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An Internet of Things Assisted Autism Spectrum Disorder Prediction Using Deep Learning Principles with Medical Image Processing Assistance

An Internet of Things Assisted Autism Spectrum Disorder Pred...

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2024 International Conference on Innovative Computing, Intelligent communication and Smart Electrical systems, ICSES 2024

作者： Bindhu, A. Mol, A. Sruthi Ravi, T. Bodkhe, R.G. Safori, Amjad Omar Vijayalakshmi, S. Infant Jesus College of Arts and Science for Women Department of Computer Science Mulagumoodu India Sathyabama Institute of Science and Technology Department of Ece Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India R.M.K. Engineering College Department of Electronics and Communication Engineering Chennai India Zaraa University Faculty of Media Department of Journalism and Digital Media Zaraa 13110 Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

Characteristics of the complex neuro-developmental condition Autism Spectrum condition (ASD) include impaired social communication and restricted, repetitive patterns of behavior. This study presents a novel approach for identifying ASD in young infants by integrating deep learning, Internet of Things (IoT) and medical image processing. The goal of this research is to create comprehensive and discriminative features by combining wearable sensor data with brain imaging and smart home environments. For the greatest results, early diagnosis is essential. The proposed method called IoT based Autism Predictive Framework (IoTAPF) has a high detection rate of 97.8% and is cross-validated against the current Learning based Autism Detection Strategy (LADS). The proposed approach aims at improving diagnostic specificity which helps in forecasting behaviors and thus pushing earlier interventions, providing better support for ASD individuals and their families. The paper discusses the design and implementation of the framework, including sensor integration, data management, and predictive modeling. Preliminary results from pilot studies are presented, demonstrating the framework's potential to improve diagnostic accuracy and support individualized care plans. The proposed solution represents a significant advancement in the application of IoT technology for early autism detection and management, paving the way for more proactive and data-driven approaches in the field of neuro-developmental disorders. © 2024 IEEE.

关键词： Diseases

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Development of Two Dimension (2D) Game Engine with Finite State Machine (FSM) Based Artificial Intelligence (AI) Subsystem 2

Development of Two Dimension (2D) Game Engine with Finite St...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Adeniyi, Abidemi Emmanuel Brahma, Biswajit Adebiyi, Marion Olubunmi Awotunde, Joseph Bamidele Jimoh, Rasheed Gbenga Olasinde, Enoch Bandyopadhyay, Anjan Department of Computer Science Bowen University Osun State Iwo Nigeria McKesson Corporation 32559 Lake Bridgeport St FremontCA94555 United States Department of Computer Science Landmark University Omu-Aran Nigeria Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Nigeria School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India

With Al becoming more and more relevant in today's world, this project aims to develop a 2D game engine with an Al subsystem for state-driven agents, which is rarely implemented by a lot of 2D engines out there. In this study, a 2D game engine was designed with an FSM (Finite State Machine) - based AL subsystem using state-driven game agents. The engine was implemented using the Javascript programming language and the WebGL 2.0 graphics library/API. It is targeted at web-based games/simulations. Components and subsystems include physics, audio, math, rendering, and AI (based on finite-state machines). The FSM-based AI subsystem is a solution aimed at reducing the ambiguity and performance hits associated with creating 2D game AI in the naive approach. The AI subsystem creates an interface for 2D games to be created with a common paradigm, and simulated with a great level of realism. The state machine used in this study is used to represent a variety of behaviours, such as wandering, attacking, and fleeing. The following conclusions were drawn as regards the impact of the AI approach used on rendering performance;the naive approach to implementing game AI is also compared with the FSM approach in terms of rendering (frames per second/ FPS, or frame rate). With the naive approach (vector math) being used to implement AI, there was a drop in the rendering frame rate to 50 FPS. The FSM approach didn't affect the frame rate, which is usually at 60FPS. With a well-developed FSM (Finite State Machine), game agents can transition between states easily as a response to user input or stimulus from the game environment. The proposed method was tested by creating a prototype game with the 2D game engine. The prototype game was a straightforward side-scrolling platformer featuring a cast of non-player characters (NPCs). This approach to implementing 2D game AI goes a long way toward improving performance and mitigating ambiguity in the code. © 2024 Elsevier B.V.. All rights rese

关键词： Artificial intelligence

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Opto-Video Encryption Based on Logistic Adjusted Sine map in FrFT

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computers, Materials & Continua 2022年第8期72卷 3651-3663页

