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Brain Tumor Detection and Segmentation Using RCNN

computers, Materials & Continua 2022年第6期71卷 5005-5020页

作者： Maham Khan Syed Adnan Shah Tenvir Ali Quratulain Aymen Khan Gyu Sang Choi Department of Computer Science University of Engineering&TechnologyTaxila47080Pakistan Faculty of Computing The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongbuk38541Korea

Brain tumors are considered as most fatal *** reduce the risk of death,early identification of the disease is *** of the best available methods to evaluate brain tumors is Magnetic resonance Images(MRI).Brain tumor detection and segmentation are tough as brain tumors may vary in size,shape,and *** makes manual detection of brain tumors by exploring MRI a tedious job for radiologists and doctors’.So an automated brain tumor detection and segmentation is *** work suggests a Region-based Convolution Neural Network(RCNN)approach for automated brain tumor identification and segmentation using MR images,which helps solve the difficulties of brain tumor identification efficiently and *** methodology is based on the accurate and efficient selection of tumorous *** reduces computational complexity and *** have validated the designed experimental setup on a standard dataset,BraTS *** used binary evaluation matrices based on Dice Similarity Coefficient(DSC)and Mean Average Precision(mAP).The segmentation results are compared with state-of-the-art methodologies to demonstrate the effectiveness of the proposed *** suggested approach attained an averageDSC of 0.92 andmAP 0.92 for 10 patients,while on the whole dataset,the scores are DSC 0.89 and mAP *** following results clearly show the performance efficiency of the proposed methodology.

关键词： Brain tumor MRI preprocessing image segmentation brain tumor localization medical ML RCNN BraTS 2020 LGG HGG

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Implementation and empirical comparison of partitioning-based multi-core scheduling

Implementation and empirical comparison of partitioning-base...

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IEEE International Symposium on Industrial Embedded systems

作者： Zhang, Yi Guan, Nan Xiao, Yanbin Yi, Wang Department of Computer Science and Technology Northeastern University China Department of Information Technology Uppsala University Sweden

ISBN: (纸本)9781612848204

Recent theoretical studies have shown that partitioning-based scheduling has better real-time performance than other scheduling paradigms like global scheduling on multi-cores. Especially, a class of partitioning-based scheduling algorithms (called semi-partitioned scheduling), which allow to split a small number of tasks among different cores, offer very high resource utilization. The major concern about the semi-partitioned scheduling is that due to the task splitting, some tasks will migrate from one core to another at run time, which incurs higher context switch overhead. So one would suspect whether the extra overhead caused by task splitting would counteract the theoretical performance gain of semi-partitioned scheduling. In this work, we implement a semi-partitioned scheduler in the Linux operating system, and run experiments on an Intel Core-i7 4-cores machine to measure the real overhead in both partitioned scheduling and semi-partitioned scheduling. Then we integrate the measured overhead into the state-of-the-art partitioned scheduling and semi-partitioned scheduling algorithms, and conduct empirical comparisons of their realtime performance. Our results show that the extra overhead caused by task splitting in semi-partitioned scheduling is very low, and its effect on the system schedulability is very small. © 2011 IEEE.

关键词： Scheduling

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Report on IWAIT 2020

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Kyokai Joho Imeji Zasshi/Journal of the Institute of Image information and Television Engineers 2020年第3期74卷 516-519页

作者： Mukai, Nobuhiko Itabashi, Ryunosuke Yagi, Nobuyuki Department of Computer Science Faculty of Information Technology Tokyo City University Tokyo Japan Graduate School of Environmental and Information Studies Tokyo City University Yokohama Japan Department of Information Systems Faculty of Informatics Tokyo City University Yokohama Japan

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Smart IoT system for Cardiopulmonary Resuscitation Training: Embedded Sensor Integration and Android Application 2

Smart IoT System for Cardiopulmonary Resuscitation Training:...

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2nd International Symposium on information technology and Digital Innovation, ISITDI 2024

作者： Aisuwarya, Ratna Erlina, Tati Mitzi, Richo Attir Universitas Andalas Faculty of Information Technology Computer Engineering Department Padang Indonesia

ISBN: (纸本)9798350389241

Lack of awareness and experience in CPR often discourages individuals from initiating rescue actions of Out-of-hospital cardiac arrest (OHCA). This research presents a new approach to CPR training using embedded system-based devices. This system, which resembles the human body's torso and head sections, monitors and calculates key parameters critical to successful CPR, including compression, airway management, and breathing techniques. Sensor nodes are placed to measure pressure during compression and monitor airway and respiratory processes. The collected data is transmitted and processed using Internet of Things (IoT) technology with a multi-user Android application, facilitating collaborative training sessions. Experimental testing validated the system's functional capabilities with successful network connection, real-time data transmission, and effective execution of CPR procedures. Hardware implementations use microcontrollers and sensors, with Arduino and NodeMcu ESP8266 enabling data processing and transmission. Software components developed within the Arduino IDE and Android Studio ensure efficient data handling and visualization. The results highlight the system's effectiveness in improving the accessibility and affordability of CPR training, potentially improving intervention by witnesses, and improving OHCA survival rates. © 2024 IEEE.

