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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 1140 条记录，以下是1041-1050 订阅

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Application Teaching Case of Stack-Differential Equation Solution

Application Teaching Case of Stack-Differential Equation Sol...

引用

2017 7th ESE international conference on Management science, Education science and Human Development (ESE-MEH 2017)

作者： Xiaochao Sun Bin Yang Library Zaozhuang University School of Information Science and Engineering Zaozhuang University

Expression evaluation is very important application of stack. In the tradition teaching process,we find that students have no interest in learning and achieving expression evaluation algorithm. this problem is faced in the learning process of solving differential equations in advanced mathematics. Based on analysis,we propose to combine two knowledge points. Expression evaluation is applied to solve differential equations. By our teaching method,the students could achieve expression evaluation,solve differential equations by programming and improve the students' interest.

关键词： Stack Teaching method Differential equation

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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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Implementing Generative AI and Large Language Models in Education

Implementing Generative AI and Large Language Models in Educ...

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Innovative Approaches in Smart Technologies (ISAS), international Symposium on

作者： Neil Anderson Aidan McGowan Leo Galway Philip Hanna Matthew Collins David Cutting School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast United Kingdom

the recent advancements in Generative AI have been highlighted by the emergence of Large Language Models (LLMs) like ChatGPT. We track this evolution from the initial recurrent neural networks to the development of architectures like Transformers and Generative Pre-trained Transformers (GPT). ChatGPT, with its impressive ability to comprehend, process, and produce natural language, has piqued the interest of educators, students, and institutions within the education sector through its creation of high-quality textual *** marks the beginning of a new era in educational possibilities: we emphasize the beneficial effects of ChatGPT in learning environments, noting its utility in programming assistance, its clarity in concept explanation, and its role in enhancing automated learning processes. We also recognize potential drawbacks, including the risks of over-reliance, plagiarism, and the inherent constraints of these models in tackling mathematical and linguistic problem-solving *** exploring the Paradox of Automation, we examine the implications of an over-reliance on AI in education. We seek to understand the importance of preserving critical thinking skills and ensuring that technology serves as a tool for augmenting human capabilities rather than supplanting them. Our analysis acknowledges that, while AI, including ChatGPT, can assist in content generation and problem-solving, it is essential for students to cultivate their abilities in analytical thinking, content verification, and error correction.

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Application of the TLM-FLM method with Optimized Relaxation in electromagnetic field analysis

Application of the TLM-FLM method with Optimized Relaxation ...

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Computer Information science and Application Technology (CISAT), international conference on

作者： Jin Fang Juan Huang Meng Fu School of Mechanical Electrical Engineering Wuhan Donghu University Wuhan China Hebei Yixian Pumped Storage Company Limited Baoding China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

In order to improve the efficiency of the transmission line model finite element method (TLM-FEM), this paper optimizes the solution process of the incident stage and the reflection stage of the method. the optimized relaxation method is used to accelerate solution of the nonlinear process voltage, the calculation of the element coefficient matrix and the decomposition of the global matrix are implemented on the GPU in parallel to further improve the computational efficiency. the optimized transmission line finite element method is applied to the calculation of electromagnetic field of single-phase transformer. the accuracy of the algorithm is verified by comparing the results of self-programming analysis with the results of ANSYS. the calculation time of the same model with different grid numbers is compared, which proves that the proposed method can be applied to calculate the electromagnetic field of large-scale.

关键词： Transmission line matrix methods Power transmission lines Accuracy Computational modeling Voltage Relaxation methods Finite element analysis Electromagnetic fields Matrix decomposition Electromagnetics

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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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Support of Block Chain Technology by Distributed Database

Support of Block Chain Technology by Distributed Database

引用

2017 7th ICEA international conference on Information science, Library science and Social sciences (ILS 2017)

作者： Xudong Ling Ningxia Radio & Televion University School of Software

this paper presents the research on the support of block chain technology by distributed database. Block chain technology is the underlying technology framework of universality, which can bring profound changes in the fields of finance, economy, science and technology and even politics. According to the current development of block chain technology, block chain technology will experience programming the digital encryption system as the main feature of the block chain 1.0 mode, the programmable financial system as the main feature of the block chain 2.0 model and the programmable society as the main feature of the block chain 3.0 model. In this paper, we will elaborate the basic model, basic principle and key technology of block chain technology, and some innovative modes of block chain outside the bit coin system, which are used in the most other block chains that are similar to Bitcoin, and only in some specific aspects of the use of bitmember models more or less variants.

