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检索条件"任意字段=11th International Conference on Computer Technologies and Development, TechDev 2022"

共 1567 条记录，以下是71-80 订阅

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Imagined Speech Classification using EEG based Brain-computer Interface 11

Imagined Speech Classification using EEG based Brain-Compute...

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11th IEEE international conference on Communication Systems and Network technologies, CSNT 2022

作者： Pawar, Dipti Dhage, Sudhir Mumbai India

ISBN: (纸本)9781665480383

Imagined speech classification in Brain-computer Interface (BCI) has acquired recognition in a variety of fields including cognitive biometric, silent speech communication, synthetic telepathy etc. the major objective of this paper is to develop an imagined speech classification system based on Electroencephalography (EEG). In the proposed framework features are extracted using discrete wavelet transform (DWT) and maximum linear cross-correlation (MaxLCor). these combined features are fed to the multiclass support vector machine (SVM). In comparison to some of the most common classification algorithms in BCI, the suggested research produces promising results in classification accuracy, indicating the great potential to create BCI-based speech prosthesis controllers for various applications. © 2022 IEEE.

关键词： Electroencephalography

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Open Source Robotics Platform for Educational Purposes 11

Open Source Robotics Platform for Educational Purposes

引用

11th international Scientific conference on computer Science, COMSCI 2023

作者： Hranov, Tsveti Hristov Hinov, Nikolay Lyuboslavov Technical University of Sofia Department of Power Electronics Faculty of Electronic Engineering and Technologies 8 Kliment Ohridski blvd Sofia1000 Bulgaria

ISBN: (纸本)9798350325256

the paper presents a development of a platform for open-source robotics with the aim to introduce the topic to wider audience in a simpler and application-oriented manner. the platform consists of hardware designs, based on popular community projects, application software designed with modularity in mind. the design isn't tied specifically to any type of robot, rather it is encouraged to be ported on different robot types and to introduce the concept long used in the personal computers - the user is presented with the hardware to assemble the configuration and install software necessary for the chosen application. What separates this approach from the already developed solutions is the emphasis on simplicity and robustness, using a number of techniques, such as minimum dependencies, maximum usage of the chosen software libraries and simplified hardware design. Nonetheless expandability to a full blown system with computer vision, artificial intelligence and internet-of-things is still possible, due to the simplicity and modularity. © 2023 IEEE.

关键词： Robotics

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Automated Detection of Wheat Powdery Mildew Using YOLACT Instance Segmentation 11

Automated Detection of Wheat Powdery Mildew Using YOLACT Ins...

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11th international conference on Reliability, Infocom technologies and Optimization, ICRITO 2024

作者： Sharma, Jatin Kumar, Deepak Chattopadhay, Saumitra Kukreja, Vinay Verma, Aditya Chitkara University Institute Engineering and Technology Chitkara University Punjab India Graphic Era HillUniversity Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350350357

there is a 5% annual decline in wheat results worldwide due to Blumeria graminis f. sp. tritici (Bgt), which makes an accurate identification methodology important. this study addressed the challenges encountered in early wheat powdery mildew detection through the development of an innovative technique that makes use of the YOLACT model, a real-time object recognition system. the review of the literature covers a variety of approaches, such as deep learning and hyperspectral imaging, with an emphasis on YOLACT incorporation for improved early detection. the study describes dataset collection, YOLACT integration, and preparation methods. Having a 95.6%recognition rate, a mean Intersection over Union (MIoU) of 0.85, a precision of 0.81, and a mean average precision (mAP) of 0.56, the results illustrate the efficiency of the YOLACT model. Comparative assessments illustrate how much stronger the suggested YOLACT methodology is. the study concludes by highlighting the accuracy of the YOLACT model in detecting wheat powdery mildew and stressing the value of texture analysis and the best possible combination of vegetative indices (VIs) for early diagnosis. By fusing technology with realistic farming situations, the YOLACT model not only increases disease identification but also can entirely reinvent agriculture and increase crop cultivation's sustainability and efficiency practices © 2024 IEEE.

关键词： Hyperspectral imaging

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Advancing Industrial Effluent Monitoring Systems for Environmental Protection and Sustainable development 11

Advancing Industrial Effluent Monitoring Systems for Environ...