关键词： Resuscitation

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Model-Driven Engineering for Embedded systems with Non-Functional Properties Analysis Integration: A Review 16

Model-Driven Engineering for Embedded Systems with Non-Funct...

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16th International Conference on Developments in esystems Engineering, DeSE 2023

作者： Kadhim, Omar Jawad Nafea, Ahmed Adil Al-Thiabi, Mohamed Kareem Sallibi, Anas D. Modern Uuniversity for Business & Science Dept. Computer Science Beirut Lebanon College of Computer Science and Information Technology University of Anbar Dept. Artificail Inteligence Ramadi Iraq College of Computer Science and Information Technology University of Anbar Dept. Computer Science Ramadi Iraq College of Computer and Information Technology University of Anbar Department of Computer Sciences Ramadi Iraq

ISBN: (纸本)9798350381344

Model-Driven Engineering (MDE) has revolutionized the realm of embedded system development, providing an avenue for systematic, high-level system design, and automatic code generation. This paper delves into an enhanced approach to MDE, emphasizing the integration of nonfunctional properties analysis. Such an integration ensures that embedded systems not only perform their primary functions, but also adhere to crucial parameters like security, reliability, and efficiency. Through a comprehensive exploration of current tools and technologies, we identify gaps and opportunities in the current landscape. We further discuss the challenges inherent in marrying non-functional attributes with traditional system design and propose innovative solutions to navigate these complexities. Real-world case studies punctuate the discussion, offering tangible insights into the tangible benefits and practical challenges of this integrated approach. In conclusion, the seamless integration of nonfunctional properties into MDE emerges as a pivotal progression, heralding a new era of robust, efficient, and holistic embedded system development. © 2023 IEEE.

关键词： Embedded systems

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An Efficient Approach for Smart Cold Storage Management system Using IoT 6th

An Efficient Approach for Smart Cold Storage Management Syst...

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6th International Conference on Communications and Cyber-Physical Engineering, ICCCE 2023

作者： Krishna, A. Vijaya Mounika, Tandlay Geetha, G. Sai Pujitha, U. Bhavya, P. Akhila, M. Department of Computer Science and Technology GNITS Hyderabad India Department of Information Technology GNITS Hyderabad India

ISBN: (纸本)9789819971367

It has been estimated by the Food and Agriculture Organization that India loses forty percent of the food it produces every year as a result of food systems that are not connected to one another and inadequate supply networks. This loss takes place even before the digestive process starts. One solution to this issue is the implementation of intelligent cold storage systems for the purpose of storing and managing bulk commodities. Between the production and distribution stages, it facilitates the bulk handling of perishable items, with a particular focus on fruits and vegetables. It does this by adjusting a variety of different variables in order to keep the freshness of the objects in question. We are making use of the Internet to automate and simplify the process in order to get around the requirement that all traditional methods involve human participation. The chilli is often one of the vegetables that is thrown away in Telangana. But, only dswq2s of chilies will be the focus of this project’s development. We intend to make use of the Internet of Things in order to track the precise location of the warehouse in real time, in addition to the temperature, the humidity, and other gases including LPG, CO, and methane. In the course of our work, we make use of a wide range of sensors in conjunction with the software known as Particle Cloud to facilitate the transmission of data from the node to the base station, where it is processed and then presented to the user via a webpage. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cold storage

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PRESERVING, RESTORING, AND PASSING DOWN VIDEO-GAME MUSIC FROM THE PAST: THE CASE OF DIRECTMUSIC 19

PRESERVING, RESTORING, AND PASSING DOWN VIDEO-GAME MUSIC FRO...

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19th Sound and Music Computing Conference, SMC 2022

作者： Ludovico, Luca A. Mattea, Alberto Mauro, Davide A. Department of Computer Science University of Milan Italy Department of Computer and Information Technology Marshall University United States

ISBN: (纸本)9782958412609

Video-game music is a form of art that is gaining increasing interest, not only in the technological field but also in musicological research and in the area of Digital Humanities. Characterized by vanishing technological support and by the discontinuing of the software and hardware once used for its reproduction, the establishment of archives and standards that allow the fruition of such artifacts become of crucial importance. The goal of this project is to preserve, restore and pass down video-game music currently available only in an obsolete format. Our main case study will revolve around Microsoft DirectMusic technology, adopted in the 90s for composing music for video games and later discontinued. This work can be seen as a first effort at a larger goal that includes a discussion related to the philological process of what needs to be preserved and how, and the creation of accessible archives. Copyright: © 2022 Luca A. Ludovico, Alberto Mattea et al.

