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8th International Conference on Intelligent Informatics and Biomedical sciences, ICIIBMS 2023

作者： Koeda, Masanao Kaihara, Yuto Sawada, Atsuro Hamada, Akihiro Magaribuchi, Toshihiro Ogawa, Osamu Onishi, Katsuhiko Noborio, Hiroshi Okayama Prefectural University Faculty of Computer Science and Systems Engineering 111 Kuboki Soja-shi Okayama Japan Kyoto University Department of Urology Graduate School of Medicine 54 Shogoin-kawahara-cho Sakyo-ku Kyoto Japan Osaka Electro-Communication University Faculty of Information Science and Arts Kiyotaki 1130-70 Shijonawate Osaka Japan

ISBN: (纸本)9798350369564

In this study, we describe an evaluation of the positional accuracy of stereo Visual SLAM with noisy feature points removed by blurring. We constructed an experimental environment that intentionally degrades the accuracy of Visual SLAM. In this environment, we placed the objects that are likely to generate noisy feature points. We evaluated the accuracy of the estimated positions of the original video and the video in which blurred regions of noise in the original video were provided to Visual SLAM. Consequently, we confirmed that the accuracy was improved compared to that of the original video. © 2023 IEEE.

关键词： Stereo image processing

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Deep Learning Based Facial Emotion Recognition using Multiple Layers Model

Deep Learning Based Facial Emotion Recognition using Multipl...

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2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021

作者： Sandra, Lidia Heryadi, Yaya Lukas Suparta, Wayan Wibowo, Antoni Krida Wacana Christian University Psychology Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665499699

A Facial Emotion Recognition (FER) system is an important tool to be implemented in any psychology academic field and beyond. This paper aims to show a system of Facial Emotion Recognition that can be done using the multiple layers model of ResN et50 which is an ANN. The dataset is an array that consists of 7 different emotions represented by the numbers 0-6. The emotion included in the dataset is 'anger', 'disgust', 'fear', 'happiness', 'sadness', 'shock', and 'neutrality'. This research found that the highest accuracy in the application of the model was recorded at 65% and the test was 60% to recognize facial emotion from a graphical input. © 2021 IEEE.

关键词： Emotion Recognition

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Visualization and Simulation of Any MPU Architecture Design with Meta-Instruction

Visualization and Simulation of Any MPU Architecture Design ...

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International Symposium on Communications and information Technologies (ISCIT)

作者： Tomoyuki Morimoto Ziming Wang Jiahui Luo Sota Ogawa Toshiyuki Tsutsumi Department of Computer Science School of Science and Technology Meiji University Kanagawa Japan VIAX Co. Ltd. Computer Science Program Graduate School of Science and Technology Meiji University Kanagawa Japan Sony Semiconductor Solutions Corporation NEC Corporation PLUSEM Co. Ltd.

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

Our conventional architecture design tool converted instructions of microprocessor (MPU) into meta-instructions with both semantic and functional expressions, and it displayed a circuit diagram of the meta-instruction. The tool was able to perform dynamic simulation only on an educational processor called COMET. However, the meta-instruction must be able to express the arbitrary instruction of at least different significant existing MPUs in order to design arbitrary MPUs. Furthermore, it should be possible to visualize all instructions and then execute them. Therefore, we have improved the meta-instruction so that the architecture design tool applies to major MPUs: MIPS, ARM, and RISC-V in addition to COMET. The improved architecture design tool visualizes and simulates the circuit diagram of the improved meta-instruction. The result shows the possibility of the meta-instruction-based architecture design tool being able to design any MPU.

关键词： Comets Visualization Translation Microprocessors Semantics Hardware Design tools information and communication technology Engines

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Intelligent Models for Forecasting Repair Timing of Leakage Water Pipelines

Intelligent Models for Forecasting Repair Timing of Leakage ...

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Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), International

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

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.

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KANVAS: A Network information Sharing Framework Based on Network Ontology Bonsai 22

KANVAS: A Network Information Sharing Framework Based on Net...

