• Title/Summary/Keyword: Behavioral Software Engineering

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Modeling in System Engineering: Conceptual Time Representation

  • Al-Fedaghi, Sabah
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.153-164
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    • 2021
  • The increasing importance of such fields as embedded systems, pervasive computing, and hybrid systems control is increasing attention to the time-dependent aspects of system modeling. In this paper, we focus on modeling conceptual time. Conceptual time is time represented in conceptual modeling, where the notion of time does not always play a major role. Time modeling in computing is far from exhibiting a unified and comprehensive framework, and is often handled in an ad hoc manner. This paper contributes to the establishment of a broader understanding of time in conceptual modeling based on a software and system engineering model denoted thinging machine (TM). TM modeling is founded on a one-category ontology called a thimac (thing/machine) that is used to elaborate the design and analysis of ontological presumptions. The issue under study is a sample of abstract modeling domains as exemplified by time. The goal is to provide better understanding of the TM model by supplementing it with a conceptualization of time aspects. The results reveal new characteristics of time and related notions such as space, events, and system behavior.

Spatio-Temporal Analysis of Trajectory for Pedestrian Activity Recognition

  • Kim, Young-Nam;Park, Jin-Hee;Kim, Moon-Hyun
    • Journal of Electrical Engineering and Technology
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    • v.13 no.2
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    • pp.961-968
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    • 2018
  • Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

Game Bot Detection Approach Based on Behavior Analysis and Consideration of Various Play Styles

  • Chung, Yeounoh;Park, Chang-Yong;Kim, Noo-Ri;Cho, Hana;Yoon, Taebok;Lee, Hunjoo;Lee, Jee-Hyong
    • ETRI Journal
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    • v.35 no.6
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    • pp.1058-1067
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    • 2013
  • An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.

Experiences with Simulation Software for the Analysis of Inverter Power Sources in Arc Welding Applications

  • Fischer W.;Mecke H.;Czarnecki T.K.
    • Proceedings of the KIPE Conference
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    • 2001.10a
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    • pp.731-736
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    • 2001
  • Nowadays various simulation tools are widely used for the design and the analysis of power electronic converters. From the engineering point of view it is rather difficult to parameterize power semiconductor device models without the knowledge of basic physical parameters. In recent years some data sheet driven behavioral models or so called 'wizard' tools have been introduced to solve this problem. In this contribution some experiences with some user-friendly power semiconductor models will be discussed. Using special simulation test circuits it is possible to get information on the static and dynamic behavior of the parameterized models before they are applied in more complex schemes. These results can be compared with data sheets or with measurements. The application of these models for power loss analysis of inverter type arc welding power sources will be described.

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Rehabilitation assistive technology in adaptation to disabled job Effect on the use of research (장애인 직무적응에 대한 재활보조공학 이용 효과 연구)

  • Jeong, S.H.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.7 no.1
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    • pp.59-66
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    • 2013
  • This study rehabilitation assistive technology system for people with disabilities employed by a company in the field of occupations and job satisfaction have adapted to, and for the rehabilitation assistive technology support(rehabilitation assistive technology hardware and the software) and service quality based on the quality of convenient for employees to work life by analyzing the factors that can act on adaptation employees on behavioral intentions was to determine the overall impact. Seoul, Gyeonggi, Incheon companies based in vocational education and training received in the employment of the disabled subject questionnaires were distributed, and finally 594 valid questionnaires were minor. In order to test the hypothesis SEM(structural equation model) were used, the results of this study can be summarized as follows. First, rehabilitation assistive technology hardware quality of the quality of rehabilitation assistive technology software affected. Second, rehabilitation assistive technology software quality on the quality of the service quality affected. Third, rehabilitation assistive technology hardware quality on the quality of the service quality affected. Fourth, quality of service, the quality of the adaptation of action for employees affected also. Fifth, rehabilitation assistive technology software for adaptive quality of the employees also had an impact on behavior. Sixth, rehabilitation assistive technology hardware to adapt the quality of the employees affected. And parameters (quality of service quality) influenced to as indirect effects. The results of this study support the rehabilitation assistive technology and rehabilitation assistive technology hardware and software) based, quality of service and quality of fused form acceptable to, the degree of action for employees to adapt more implications that may affect have provided.

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State-Based Behavior Modeling in Software and Systems Engineering