引用

11th international conference on Reliability, Infocom technologies and Optimization, ICRITO 2024

作者： Mitra, Milan Kumar, Akash Yadav, Lokesh Kaur, Mandeep School of Engineering & Technology Sharda University Department of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350350357

Industrial Effluent Monitoring Systems (IEMS) serve as vital tools for upholding environmental regulations and safeguarding public health and ecosystems. these systems are designed to assess the quality of wastewater discharged from industrial facilities, enabling monitoring of various parameters including pH, temperature, conductivity, Total Dissolved Solids (TDS), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), nutrients, heavy metals, and toxic organic compounds. the choice of parameters to monitor depends on the specific industry and the regulations that pertain to it. In recent years, there has been a notable shift towards automated IEMS, driven by their increased efficiency and accuracy. Automated systems offer the significant advantage of real-time data collection, which facilitates the early identification and prompt resolution of environmental issues, reducing the risk of non-compliance and pollution incidents. this paper presents a comprehensive overview of the latest advancements in IEMS technology and underscores their role in enhancing environmental protection. It also references related research, contributing to a broader understanding of the field. By embracing these innovative monitoring systems and staying abreast of technological developments, industries can not only ensure compliance but also minimize their ecological footprint, fostering a more sustainable and responsible approach to wastewater management. © 2024 IEEE.

关键词： Environmental regulations

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A Scientometric Review and Research Trends of Internet of things in Application of Smart City 11

A Scientometric Review and Research Trends of Internet of Th...

引用

11th international conference on ICT for Smart Society, ICISS 2024

作者： Maulana, Fairuz Iqbal Prasetyo Adi, Puput Dani Pramono, Andi Rahayu, Anita Persada, Satria Fadil Nadlifatin, Reny School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Research Center for Telecommunication National Research and Innovation Agency Bandung Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Information System Surabaya Indonesia

ISBN: (纸本)9798350389654

the Internet of things (IoT) has revolutionized the concept of Smart Cities by enabling the seamless integration of various technologies and devices to enhance urban living. this abstract presents a comprehensive overview of the research trends and advancements in IoT applications within Smart Cities from 2019 to 2023. By conducting a scientometric review and bibliometric analysis using R studio and VOSviewer software, this study aims to identify key focus areas, challenges, and opportunities in the implementation of IoT technologies in urban environments. Data selection from the Scopus database yielded a total of 3849 documents from 1515 sources. the most cited article from 2021 is 166 citations. Average citations per doc is 18.56. China, India, and Korea appear to dominate in terms of the number of published documents. Future research directions include exploring innovative solutions leveraging technologies like blockchain, edge computing, and artificial intelligence to improve the efficiency, sustainability, and resilience of Smart City initiatives. By synthesizing insights from existing literature and exploring emerging trends, this study contributes to the advancement of Smart Cities and the development of a more connected and intelligent urban future. © 2024 IEEE.

关键词： Sustainable city

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Cryptography and Fermat's Last theorem 11

Cryptography and Fermat's Last Theorem

引用

11th international Scientific conference on computer Science, COMSCI 2023

作者： Zyulyamova, Byulbyul Redzheb, Adnan Kopanov, Peter Technical University of Sofia Department of Computer Systems 8 Kliment Ohridski Blvd Sofia1756 Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Department of Cybersecurity 8 Kliment Ohridski Blvd Sofia1756 Bulgaria University of Plovdiv Paisii Hilendarski Faculty of Mathematics and Informatics Department of Mathematical Analysis 236 Bulgaria Blvd Plovdiv4027 Bulgaria

A non-trivial one-time pad (OTP) key generation scheme is proposed, allowing exchange or pre-negotiation of only very short messages. this scheme will eventually enable the wider use of one-time pad in modern cybersec... 详细信息

ISBN: (纸本)9798350325256

关键词： Fermat's last theorem finite additive group one-time pad OTP

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Achieving Energy Efficiency in Smart Home by Using Machine Learning Algorithm for Prediction 11

Achieving Energy Efficiency in Smart Home by Using Machine L...

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11th international Scientific conference on computer Science, COMSCI 2023

作者： Kutseva, Milka Technical University of Sofia Plovdiv Branch Department of Computer Systems and Technologies 25 Tzanko Dustabanov Plovdiv4000 Bulgaria

ISBN: (纸本)9798350325256

this article presents a system that can be utilized in Smart Homes without reducing the level of comfort for the residents. We provide a frequent sequential pattern mining approach that is appropriate for providing real-world event data for Smart Homes. With the aid of a network connection, the Smart Home allows the remote monitoring and control of equipment. In this paper we present the seven-layered IoT architecture, with the help of which the Smart Home was implemented. the main goal is to build a system that analyzes the monthly consumption data and predicts the future monthly consumption based on it. this was achieved by using machine learning approach in particular ***. there are different types of machine learning algorithms that are available for this purpose. this paper focuses mainly on forecasting algorithm called Singular Spectrum Analysis (SSA). © 2023 IEEE.

关键词： Forecasting

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Educating a Robot to Walk on Mars using Artificial Intelligence 18

Educating a Robot to Walk on Mars using Artificial Intellige...

