tool by means of entity-relationship diagram, entity life history and dataflow diagram. Subsequently, crucial security controls targeted towards the protection of database objects are incorporated by means of discretionary and role-based access controls. Following the encoding of the system’s design data is adorned with the required security elements, the CASE tool performs an in-depth analysis that aids in the detection of potential security pitfalls. Provided that the database design enhanced with security elements is satisfactory, i.e., all checks conducted are successful, the CASE tool generates Structured Query Language (SQL) language constructs for well-known multi-tenant scenarios. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： information systems

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Electronic-offering of fresh fruit bunches oil palm by independent farmer with a blockchain approach

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AIP Conference Proceedings 2025年第1期3223卷

作者： Harison Marimin Sukardi Faqih Udin Yani Nurhadriyani Engineer Professional Education Study Program Universitas Andalas Padang Indonesia - 25000 Department of Agro-industrial Technology Faculty of Agricultural Engineering and Technology IPB University Bogor Indonesia - 16680 Department of Computer Science Faculty of Mathematics and Natural Sciences IPB University Bogor Indonesia – 16680

Indonesia meets the needs of 50% of the world's palm oil needs. Sources of Indonesian palm oil, 34 % are produced by independent smallholders. The lack of governance of independent smallholders leads to low productivity of their crops. Global market demands for palm oil derivative sources become an obligation to compete. The development of blockchain technology that favors traceability and transparency is applied in the supply agriculture sector, and this is an opportunity for how blockchain technology can help the palm oil supply chain become transparent and can find its source. This research uses the system development life cycle (SDLC) method. And business process model and notation in business model design. The results of the design of the FFB sale and purchase transaction system with blockchain technology have succeeded in connecting farmer transactions as FFB providers with traders and PKS as FFB buyers. Every transaction sent by the farmer will be locked by a hash, as immunity makes the data sent immutable. The system can display the traceability of transactions while maintaining the integrity of member information.

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