作者： Osama S.Faragallah Ashraf Afifi Ibrahim F.Elashry Ensherah A.Naeem Heba M.El-Hoseny Ahmed I.Sallam Hala S.El-sayed Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Electrical Engineering Kafrelsheikh UniversityKafrelsheikh 61519Egypt Electrical Department Faculty of Industrial EducationSuez UniversitySuez 43527Egypt Department of Electronics and Electrical Communication Engineering Al-Obour High Institute for Engineering and Technology 3036Egypt Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom 32511Egypt

In the last few years,videos became the most common form of information transmitted over the internet,and a lot of the traffic is confidential and must be protected and delivered safely to its intended *** introduces the challenges of presenting encryption systems that can encode videos securely and efficiently at the same *** paper presents an efficient opto-video encryption system using Logistic Adjusted Sine map(LASM)in the Fractional Fourier Transform(FrFT).In the presented opto-video LASM-based FrFT scheme,the encoded video is split into distinct frames and transformed into optical signals utilizing an optical *** of the developed optical video frames is ciphered by utilizing the LASM in optical FrFT system using two-phase modulation forms on the video frame,the first in the time-domain and the second in the FrFT *** the end,the ciphervideo frame is spotted utilizing a CCD digital camera and transformed into a digital structure that can be managed using a *** test the proposed opto-video LASM-based FrFT scheme using various security *** outcomes demonstrate that the presented scheme can effectively encrypt and decrypt video *** addition,it encrypts videos with a high level of encryption qualitywithout sacrificing its resistance to noise ***,the test outcomes demonstrate that the presented scheme is immune to known attacks.

关键词： Optical encryption FrFT logistic-adjusted sine map

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Correction to: Automated approach to predict cerebral stroke based on fuzzy inference and convolutional neural network (Multimedia Tools and Applications, (2024), 10.1007/s11042-024-19254-0)

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Multimedia Tools and Applications 2024年 1-2页

作者： Alrowais, Fadwa Jamjoom, Arwa A. Karamti, Hanen Umer, Muhammad Alsubai, Shtwai Abate, Andrea F. Ashraf, Imran Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science The Islamia University of Bahawalpur Bahawalpur Pakistan Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University P.O. Box 151 Al-Kharj11942 Saudi Arabia Department of Computer Science University of Salerno Fisciano84084 Italy Department of Information and Communication Engineering Yeungnam University Gyeongsan38541 Korea Republic of

The original publication of this article contains an error in the affiliation of authors Fadwa Alrowais and Hanen Karamti. Incorrect: department of Information systems, College of computer and Information sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia Correct: department of computer sciences, College of computer and Information sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia The original article has been corrected. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

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Enhanced Condition Monitoring of Low Voltage Motors in Harsh Environments with Ladybug Beetle Optimization and Context-Aware Graph Convolutional Networks 4

Enhanced Condition Monitoring of Low Voltage Motors in Harsh...

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4th International Conference on Sustainable Expert systems, ICSES 2024

作者： Rajasekar, P. Tiwari, Praveen Prakash Sharmila, L. Garg, Akriti Srinivas, Rayudu Tallapragada, V. V. Satyanarayana Srm Institute of Science and Technology Department of Data Science and Business System Tamil Nadu Kattankulathur603203 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai600062 India Mahatma Jyotiba Phule Rohilkhand University Department of Electrical Engineering Uttar Pradesh Bareilly243006 India Aditya College of Engineering & Technology Department of Electrical and Electronics Engineering Andhra Pradesh Surampalem533437 India School of Engineering Mohan Babu University Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India

ISBN: (纸本)9798331540364

Low voltage motors are essential in many applications in contemporary industrial settings, as they power machines and guarantee efficient operations. However, these motors often operate in harsh environments where they are exposed to factors such as extreme temperatures, moisture, dust, and vibrations, which can lead to premature wear and failure. This paper proposes a hybrid method for low voltage motor condition monitoring in challenging industrial environments. The proposed method is the combined execution of Ladybug Beetle Optimization algorithm (LBOA) and Heterogeneous Context-Aware Graph Convolutional Network (HCAGCN). Hence it is named as LBOA-HCAGCN technique. Initially, the input data is collected from Triboelectric vibration sensors. Then, the collected data is fed into preprocessing utilizing Generalized Multi-kernel Maximum Correntropy Kalman Filter (GMKMCKF). This filter normalizes and cleans the data by effectively removing noise. Recursive Hilbert Transform (RHT) is used to extract time domain features such as mean, Root Mean Square (RMS), Peak-to-Peak Value, Skewness, and Kurtosis. Then the extracted features are given to HCAGCN for classify the motor health conditions such as normal, broken-bar, bowed-bar, bowed-rotor, faulty bearing, and voltage imbalance. In general, HCAGCN does not express adapting optimization strategies to determine optimal parameters to classify motor conditions. Hence, the LBOA is used to optimize the weight parameter of the HCAGCN which accurately classify motor conditions. The proposed LBOA-HCAGCN is implemented in MATLAB. Performance indicators such as Mean Absolute Error (MAE), Precision, and Accuracy were used to analyze the effectiveness of the proposed approach. Comparing the proposed LBOA-HCAGCN methodology to other existing techniques like Deep Residual Neural Network (DRNN), Convolutional Neural Network (CNN), and Recursive Neural Network (RNN), it achieves 25.8%, 26.4%, and 24.7% greater accuracy, 26.7%, 29.4%, and

