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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1136 条记录，以下是551-560 订阅

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An Effective Method for Skin Cancer Detection using Convolutional Kernel Extreme Learning Machine

An Effective Method for Skin Cancer Detection using Convolut...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Anuradha Sarkar N Badrinath Poonam Kapse Diksha Madhav Bhalerao Kamlesh Singh K.V.Daya Sagar Neville Wadia Institute of Management Studies and Research Pune Maharashtra India School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of CSE AIML Bharati Vidyapeeth (Deemed to be University) Kharghar Navi Mumbai Maharashtra India Department of Engineering and Technology Bharati Vidyapeeth (Deemed to be University) Navi Mumbai Maharashtra India Department of Computer Science and Engineering Graphie Era Hill University Dehradun Campus Dehradun Uttarakhand India Department of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation vaddeswaram Guntur Andhra Pradesh India

Skin cancer is the most common type of cancer. Every year, it has a significant effect on the lives of tens of millions of individuals. Approximately three million people are told they have it every year for the United States only. Survival rates are much lower at that point. In proportion to the severity of the condition. Yet, early skin cancer screening is a difficult and expensive process. the four main phases in skin cancer detection are preprocessing, segmentation, feature extraction, and classification. Because it improves the odds of successfully treating cancer, early detection is vital. In this study, Otsu's thresholding is utilized to distinguish the foreground from the background after the Gaussian filter has been applied during the pre-processing stage. the histogram equalization phase of the pre-processing stage uses the input from the median filter to remove noise. Compatibility of Grey-Level Signals, normalization for symmetry extraction of skin lesion characteristics are done by using GLCM matrix. Afterwards, the proposed model is trained via CKELM. When compared to other state-of-the-art models like CNN and KELM, the proposed model achieves a higher accuracy of around 98%.

关键词： Histograms Extreme learning machines Convolution Feature extraction Market research Skin Convolutional neural networks

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Low-Computational Model Predictive Control of T-Type three-Level Inverter with Fixed Switching Frequency

Low-Computational Model Predictive Control of T-Type Three-L...

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China international Electrical and Energy conference (CIEEC)

作者： Zhihao Chen Guoliang Yang Department of Electrical Engineering and Automation Yanshan University Qinhuangdao China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Conventional Model Predictive Control (C-MPC) typically suffers from an unfixed switching frequency and requires significant computational power from the controller, which restricts its widespread industrial application. To overcome this limitation, this paper proposes a low-computational control strategy for achieving a fixed switching frequency in aT-type three-level inverter. In this strategy, the 27 vectors are initially grouped together, and the candidate vector group for optimized rolling is determined by evaluating the position of the reference voltage vector in space. Subsequently, the vectors are categorized into P-type vectors and N-type vectors based on their impact on the capacitance voltage of the DC side. By comparing the magnitude of the capacitance voltage and simultaneously balancing the neutral-point voltage of the DC side, the candidate vectors are further narrowed down. Importantly, the objective function no longer needs to consider neutral-point voltage balancing, thus simplifying the computational process. Lastly, the candidate vectors are evaluated, ranked according to the objective function, and assigned action times. through simulation and experimentation, it is demonstrated that this approach enables the T -type inverter to achieve high performance while minimizing computational load.

关键词： Fluctuations Switching frequency Capacitance-voltage characteristics Linear programming Control systems Cost function Vectors

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Fuzzy Multi-Objective Optimization Considering the Uncertainty of Distributed Generation

Fuzzy Multi-Objective Optimization Considering the Uncertain...