关键词： Block chain Distributed database General system

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Optimizing Age of Information in Random Access Networks With Correlated Sources

Optimizing Age of Information in Random Access Networks With...

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IEEE international conference on Information Communication and Signal Processing (ICICSP)

作者： Long Liang Siyuan Zhou Bin Tang Guoping Tan College of Information Science and Engineering Hohai University Nanjing China College of Computer Science and Software Engineering Hohai University Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Random access is a wireless network access technique that can meet the transmission requirements of a massive number of Internet of things terminals under limited resource constraints. To address the needs of delay-sensitive applications, it is essential to study random access strategies from the perspective of information timeliness. Existing research often assumes that the information transmitted by terminals is independent of each other, neglecting the correlation between information in the design process of random access strategies. However, in scenarios such as video surveillance and sensor monitoring, adjacent terminal transmissions exhibit spatial correlation. To overcome this limitation, this paper proposes a random access strategy based on information timeliness and information correlation. Specifically, we establish information correlation between information sources and analyze the coupling variation of Age of Information (AoI) in multipoint transmission scenarios, deriving an expression for the average network AoI. Next, by jointly optimizing the random access probabilities of various terminals, we minimize the average network AoI. To address the non-convex and nonlinear optimization problem, we design an optimization algorithm based on Sequential Quadratic programming and propose an approach to obtain initial values for improved algorithm stability. Simulation results demonstrate that the proposed method significantly reduces the average network AoI compared to random strategies that do not consider correlation.

关键词： Correlation Wireless networks Simulation Signal processing algorithms Signal processing Reliability theory Information age Video surveillance Stability analysis Quadratic programming

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Segmentation of Small Animal Computed Tomography Images Using Original CT Values and Converted Grayscale Values

Segmentation of Small Animal Computed Tomography Images Usin...

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7th IFIP WG 5.14 international conference,CCTA 2013

作者： Guoqiang Ma Naixiang Li Xiaojuan Wang Dept. of Computer Science & Information Engineering Tianjin Agriculture University Library Tianjin Agriculture University

ISBN: (纸本)9783642543432

Medical image segmentation is the foundation of normal and diseased tissue 3D visualization,operation simulation and visual *** this paper,we comprehensively use two values that represent the same object(body tissue),to segment by the same algorithm *** original CT images are downloaded from the web source,the dog rib tumor CT scan image by GE medical systems,all the experiment of dataset of 312 thoracic CT *** core of the segmentation is k-means clustering *** segmentation process consisted of two phases:(1) convert CT value to JPG gray value or not use the original CT value as the data sets for clustering;(2)segmentation bone tissue using the new k-means clustering algorithm program which is implemented with MATLAB 2012 a programming language and for two-dimensional data matrix *** experiment produced strikingly different *** results may be indicating that not only the segmentation algorithm of CT image is important,but also the data for segmentation is important too.

关键词： Image segmentation Computed tomography k-means clustering

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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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Query rewriting under ontology contraction 6th

Query rewriting under ontology contraction

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6th international conference on Web Reasoning and Rule Systems, RR 2012

作者： Tsalapati, Eleni Stoilos, Giorgos Stamou, Giorgos Koletsos, George School of Electrical and Computer Engineering National Technical University of Athens Zographou Campus Athens15780 Greece

ISBN: (纸本)9783642332029

Conjunctive query (CQ) answering is a key reasoning service for ontology-based data access. One of the most prominent approaches to conjunctive query answering is query rewriting where a wide variety of systems has been proposed the last years. All of them accept as input a fixed CQ q and ontology O and produce a rewriting for q,O. However, in many real world applications ontologies are very often dynamic—that is, new axioms can be added or existing ones removed frequently. In this paper we study the problem of computing a rewriting for a CQ over an ontology that has been contracted (i.e., some of its axioms have been removed) given a rewriting for the input CQ and ontology. Our goal is to compute a rewriting directly from the input rewriting and avoid computing one from scratch. We study the problem theoretically and provide sufficient conditions under which this process is possible. Moreover, we present a practical algorithm which we implemented and evaluated against other state-of-the-art systems obtaining encouraging results. Finally, axiom removal can also be relevant to ontology design. For each test ontology we study how much the removal of an axiom affects the size of the rewriting and the performance of systems. If the removal of a single axiom causes a significant decrease either in the size or in the computation time then this part of the ontology can be re-modelled. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Ontology

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