关键词： Mean square error

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Smart Happy Device with IoT : For those who suffer anxiety, stress, and depression 12

Smart Happy Device with IoT : For those who suffer anxiety, ...

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12th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2024

作者： Yakub, Fitri Azizan, Azizul Dhamanti, Inge Khudzari, Ahmad Zahran Md. Govindan, Niranjana Muljono, Muljono UTM Malaysia-Japan International Institute of Technology Electronic System Engineering Department Kuala Lumpur Malaysia Universiti Teknologi Malaysia Cyberphysical Research Group Embedded AI & ML Science Lab Faculty of Artificial Intelligence Kuala Lumpur Malaysia Universitas Airlangga Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia UTM Faculty of Engineering Department of Biosciences & Medical Engineering Johor Bahru Malaysia SRMIST Faculty of Engineering & Technology Department of Computing Technologies Chennai India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350340204

Due to the rising cases of Covid-19 in the world especially in Malaysia, the impact had been hit hard for many people. Due to this all people must be isolated in their home. It has affected the well-being and working life of millions of people across the world. Due to this disease, the mental health among people has increased significantly for the past 2 years. According to MoH, out of 983 Malaysian students, about 20.4%, 6.6%, and 2.8% are experienced minimal to moderate, marked to severe, and most extreme levels of anxiety, respectively. The main stressors are the remote online teaching, and uncertainty about the future regarding study and career which can affect mental health. Thus, the main objective of this project is to develop a product that may provide different medication methods to its users by helping people who suffer anxiety, stress, and depression. We used aromatherapy, positive quotes, and music therapy in order to release stress. The user can also check his or her pulse rate by only touching the fingerprint through the sensor. The microcontrollers used in this project are Arduino Uno and Arduino Mega to build the project circuit. The experimental results can improve body health, mind and spirit which enhances both physical and emotional health. © 2024 IEEE.

关键词： COVID-19

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Fake Currency Note Recognition using Extreme Learning Machine 2

Fake Currency Note Recognition using Extreme Learning Machin...

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2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Kumar, Rajeev Lamba, Anil Kumar Mohammed, Sayed Asokan, Anju Aswal, Upendra Singh Kolavennu, Subbarao Gopal Narayan Singh University Faculty of Information Technology Bihar Jamuhar India Psna College of Engineering and Technology Ece Tamilnadu Dindigul India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India School of Computer Science and Engineering Geeta University Delhi India Sri Eshwar College of Engineering Kinathukadavu Department of Computer and Communication Engineering Tamilnadu Coimbatore India Sphoorthy Engineering College Cse Cyber Security Department Telangana Hyderabad India

ISBN: (纸本)9781665456302

Color printing technology has made it simpler for forgers to make and copy large numbers of fake currency. The production of legible banknotes was once the sole purview of print shops, but today even a novice printer with a simple laser printer can do the job. Because of this, the prevalence of counterfeit money has increased dramatically. A number of problems, including corruption and the existence of 'black money,' have hounded India for a long time. There is also a serious problem with the circulation of counterfeit currency. The outcome is a system that can detect fake currency with greater speed and precision. It is a serious crime to create counterfeit currency, which is money that has not been authorized by the government. The vast majority of them do this professionally. The circulation of counterfeit currency retards economic development and devalues legitimate currency. In this study, it uses image processing to the problem of identifying fake Indian notes. This technique finishes the initial acquisition before the image is processed further. Pre-processing includes actions such as cropping, smoothing, and modifying the image;converting the image to greyscale;applying image segmentation;extracting features;and resizing the image. The model is then trained using an ELM. Proposed model exceeds both the CNN and SVM models in terms of accuracy, at around 97.8 percent. © 2023 IEEE.

