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14th Pacific Asia Conference on Information systems, PACIS 2010

作者： Bhuiyan, Moshiur Krishna, Aneesh OptInfra Systems Australia Decision Systems Laboratory School of Computer Science and Software Engineering University of Wollongong NSW 2522 Australia Department of Computing Faculty of Science and Engineering Curtin University of Technology Perth WA 6102 Australia

Requirements specification should not be concerned only with the software specification, but should also be able to integrate with the organizational models describing the environment in which the system will function. Agent-oriented conceptual modeling notations such as i* represents an interesting approach for modeling early phase requirements which includes organizational contexts, stakeholder intentions and rationale. Business Process Modeling notations such as BPMN are used to effectively conceptualize and communicate important process characteristics to relevant stakeholders. On the other hand, Unified Modeling Language (UML) is suitable for later phases of requirement capture which usually focus on completeness, consistency, and automated verification of functional requirements for the new system. In this paper, we illustrate the use of a methodology that facilitate and support the combined use of notation for modeling requirement engineering process in a synergistic fashion in a complex project for a large government Department. The notations we used were i*, BPMN and UML Use Case.

关键词： Unified Modeling Language

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A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

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computers, Materials & Continua 2023年第4期75卷 165-182页

作者： Muhammad Azhar Sehat Ullah Khalil Ullah Habib Shah Abdallah Namoun Khaliq Ur Rahman Department of Computer Science&IT University of MalakandChakdara18800Pakistan Department of Software Engineering University of MalakandChakdara18800Pakistan College of Computer Science King Khalid UniversityAbha62529Saudi Arabia Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan

Human biometric analysis has gotten much attention due to itswidespread use in different research areas, such as security, surveillance,health, human identification, and classification. Human gait is one of the keyhuman traits that can identify and classify humans based on their age, gender,and ethnicity. Different approaches have been proposed for the estimation ofhuman age based on gait so far. However, challenges are there, for which anefficient, low-cost technique or algorithm is needed. In this paper, we proposea three-dimensional real-time gait-based age detection system using a machinelearning approach. The proposed system consists of training and testingphases. The proposed training phase consists of gait features extraction usingthe Microsoft Kinect (MS Kinect) controller, dataset generation based onjoints’ position, pre-processing of gait features, feature selection by calculatingthe Standard error and Standard deviation of the arithmetic mean and bestmodel selection using R2 and adjusted R2 techniques. T-test and ANOVAtechniques show that nine joints (right shoulder, right elbow, right hand, leftknee, right knee, right ankle, left ankle, left, and right foot) are statisticallysignificant at a 5% level of significance for age estimation. The proposedtesting phase correctly predicts the age of a walking person using the resultsobtained from the training phase. The proposed approach is evaluated on thedata that is experimentally recorded from the user in a real-time *** (50) volunteers of different ages participated in the experimental *** the limited features, the proposed method estimates the age with 98.0%accuracy on experimental images acquired in real-time via a classical generallinear regression model.

关键词： Age estimation gait biometrics classical linear regression model

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Factors influencing the continuous use of cloud computing services in organization level 17

Factors influencing the continuous use of cloud computing se...

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2017 International Conference on Advances in Image Processing, ICAIP 2017

作者： Al-Sharafi, Mohammed A. Arshah, Ruzaini Abdullah Abu-Shanab, Emad A. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang Kuantan26300 Malaysia Accounting and Information Systems College of Business and Economics Qatar University Doha Qatar

ISBN: (纸本)9781450352956

The primary purpose of carrying out this research work is to identify the crucial factors that influence the continuous use of cloud computing services in organizations. To achieve this identified objective, this research work carried out a comprehensive literature review on cloud computing services' adoption at the organizational level, particularly emphasizing the factors that define the prolonged adoption of cloud computing services. The factors identified, served as a guide required by organizations for completely safe and effective cloud computing service and their use in businesses. This research adopts the criteria of Wymer and Regan as a basis for this study. A total of 53 factors were obtained from prior studies on the cloud computing services' adoption. Results obtained during the cause of study revealed that the most crucial factors affecting the continuous use of cloud computing services in organizations are as follows: Relative advantage;Complexity: Perceived security and privacy;Compatibility;Top manager's support;Cost reduction;Competitive pressure;IT readiness;Firm size;Vendor support;Regulations and Government policy;Trialability;Perceived reliability;Perceived availability;Uncertainty and Perceived Trust. © 2017 Association for Computing Machinery.

关键词： Cost reduction

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

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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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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore software Maintenance

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computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia 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)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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A novel feature fusion and mountain gazelle optimizer based framework for the recognition of jute pests in sustainable agriculture

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Scientific reports 2025年第1期15卷 18148页

作者： Soner Kiziloluk Mucahit Karaduman Serpil Aslan Muhammed Yildirim Muhammad Attique Khan Fatimah Alhayan Yunyoung Nam Department of Computer Engineering Faculty of Engineering and Natural Sciences Malatya Turgut Ozal University Malatya Turkey. Department of Software Engineering Faculty of Engineering and Natural Sciences Malatya Turgut Ozal University Malatya Turkey. Department of AI College of Computer Engineering and Science Prince Mohammad Bin Fahd University Al-Khobar Saudi Arabia. attique.khan@***. Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O.Box 84428 11671 Riyadh Saudi Arabia. Emotional and Intelligent Child Care Convergence Research Center Soonchunhyang University Asan 31538 Korea. ynam@sch.ac.kr.