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17th Asian Internet Engineering Conference, AINTEC 2022

作者： Kuchii, Kanta Kondo, Takao Teraoka, Fumio Graduate School of Science and Technology Keio University Kanagawa Yokohama Japan Computer Security Incident Response Team Keio University Minato-ku Tokyo Japan Faculty of Science and Technology Keio University Kanagawa Yokohama Japan

ISBN: (纸本)9781450399814

Demands for acquiring Internet behavior are increasing for Internet-scale network understanding such as inter-AS path management and traffic engineering. Although there are several efforts to make Internet behavior public, most of the public information is not structured and it is hard for applications to use such information. This paper proposes a network information sharing framework called KANVAS. It defines a network ontology called Bonsai which models network structure from viewpoints of physical, logical, service, and operation network structures. Bonsai can express network virtualization technologies such as link aggregation (LAG), VLAN, L2 over L3 tunneling, and virtual routing and forwarding (VRF). Applications can access network information via useful API. As a first step of development of KANVAS and Bonsai, this paper describes network information sharing within a single domain focusing on failure localization and throughput monitoring as examples. Evaluation results on a PoC system show that the time for failure localization is short enough and a throughput monitoring tool can choose appropriate monitoring points. © 2022 ACM.

关键词： Ontology

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LOA-RPL:Novel Energy-Efficient Routing Protocol for the Internet of Things Using Lion Optimization Algorithm to Maximize Network Lifetime

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computers, Materials & Continua 2021年第10期69卷 351-371页

作者： Sankar Sennan Somula Ramasubbareddy Anand Nayyar Yunyoung Nam Mohamed Abouhawwash Department of Computer Science Engineering Sona College of TechnologySalem636005India VNR Vignana Jyothi Institute of Engineering&Technology Hyderabad500090India Graduate School Duy Tan UniversityDa NangVietnam550000Vietnam Faculty of Information Technology Duy Tan UniversityDa NangVietnam550000Vietnam Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Electrical and Computer Engineering Michigan State UniversityEast LansingMI48824USA

Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained *** is an effective technique for saving energy by reducing duplicate *** a clustering protocol,the selection of a cluster head(CH)plays a key role in prolonging the lifetime of a ***,most cluster-based protocols,including routing protocols for low-power and lossy networks(RPLs),have used fuzzy logic and probabilistic approaches to select the CH ***,early battery depletion is produced near the *** overcome this issue,a lion optimization algorithm(LOA)for selecting CH in RPL is proposed in this ***-RPL comprises three processes:cluster formation,CH selection,and route establishment.A cluster is formed using the Euclidean *** selection is performed using *** establishment is implemented using residual energy *** extensive simulation is conducted in the network simulator ns-3 on various parameters,such as network lifetime,power consumption,packet delivery ratio(PDR),and *** performance of LOA-RPL is also compared with those of RPL,fuzzy rule-based energyefficient clustering and immune-inspired routing(FEEC-IIR),and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm(RISARPL).The performance evaluation metrics used in this study are network lifetime,power consumption,PDR,and *** proposed LOARPL increases network lifetime by 20%and PDR by 5%–10%compared with RPL,FEEC-IIR,and ***-RPL is also highly energy-efficient compared with other similar routing protocols.

关键词： Internet of things cluster head clustering protocol optimization algorithm lion optimization algorithm network lifetime routing protocol wireless sensor networks energy consumption low-power and lossy networks

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A Sustainable Approach for Determining Compromise Ranking Based on Intuitonistic Fuzzy Score Functions

A Sustainable Approach for Determining Compromise Ranking B...

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Special Sessions in the Advances in information Systems and Technologies Track, AIST 2022 and 17th Conference on information Systems Management, ISM 2022 held as part of the Federated Conference on computer science and information Systems, FedCSIS 2022

作者： Paradowski, Bartosz Kizielewicz, Bartlomiej Więckowski, Jakub Salabun, Wojciech Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin Poland National Institute of Telecommunications Szachowa 1 Warsaw04-894 Poland

ISBN: (纸本)9783031295690

Many real-world decision-making problems require some degree of uncertainty to be taken into account. For purpose of representing such problems, intuitionistic fuzzy sets are used, however, most well-known multi-criteria decision-making methods operate in a crisp environment. In this paper, we present an assessment of score functions that are used to convert fuzzy numbers into crisp ones. Five score functions were selected to assess their usefulness and effectiveness. Those functions were used to transform the theoretical fuzzy decision matrix problems into a crisp environment for evaluating alternatives using the Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS) method. In addition, the compromise between score functions is presented and compared with the other results. The research showed that score functions are useful tools when dealing with problems in an uncertain environment and might prove helpful for decision-makers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems

Implementation of Face Patterns and Smile Recognition for In...