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IEEE conference on Energy Internet and Energy System Integration (EI2)

作者： Yi An Luxin Zhan Jing Gao Qinya Qi Long Zhao State Grid Jiangxi Electric Power Co. Ltd. Electric Power Research Institute Nanchang China School of Electrical and Information Engineering Changsha University of Science and Technology Changsha China State Grid Hunan Extra High Voltage Substation Company Changsha China CYG SUNRI Co. LTD. Shenzhen China

Distributed generation makes distribution network become more complex and requirements of distribution system become higher. Due to the uncertainty of distributed new energy, applying traditional heuristic algorithms or intelligent algorithms to distribution network reconfiguration is less stable and may fall into the local optimum, which affects the rapidity and reliability of net-work programming. In this paper, the original nonlinear reconfiguration model is converted into a mixed-integer second-order cone model by second-order cone relaxation. By deriving the re-Iaxation conditions such as phase angle relaxation and second-order cone relaxation in the model power flow equation, the reconstruction model of multi-source distribution network based on second-order cone relaxation is constructed, and MATLAB/CPLEX is used to realize the fast operation. the model is simulated based on the triangular fuzzy theory with the objective function of minimizing the network loss and the main grid power purchase, the multi-objective Pareto front and objective function boundary values are obtained considering the uncertainty of distributed power supply and load. It is verified through simulation that economic reconfiguration through method of this paper can effectively can reduce the network loss, improve the distribution of the system currents, and enhance the system economy.

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Internet of things Security: A Review on Challenges, Solutions and Research Directions

Internet of Things Security: A Review on Challenges, Solutio...

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international conference on Internet of things and Applications (IoT)

作者： S. Mohammadali Zanjani Hossein Shahinzadeh Seyed Mohamad Kargar Majid Moazzami Farshad Ebrahimi Mohammadreza Hemmati Smart Microgrid Research Center Najafabad Branch Islamic Azad University Najafabad Iran Department of Electrical Engineering Najafabad Branch Islamic Azad University Najafabad Iran Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Computer Science Research Centre Royal College of Art London United Kingdom Department of Electrical and Computer Engineering University of Houston Houston TX USA Faculty of Computer Engineering Najafabad Branch Islamic Azad University Najafabad Iran

the Internet of things (IoT) is a highly diverse system of services and technologies. However, the lack of a suitable processing platform can result in inappropriate outputs when transferring the large volume of heterogeneous data generated by devices to users. Ensuring the reliability of processed data is fundamental for maintaining integrity and reliability in IoT systems. As the number of connected devices increases, so does the risk of cyber-attacks. Hackers exploit vulnerabilities through methods like denial-of-service attacks, malicious emails, viruses, and Trojans, compromising IoT devices for their advantage. Recent studies indicate that 70% of IoT devices are vulnerable to attacks. Enhancing IoT security involves methods such as data encryption, security updates, security protocols, access control, and secure networks. Educating and raising awareness among users also plays a crucial role. Addressing these aspects and employing appropriate security measures are key to improving IoT security. this article reviews IoT challenges, security improvement methods, and future directions. Attention to data encryption, security updates, security protocols, access control, and secure networks is essential for enhancing IoT security.

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Research on Game Strategy of Crossing Desert 7

Research on Game Strategy of Crossing Desert

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2020 7th international conference on Computer-Aided Design, Manufacturing, Modeling and Simulation, CDMMS 2020

作者： Ju, Tuo Cao, Jiayi Leng, Shuai Xie, Yuxin Zhuang, Junjie Faculty of Transportation Engineering Huaiyin Institute of Technology Huaian Jiangsu223001 China

this paper analyzes the players in the game of "crossing the desert", and puts forward the optimal customs clearance strategy to help the game players reach the destination within the specified time under the condition that the remaining funds are retained as much as possible. Firstly, the redundant paths are eliminated and the complete subgraph of the game map is drawn to improve the speed of computer optimization. then, the multiple rules in the game are transformed into the constraints in the planning model, such as load constraint, remaining fund constraint, resource margin constraint and so on. By solving the model based on adjacency matrix and mixed integer programming, the rationality of the optimization strategy is verified by an example. the waiting model is used to decompose the number of players and consider different space and time to maximize the revenue of a mine as much as possible, while reducing the basic consumption of latecomers in a certain area and the consumption of resources purchased in the same village. © Published under licence by IOP Publishing Ltd.