Sustainable agriculture is an approach that involves adopting and developing agricultural practices to increase efficiency and preserve resources, both environmentally and economically. Jute is one of the primary sources of income grown in many countries. At this stage, increasing efficiency in jute production and protecting it from pests is essential. Detecting jute pests at an early stage will not only improve crop yield but also provide more income. In this paper, an artificial intelligence-based model was suggested to detect jute pests at an early stage. In this developed model, two different pre-trained models were used for feature extraction. To improve the performance of the developed model, the features obtained using the DarkNet-53 and DenseNet-201 models were combined. After this stage, the metaheuristic Mountain Gazelle Optimizer (MGO) was used, allowing the developed model to work faster and achieve more successful results. Feature selection was carried out using MGO; thus, more successful results were obtained with fewer, more compelling features. The proposed model was compared with six different models and five different classifiers accepted in the literature. In the developed model, 17 different jute pests were detected with 96.779% accuracy. The accuracy value achieved in the developed model is promising in successfully detecting jute pests.

关键词： Classification Deep learning Jute Mountain gazelle optimizer Optimization

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Time series forecasting of energy commodity using grey Wolf optimizer

Time series forecasting of energy commodity using grey Wolf ...

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International MultiConference of Engineers and computer Scientists 2015, IMECS 2015

作者： Yusof, Yuhanis Mustaffa, Zuriani School of Computing College of Arts and Sciences Universiti Utara Malaysia Sintok Kedah06010 Malaysia Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Malaysia

ISBN: (纸本)9789881925329

The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices. In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting. The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price. Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE). Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. Furthermore, the proposed GWO produces a better forecast for gasoline price as compared to the ABC model, as well as being at par in crude oil. Such an achievement indicates that GWO may become a competitor in the domain of time series forecasting and would be useful for investors in planning their investment and projecting their profit.

关键词： Data mining

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Robust In-Vehicle Diagnostic-Based Intrusion Detection System

Robust In-Vehicle Diagnostic-Based Intrusion Detection Syste...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Shafee, Ahmed Awaad, Tasneem A. Moro, Ahmed Adams State University Department of Engineering and Computer Science AlamosaCO United States Ain Shams University Faculty of Engineering Department of Computer and Systems Engineering Cairo Egypt Siemens Eda Cairo Egypt Siemens Digital Industries Software Integrated Electrical Systems Segment Cairo Egypt

ISBN: (纸本)9798350364910

Cybersecurity has become a significant concern for automotive manufacturers as modern cars increasingly incorporate electronic components. Electronic Control Units (ECUs) have evolved to become the central control units for critical car functions such as engines and brakes, experiencing rapid technological advancements. However, this swift progression in ECU technology has also made them prime targets for cyber attacks. This vulnerability has spurred researchers to focus on securing ECUs. Numerous studies have proposed intrusion detection systems (IDS) to protect against attacks on ECUs in vehicles. Yet, these IDSs are not impenetrable;attackers can exploit them by launching evasion attacks, which can trigger numerous false positive alarms. Such false alarms can be disruptive and potentially hazardous for drivers. Additionally, attackers can evade IDSs from detecting malicious data that can cause harm to the vehicle. Accordingly, in this paper, we propose a novel training framework to train a robust in-vehicle IDS that can encounter evasion attacks. Our methodology is based on implementing two rounds of mimic learning technique for training Random Forest (RF) based IDS. RF has been chosen to incorporate the randomness of the RF architecture to enhance the robustness of the model. Additionally, in each round of the two rounds of the mimic learning technique, an RF model with a different architecture is chosen to improve the resilience of the model against evasion attacks without affecting its accuracy. Our Experimental results have shown the effectiveness of our framework against evasion attacks. © 2024 IEEE.

关键词： Robustness (control systems)

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Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

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computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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Enhancement the video quality forwarding Using Receiver-Based Approach(URBA) in Vehicular Ad-Hoc Network

Enhancement the video quality forwarding Using Receiver-Base...

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2017 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2017

作者： Hammood, Omar A. Kahar, Mohd Nizam Mohmad Mohammed, Muamer N. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia IBM Center of Excellence University Malaysia Pahang Pahang Malaysia Department of Computer Sciences Bayan University Erbil Iraq

ISBN: (纸本)9781538638491

In Vehicular Ad-hoc Networks (VANETs), data routing is a major problem because of its quick change in topology and vehicular high mobility. VANETs are ad hoc wireless mobile networks which play important role in commercial applications and safety of public vehicular communications. The routing protocols that base on vehicular position are attracting much interest because of the availability and advancement of devices equipped with GPS. A major problem with VANETs is the frequent disruptions in the path of vehicles due to the high mobility of the participating vehicles. This can lead to the breaking of established links and result in low throughput, delay in service delivery, less overhead as well as low rate of delivery. In this paper, Using Receiver-Based Approach (URBA) is proposed. The proposed approach (URBA) compared to VANET, incorporates a potential receiver-based strategy which is traditionally better in performance and might achieve less delay in service delivery with a higher rate of delivery. © 2017 IEEE.

关键词： Vehicular ad hoc networks

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