关键词： Crime

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Preventive and proactive planning of PaaS maintenance service teams

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IFAC-PapersOnLine 2024年第19期58卷 778-783页

作者： Eryk Szwarc Grzegorz Bocewicz Arkadiusz Gola Robert Wójcik Zbigniew Banaszak Faculty of Electronics and Computer Science Koszalin University of Technology Poland Department of Production Computerisation and Robotisation Faculty of Mechanical Engineering Lublin University of Technology Poland Department of Computer Engineering Faculty of Information and Communication Technology Wrocław University of Science and Technology Poland

This paper employing the Product-as-a-Service (PaaS) paradigm provides a model integrating preventive and proactive management strategies to maintain the required service level availability in MultiFunction Device (MFD) offerings. The problems of resource allocation and servicing problems implied by these strategies focus on planning leasing offers that meet an acceptable failure risk level and routing service teams participating in maintenance missions. The aim is to allocate services that provide balanced risk to suppliers and renters, reduce delays, and prioritize urgent cases by routing a fleet of technical vehicles responsible for delivering and receiving service teams without the constraint of requiring the exact vehicle for both operations. The conducted computer experiments demonstrated the effectiveness of the adopted reference model, allowing for increasing PaaS availability and minimizing service costs.

关键词： Product-as-a-Service preventive proactive planning vehicle routing resource allocation

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Drone Gesture Control using OpenCV and Tello 8

Drone Gesture Control using OpenCV and Tello

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8th Conference on Information communication Technology and Society, ICTAS 2024

作者： Khoza, Nokuthula Owolawi, Pius Malele, Vusumuzi Soshanguve Campus Tshwane University of Technology Faculty of Information and Communication Technology Department of Computer Systems Engineering Pretoria South Africa North-West University Unit for Data Science and Computing School of Computer Science and Information Systems Vanderbijlpark Campus Vanderbijlpark South Africa

ISBN: (纸本)9798350314892

Tracking a person with an onboard camera is a very difficult and perhaps technically impossible if one camera is used. In this regard, real-life projects use a series of cameras to achieve the task. The advent of camera installed drone technology has made it possible for researchers and designers to resolve the tracking issues of a single or multiple stagnant devices. This paper presents a method that makes it possible for a drone to recognize hand gestures as control mechanism and follow the person who control it. Furthermore, the method assists in drone object detection using an integrated depth camera that provides video capturing. The OpenCV and Tello were used in this project. A stabilized depth video is for use with current person trackers like the OpenCV tracker. The estimated Tello pose deduced from vision to stabilize the depth image by warping it to a virtual-static camera. This method allows the Tello to obtain not only the tracked person's position and orientation but also their full body pose, which can then be used, for instance, to recognize hand gestures and alter the Tello's behavior. This work has a potential of contributing or enhancing cutting-edge applications such as hands-free photography and videography. © 2024 IEEE.

关键词： Drones

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Model-Based Testing of Access Control Requirement in Multi-tenant Application: An Extensive Life Cycle 1

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3rd International Conference on computer science, Electrical and Electronic engineering, ICCEE 2021

作者： Duraisamy, Gunavathi Ghani, Abdul Azim Abd Zulzalil, Hazura Abdullah, Azizol Faculty of Computer Science and Information Technology Department of Software Engineering and Information System Universiti Putra Malaysia Selangor Serdang Malaysia Faculty of Computer Science and Information Technology Department of Communication Technology and Networking Universiti Putra Malaysia Selangor Serdang Malaysia Lee Kong Chian Faculty of Engineering and Science Department of Internet Engineering and Computer Science Universiti Tunku Abdul Rahman Sungai Long Campus Selangor Kajang Malaysia

ISBN: (数字)9789811697814

ISBN: (纸本)9789811697807

Model-based testing is a substantial approach that is based on and involving models. It is well known for achieving test coverage and for generating and executing test cases automatically. The main and core activity of model-based testing is the modelling activity. Models are used to explain and represent the behaviour of the product. The requirement will be translated into models and those models will be used in generating the test cases automatically in model-based testing. The modelling activity clarifies test requirement and contribute to automatic generation and execution of large test suites with tool support. Model-based testing provides numerous advantages in testing;mainly on achieving appropriate test coverage and reduce manual effort and time spent since it can execute the test cases automatically. Despite all the benefit it can provide, there are some drawbacks too. However, the challenges faced can overcome by implementing proper test modelling activity and by adopting a well-versed test management activity. Thus, in this paper, we have studied the existing testing process, the taxonomy of model-based testing and model-based testing steps and proposed an extensive lifecycle for model-based testing with detail activities and steps to be carried out in order to test and validate access control requirement for multi-tenant application. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Access control

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