关键词： Integer programming

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Legend Pattern Calculation for Dynamic Traffic Management Using ILP

Legend Pattern Calculation for Dynamic Traffic Management Us...

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IEEE international conference on Automation science and engineering (CASE)

作者： J.J. Verbakel J. van Meurs J.M. van de Mortel-Fronczak W.J. Fokkink J.E. Rooda Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands Department of Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands

To ensure the safety of highway traffic, traffic management systems are used. In the Netherlands, a traffic management system is used consisting of roadside units, which are controlled from traffic centers. the roadside units are capable of showing legends, such as speed limits or directional instructions. Operators are monitoring the road 24/7, and during roadworks or when an incident happens, they can request a measure, e.g., a lane closure. the system then automatically determines the required legend pattern, comprising of directional arrows to lead traffic away from the closed lanes and speed limits on the remaining open lanes. this system is managed by Rijkswaterstaat, which is part of the Dutch ministry of infrastructure and water management. In this paper, integer linear programming is used to determine the legend pattern, based on operator input. the model adheres to the traffic rules used by Rijkswaterstaat. By using a model-based optimization approach, a solution is found which guarantees legend patterns follow the rules, while minimizing the impact on traffic. the model can be easily adapted to tryout different road configurations or alternative rules. Furthermore, a graphical user interface is created for validation of the generated solutions, by the operators from Rijkswaterstaat. this model is also applicable to highways that are not equipped with physical signaling equipment. therefore, it can be used to control two thirds of the Dutch highway network, where the current system is not implemented.

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Analytical study of Virtual reality in Moroccan higher education

Analytical study of Virtual reality in Moroccan higher educa...

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international conference on Information science and Technology (ICIST)

作者： Khadija Talbi Imane Zergout Ajana Souad ZinebAithaddouchane ResearchLaboratory ERFSI University Hassan II ENSEM Engineering Casablanca Morocco

the Virtual reality (VR) experience immerses users in an interactive digital environment similar to the real world. In the context of education, virtual reality can represent an active learning tool which could improve learning outcomes for students by involving their visualization and their interactivity with virtual dynamic and complex systems. Nowadays this technology become widely employed in many higher education programs all over the *** paper examines the use of VR in Moroccan higher education context. the study begins with stating the current situation of VR in education in general, and then in Moroccan higher education. the results of this state of the art are gathered with an empirical analysis of VR integration into some post-secondary institutions and schools’ pedagogy and curricula. these results helped then to conduct a SWOT analysis of virtual reality technologies in Moroccan higher education environment. A particular case study of mechanical engineering skills is *** show that Morocco has significant potential to effectively adopt this technology, contingent upon addressing the current inconveniences and constraints. through the successful navigation of these challenges, the nation has the potential to leverage the advantages of virtual reality technology, thereby transforming its educational domain. this study highlights the importance of strategic planning and investment in order to effectively harness the benefits of virtual reality in increasing educational experiences and equipping students for future endeavors.

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Deep Learning for Plant Disease Detection and Crop Yield Prediction based on NPP-WPF Analysis in Smart Agriculture

Deep Learning for Plant Disease Detection and Crop Yield Pre...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Amudha S Bindu G Sasi Rekha Sankar E Poongothai VijayaLakshmi K Velliangiri Sarveshwaran Department of Computational Intelligence School of Computing Faculty of Engineering and Technology SRM Institute of Science and TechnologyChennai Kattankulathur Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India