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18th INDIAcom;11th international conference on Computing for Sustainable Global development, INDIACom 2024

作者： Mittal, Manisha Dewan, Prachi Panesar, Tanisha Singh, Mahender Guru Tegh Bahadur Institute of Technology Ggsipu Electronics and Communication Engineering New Delhi India Guru Tegh Bahadur Institute of Technology Ggsipu Computer Science Department New Delhi India

ISBN: (纸本)9789380544519

Mars, with its harsh and uncharted terrain, presents unique challenges for robotic exploration. Autonomous locomotion is a critical capability for robotic systems on the Martian surface, allowing them to traverse diverse landscapes, avoid obstacles, and accomplish scientific objectives efficiently. the AI-educated robot exhibits remarkable adaptability, successfully navigating through challenging terrains and environments while efficiently conserving energy. Additionally, the transfer of learned behaviours from simulation to the real-world robot validates the feasibility of this approach for future Mars missions. this research paper proposes a novel approach for teaching a robot to walk on Mars using AI and machine learning techniques. It demonstrates the effectiveness of the proposed approach in educating a robot to walk on Mars autonomously. the study focuses on the development of an autonomous walking algorithm for a robotic rover, leveraging state-of-the-art AI technologies. To achieve this, this paper employs deep reinforcement learning (DRL), which enables the robot to learn and adapt its locomotion strategies through interactions with its environment. A simulated Mars environment is constructed, emulating the unique challenges posed by the Martian landscape, including uneven terrain, loose soil, and rocks. this research presents a comparative analysis between previous findings from existing Mars exploration technologies, exemplified by missions like Curiosity and Perseverance, and a proposed mechanism for training a robot to autonomously walk on Mars using advanced AI. It represents a significant step toward enhancing the autonomy and versatility of robotic systems on Mars, contributing to the advancement of space exploration by enabling robots to explore, and investigate previously inaccessible regions of the Red Planet. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： artificial intelligence autonomous navigation deep reinforcement deep reinforcement learning machine learning planetary robotics robotic locomotion

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Novel Pythagorean Fuzzy Entropy for Selection of Vehicles' Battery using VIKOR Approach 18

Novel Pythagorean Fuzzy Entropy for Selection of Vehicles' B...

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18th INDIAcom;11th international conference on Computing for Sustainable Global development, INDIACom 2024

作者： thakur, Palvinder Gandotra, Neeraj Saini, Namita Shoolini University Yogananda School of AI Computer and Data Sciences Solan India

ISBN: (纸本)9789380544519

Over the past few decades, the widespread adoption of vehicle batteries (VBs) and allied technologies has garnered significant attention. the decision-making (DM) process for selecting efficient VBs is inherently challenging. this study addresses this challenge by introducing a new methodology entropy measure of Pythagorean fuzzy sets (PFSs) in conjunction with the Vlekriterijumsko Kompromisno Rangiranje (VIKOR) method to assess the efficiency of VBs. While exploring PFSs, previous studies have given limited attention to the entropy measures of PFSs. therefore, this paper contributes by introducing novel entropy measure for PFSs. the extended method is employed to address Multi-criteria decision-making (MCDM) challenges involving PFSs, specifically when criteria weights are entirely unidentified. To enhance decision-making, decision-making experts devise new approaches based on extended procedures, including Pythagorean fuzzy (PF) entropy, to capture substantial degrees of decision-expert and criteria. the PF weighted averaging operator is utilized to integrate unique choice information into a cohesive group decision matrix. the aimed approach is illustrated through a case study involving the selection of VBs, where the assessment of batteries alternatives against each criterion is extracted using Pythagorean fuzzy numbers (PFN). the results demonstrate the efficacy of the PFVIKOR method in effectively selecting vehicles' batteries. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Multi-criteria decision-making Pythagorean fuzzy numbers Pythagorean fuzzy sets Vehicles's batteries

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A Convolutional Neural Network Approach for Diabetic Retinopathy Classification 11

A Convolutional Neural Network Approach for Diabetic Retinop...

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11th IEEE international conference on Communication Systems and Network technologies, CSNT 2022

作者： Jiwani, Nasmin Gupta, Ketan Afreen, Neda University of the Cumberlands United States Jamia Millia Islamia Department of Computer Engineering New Delhi India

ISBN: (纸本)9781665480383

Diabetic Retinopathy (DR) is a kind of problem which affects diabetic patients, particularly those at their age of working, and can result in vision impairment and possibly irreversible blindness. For diagnosis and to prevent blindness or degeneration, early detection is critical. When ophthalmologists execute the diagnosis step of DR manually, it takes more time, effort, and money, and there are more possibility of misdiagnosis. the scientific community is focusing on developing a computer-aided recognition system for early identification and grading of DR severity. Ongoing AI research has highlighted the growth of the deep learning technique, which is better technique for doing medical image analysis and classification. © 2022 IEEE.

关键词： Convolutional neural networks

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