  • Sabah Al-Fedaghi
    • International Journal of Computer Science & Network Security
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    • v.23 no.5
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    • pp.21-32
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    • 2023
  • The design of complex man-made systems mostly involves a conceptual modeling phase; therefore, it is important to ensure an appropriate analysis method for these models. A key concept for such analysis is the development of a diagramming technique (e.g., UML) because diagrams can describe entities and processes and emphasize important aspects of the systems being described. The analysis also includes an examination of ontological concepts such as states and events, which are used as a basis for the modeling process. Studying fundamental concepts allows us to understand more deeply the relationship between these concepts and modeling frameworks. In this paper, we critically analyze the classic definition of a state utilizing the Thinging machine (TM) model. States in state machine diagrams are considered the appropriate basis for modeling system behavioral aspects. Despite its wide application in hardware design, the integration of a state machine model into a software system's modeling requirements increased the difficulty of graphical representation (e.g., integration between structural and behavioral diagrams). To understand such a problem, in this paper, we project (create an equivalent representation of) states in TM machines. As a case study, we re-modeled a state machine of an assembly line system in a TM. Additionally, we added possible triggers (transitions) of the given states to the TM representation. The outcome is a complicated picture of assembly line behavior. Therefore, as an alternative solution, we re-modeled the assembly line based solely on the TM. This new model presents a clear contrast between state-based modeling of assembly line behavior and the TM approach. The TM modeling seems more systematic than its counterpart, the state machine, and its notions are well defined. In a TM, states are just compound events. A model of a more complex system than the one in the assembly line has strengthened such a conclusion.

Automated Analysis Approach for the Detection of High Survivable Ransomware

  • Ahmed, Yahye Abukar;Kocer, Baris;Al-rimy, Bander Ali Saleh
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2236-2257
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    • 2020
  • Ransomware is malicious software that encrypts the user-related files and data and holds them to ransom. Such attacks have become one of the serious threats to cyberspace. The avoidance techniques that ransomware employs such as obfuscation and/or packing makes it difficult to analyze such programs statically. Although many ransomware detection studies have been conducted, they are limited to a small portion of the attack's characteristics. To this end, this paper proposed a framework for the behavioral-based dynamic analysis of high survivable ransomware (HSR) with integrated valuable feature sets. Term Frequency-Inverse document frequency (TF-IDF) was employed to select the most useful features from the analyzed samples. Support Vector Machine (SVM) and Artificial Neural Network (ANN) were utilized to develop and implement a machine learning-based detection model able to recognize certain behavioral traits of high survivable ransomware attacks. Experimental evaluation indicates that the proposed framework achieved an area under the ROC curve of 0.987 and a few false positive rates 0.007. The experimental results indicate that the proposed framework can detect high survivable ransomware in the early stage accurately.

LSTM(Long Short-Term Memory)-Based Abnormal Behavior Recognition Using AlphaPose (AlphaPose를 활용한 LSTM(Long Short-Term Memory) 기반 이상행동인식)

  • Bae, Hyun-Jae;Jang, Gyu-Jin;Kim, Young-Hun;Kim, Jin-Pyung
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.5
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    • pp.187-194
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    • 2021
  • A person's behavioral recognition is the recognition of what a person does according to joint movements. To this end, we utilize computer vision tasks that are utilized in image processing. Human behavior recognition is a safety accident response service that combines deep learning and CCTV, and can be applied within the safety management site. Existing studies are relatively lacking in behavioral recognition studies through human joint keypoint extraction by utilizing deep learning. There were also problems that were difficult to manage workers continuously and systematically at safety management sites. In this paper, to address these problems, we propose a method to recognize risk behavior using only joint keypoints and joint motion information. AlphaPose, one of the pose estimation methods, was used to extract joint keypoints in the body part. The extracted joint keypoints were sequentially entered into the Long Short-Term Memory (LSTM) model to be learned with continuous data. After checking the behavioral recognition accuracy, it was confirmed that the accuracy of the "Lying Down" behavioral recognition results was high.

Context-Awareness Cat Behavior Captioning System (반려묘의 상황인지형 행동 캡셔닝 시스템)

  • Chae, Heechan;Choi, Yoona;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • Journal of Korea Multimedia Society
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    • v.24 no.1
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    • pp.21-29
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    • 2021
  • With the recent increase in the number of households raising pets, various engineering studies have been underway for pets. The final purpose of this study is to automatically generate situation-sensitive captions that can express implicit intentions based on the behavior and sound of cats by embedding the already mature behavioral detection technology of pets as basic element technology in the video capturing research. As a pilot project to this end, this paper proposes a high-level capturing system using optical-flow, RGB, and sound information of cat videos. That is, the proposed system uses video datasets collected in an actual breeding environment to extract feature vectors from the video and sound, then through hierarchical LSTM encoder and decoder, to identify the cat's behavior and its implicit intentions, and to perform learning to create context-sensitive captions. The performance of the proposed system was verified experimentally by utilizing video data collected in the environment where actual cats are raised.

VERIFICATION OF PLC PROGRAMS WRITTEN IN FBD WITH VIS

  • Yoo, Jun-Beom;Cha, Sung-Deok;Jee, Eun-Kyung
    • Nuclear Engineering and Technology
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    • v.41 no.1
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    • pp.79-90
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    • 2009
  • Verification of programmable logic controller (PLC) programs written in IEC 61131-3 function block diagram (FBD) is essential in the transition from the use of traditional relay-based analog systems to PLC-based digital systems. This paper describes effective use of the well-known verification tool VIS for automatic verification of behavioral equivalences between successive FBD revisions. We formally defined FBD semantics as a state-transition system, developed semantic-preserving translation rules from FBD to Verilog programs, implemented a software tool to support the process, and conducted a case study on a subset of FBDs for APR-1400 reactor protection system design.