关键词： Image reconstruction

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Relay Selection Strategy in the Secure Cooperative Communications system

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Journal of Electronic science and technology 2017年第3期15卷 271-276页

作者： Hsin-Ying Liang Cheng-Ying Yang Wei-Liang Wu Department of Information and Communication Engineering Chaoyang University of Technology Taichung 41349 Department of Computer Science University of Taipei Taipei 11153 Department of Mathematics University of Taipei Taipei 11153

With the low cost and low hardware complex considerations,cooperative systems are a tendency in the future *** work considers the secure cooperative communications *** a practical situation in the system,the scenario includes multiple source stations,multiple relay stations,multiple destination stations,and *** analyze the optimal relay selection in the system,we begin with the performance analysis for a single source station and a single destination *** applying two cooperative models,the amplify-andforward（AF） mode and decode-and-forward（DF）mode,the secrecy capacity is ***,we apply the derived results to the considered environment to find the optimal relay *** the way,the relay selection can be obtained by the exhaustive search ***,there are a lot of steps needed if the number of source stations is ***,applying the characters of the cooperative modes in the relay selection,the pre-selection step is proposed with a mathematical *** could be used for the practical situation without a long-time calculation.

关键词： Index Terms--Amplify-and-forward （AF） mode,exhaustive search method fixed decode-and-forward（DF） mode mutual information relay selection secrecycapacity secure cooperative communications.

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Deep-piRNA:Bi-Layered Prediction Model for PIWI-Interacting RNA Using Discriminative Features

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computers, Materials & Continua 2022年第8期72卷 2243-2258页

作者： Salman Khan Mukhtaj Khan Nadeem Iqbal Mohd Amiruddin Abd Rahman Muhammad Khalis Abdul Karim Department of Computer Science Abdul Wali Khan University MardanKhyber Pakhtunkhwa23200Pakistan Department of Information Technology University of HaripurKhyber Pakhtunkhwa22620Pakistan Faculty of Science Universiti Putra MalaysiaUPM Serdang43400Malaysia

Piwi-interacting Ribonucleic acids(piRNAs)molecule is a wellknown subclass of small non-codingRNAmolecules that are mainly responsible for maintaining genome integrity,regulating gene expression,and germline stem cell maintenance by suppressing transposon *** piRNAs molecule can be used for the diagnosis of multiple tumor types and drug *** to the vital roles of the piRNA in computational biology,the identification of piRNAs has become an important area of research in computational *** paper proposes a two-layer predictor to improve the prediction of piRNAs and their function using deep learning *** proposed model applies various feature extraction methods to consider both structure information and physicochemical properties of the biological sequences during the feature extraction *** outcome of the proposed model is extensively evaluated using the k-fold cross-validation *** evaluation result shows that the proposed predictor performed better than the existing models with accuracy improvement of 7.59%and 2.81%at layer I and layer II *** is anticipated that the proposed model could be a beneficial tool for cancer diagnosis and precision medicine.

关键词： Deep neural network DNC TNC CKSNAP PseDPC cancer discovery Piwi-interacting RNAs Deep-piRNA

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Deep Learning-Based E-Learning Solution for Identifying and Bridging the Knowledge Gap in Primary Education

Deep Learning-Based E-Learning Solution for Identifying and ...

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2023 International Research Conference on Smart Computing and systems Engineering, SCSE 2023

作者： Arunoda, D.P.H. Walpola, S.R. Piumira, S.M.I. Athukorala, A.D.M.P. Thilakarathna, Thusithanjana Chandrasiri, Sanjeevi Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350341454

Educational teaching apps are primarily available in app stores to educate students in various contexts. Lack of educational resources, physical and mental health conditions, and poverty cause some students to skip school and move on to the next school grade without completing the course content of the previous grade. Most of the available apps focus on specific content to cover. The Smart Primary Education Tutor (SPET) teaching app specifically focuses on the missed content by analyzing their knowledge gap and providing lessons to cover the missed content. The main objective of SPET is to develop a methodology to identify the gap in student knowledge and fill the knowledge gap by teaching using smart techniques. SPET is determined to identify students' interactions (attention, emotions) with the system to identify students' ability to use the learning tool, identifying gaps in students' knowledge levels compared to their actual grades using activities and voice-based technologies, teaching to cover the knowledge gap by providing engaging activities and lessons and evaluating students by conducting a final assessment and analyze students' knowledge and performance obtained through the system. Students between the ages of 5 and 8 are targeted in the community to apply. The solution embeds deep learning-based models including attention classification models using head posture estimation, facial expression recognition, and eye gaze estimation, speech recognition models to identify provided verbal answers, handwriting recognition models to evaluate student performance, and smart teaching. The child emotion recognition model achieved 93% accuracy. The Attention span evaluation model achieved 85% accuracy. The handwritten numerical and English character data recognition model which detects answers for the final assessment paper achieved 85% percent of accuracy. © 2023 IEEE.

关键词： Students

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