Despite a sharp rise in population, agriculture still provides food for all people and acts as a backbone of the country. Nowadays, no proper guidance given to farmers and they are not able to analyze the nature of soil, disease of plant and its requirements. this leads to the depletion of farming in future. Crop diseases must be identified and prevented in order to increase the productivity. To overcome this, the nature of the soil is analyzed through various parameters like Nitrogen-Potassium-Phosphorus Content in soil, Humidity, Temperature, pH value of the soil, Rainfall using sensors, plants disease using cameras in real-time environment. these parameters are obtained using various IoT Sensors, cameras and existing Data, are analyzed through ML Algorithms. the proposed system consists of two modules in crop yield prediction system using the features NPP-WPF whereas NPP stands for Nitrogen-Potassium-Phosphorus and WPF stands for Water Content-Pesticide-Fertilizer, the Farmers can be guided with the details of the crop that is suitable for the soil and about Fertilizer, Pesticide, Water requirements. the second module called as automatic disease detection system uses CNN, ResNet, VGGNet, and Mobile net models to recognize and diagnose plant diseases from their leaves at the early stage. the proposed model is implemented with the dataset of 14 different species of plants and with the categorical classes of 38 classes. the result analysis shows that the suggested model provides accuracy of 98.2% when compared to the existing state-of-the-art methodologies.

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Generalized Face Spoofing Detection Using Spatial Features

Generalized Face Spoofing Detection Using Spatial Features

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Neenu Daniel A. Anitha Computer Science and Engineering Noorul Islam centre for Higher Education Nagercoil India

Authenticating a person using biometric traits like fingerprint, iris, and face is widely adopted in security applications. Compared to other authentication procedures biometrics provides high accuracy. Face biometrics possess high precision and low intrusiveness. However, face recognition-based security systems are vulnerable to face spoofing attacks. Using printed photo or video replay intruders attempt to break the recognition system. Face spoof detection systems classify real and fake users by analyzing the features. Various spoof detection techniques have evolved based on texture and quality features. However, these methods suffer from generalization ability and variations in textures. So, in this research work, a face spoofing detection model is presented that utilizes spatial and frequency features to detect real and fake users. Feature descriptors like Histogram of Gradient (HOG) and Gray-Level Co-occurrence Matrix (GLCM) are used to obtain the essential features and extracted features are processed through a random forest classifier module. Extensive experiments on benchmark datasets namely the Reply-attack database and MSU-Mobile face spoof database demonstrate the better detection performance of the proposed spoof detection model compared to state of art of techniques. Cross-database evaluation of the proposed approach possesses minimum error indicates the generalization ability of the proposed face spoof detection model.

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Smart Voice Navigation and Object Perception for Individuals with Visual Impairments

Smart Voice Navigation and Object Perception for Individuals...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Sheetalrani Rukmaji Kawale Shruti Mallikarjun Dankan Gowda V K D V Prasad Anusha M N Anil Kumar N Department of Computer Science Karnataka State Akkamahadevi Women University Vijayapura Karnataka India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka India Symbiosis Institute of Business Management Hyderabad Symbiosis International (Deemed University) Pune India Department of Electronics & Communication Engineering BGS Institute of Technology/ACU B G Nagara Mandya Karnataka India Department of Electronics and Communications Engineering School of Engineering Mohan Babu University Tirupati India

Technological advancements have brought about substantial changes to the accessibility alternatives that cater to those with diverse abilities. the integration of artificial intelligence (AI) into assistive technology has presented unprecedented opportunities for enhancing the autonomy and quality of life of those with disabilities. the focus of rigorous investigation is on "Smart Blind Sticks," which are novel equipment designed to enhance the mobility and safety of those with visual impairments. this article presents a comprehensive account of the conceptualization, design, and implementation of a technologically advanced blind stick. the primary objective of this innovative device is to detect and promptly respond to impediments in the immediate environment, hence facilitating navigation for those with vision impairments. the proposed system utilizes advanced sensor technologies and advanced data processing techniques to provide precise obstacle detection. Moreover, it employs state-of-the-art navigation systems to provide instantaneous guidance, guaranteeing seamless and secure transportation at all instances. the distinguishing characteristics of the smart blind stick set it apart from conventional white canes, hence affording its users more mobility. Experimental evidence showcases the practical use of this approach, therefore emphasizing its capacity to significantly enhance accessibility and promote autonomy among individuals with visual impairments.

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