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International Conference of computer and Informatics Engineering (IC2IE)

作者： Miftakhurrokhmat Teddy Suparyanto Gregorius Natanael Elwirehardja Shofiyati Nur Karimah Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Students “attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students” attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification.

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3D LiDAR-Based Lane Line Recognition and Obstacle Avoidance for Autonomous Mobile Robot - A Robust Approach without Image Sensors

3D LiDAR-Based Lane Line Recognition and Obstacle Avoidance ...

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SICE Annual Conference

作者： Takuya Yamakawa Koki Kubota Kazuyuki Kobayashi Tomoyuki Ohkubo Kaiqiao Tian Nashwan J Sebi Ka C Cheok Cai Changqing Graduate School of Science and Engineering Hosei University Tokyo Japan Faculty of Advanced Engineering Nippon Institute of Technology Saitama Japan Electrical & Computer Engineering Department School of Engineering & Computer Science Oakland University Rochester MI USA School of Electrical Engineering and Information Technology Changchun Institute of Technology China

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

The Intelligent Ground Vehicle Competition (IGVC) is an annual competition for autonomous mobile robots held in the U.S. One of the vital functions of success in this competition is the autonomous lane-following function, which requires stable lane line recognition while avoiding obstacles and staying within lanes. The most popular approach for lane line recognition employs image sensors such as cameras. However, this approach has inherent weaknesses due to changes in outdoor lighting conditions, which are caused by limitations in the dynamic range of the image sensor. To overcome the weaknesses of image sensor-based lane line recognition, we propose a new method that utilizes the reflection intensity of the point cloud acquired by 3D LiDAR. The combination of point clouds and intensity enables the detection of both lane lines and obstacles without the effect of lighting condition changes. In this paper, we propose a novel, safer, and more robust lane-following algorithm that uses only 3D LiDAR, without the need for an image sensor. Lane line detection is performed by extracting a group of points with reflection intensities within a certain range while estimating the direction of the lane line and using a reflection intensity threshold value. Detected lane lines and obstacles are represented as a one-dimensional evaluation cost function, and a local target destination is determined in the direction with the lowest cost. This enables robust control regardless of outdoor lighting conditions. The performance of lane-following, obstacle avoidance, and real-time operation were evaluated in a simulation environment.

关键词： Point cloud compression Image sensors Three-dimensional displays Laser radar Image recognition Velocity control Lighting Reflection Real-time systems Collision avoidance

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Securing Healthcare Data in IoMT Network Using Enhanced Chaos Based Substitution and Diffusion

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computer Systems science & Engineering 2023年第11期47卷 2361-2380页

作者： Musheer Ahmad Reem Ibrahim Alkanhel Naglaa FSoliman Abeer D.Algarni Fathi E.Abd El-Samie Walid El-Shafai Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia

Patient privacy and data protection have been crucial concerns in Ehealthcare systems for many *** modern-day applications,patient data usually holds clinical imagery,records,and other medical ***,the Internet of Medical Things(IoMT),equipped with cloud computing,has come out to be a beneficial paradigm in the healthcare ***,the openness of networks and systems leads to security threats and illegal ***,reliable,fast,and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT *** paper presents an image protection scheme for healthcare applications to protect patients’medical image data exchanged in IoMT *** proposed security scheme depends on an enhanced 2D discrete chaotic map and allows dynamic substitution based on an optimized highly-nonlinear S-box and diffusion to gain an excellent security *** optimized S-box has an excellent nonlinearity score of *** new image protection scheme is efficient enough to exhibit correlation values less than 0.0022,entropy values higher than 7.999,and NPCR values around 99.6%.To reveal the efficacy of the scheme,several comparison studies are *** comparison studies reveal that the novel protection scheme is robust,efficient,and capable of securing healthcare imagery in IoMT systems.

关键词： Secure communication healthcare data encryption Internet of Medical Things(IoMT) discrete chaotic map substitution box(S-box)

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