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Application of Recursive Query on Structured Query Language Server

Journal of Donghua University(English Edition) 2023年第1期40卷 68-73页

作者：荀雪莲 ABHIJIT Sen 姚志强 Library North China Institute of Aerospace EngineeringLangfang 065000China Department of Computer Science&Information System Kwantlen Polytechnic UniversitySurreyCanada School of Computer Science and Engineering North China Institute of Aerospace EngineeringLangfang 065000China

The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done *** query language(SQL)is a database language and is used to manipulate *** Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its *** table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive *** data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive *** recursive query is illustrated and implemented on some simple hierarchical *** addition,one business case study is brought forward and the solution using recursive query based on CTE is *** the same time,stored procedures are programmed to do the recursion in *** results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax.

关键词： structured query language(SQL)server common table expression(CTE) recursive query stored procedure hierarchical data

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Taxonomy of Multi-Agent systems Attacks and their Defense Tactics in Certifying Security of Cyber Physical systems

Taxonomy of Multi-Agent Systems Attacks and their Defense Ta...

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2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023

作者： Jain, Garima Solomon Jebaraj, N.R. Noida Institute of Engineering and Technology Department of Computer Science & Business System Uttar Pradesh Greater Noida India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350344387

The utilization of multi-agent systems has been increasingly prevalent across various sectors, owing to their notable efficacy in execution. However, a multitude of hazards exist that possess the capability to undermine the integrity of the agent and pose a threat to the overall security of the system. Therefore, it is crucial to carefully evaluate and address security vulnerabilities during the process of creating Multi-Agent systems (MAS). This survey assesses different models that aim to guarantee the security of Multi-Agent systems (MAS). These models were developed based on principles related to the agents' functionality and communication. This study offers a comprehensive examination and categorization of the prevailing threats targeting Multi-Agent systems (MASs). Following this, we conduct a comprehensive analysis and assessment of diverse security strategies described in scholarly sources, classifying them into prevention, detection, and resiliency approaches based on their established credibility and reliability. In conclusion, we offer a suggestion for the optimal security approach to address particular types of threats, considering the most recent breakthroughs in the field of study. © 2023 IEEE.

关键词： Attacks Cyber Physical systems Multi Agent systems Resiliency Security

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Character Recognition Techniques using Machine Learning: A Comprehensive Study 1

Character Recognition Techniques using Machine Learning: A C...

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1st IEEE International Conference on Applied Intelligence and Sustainable Computing, ICAISC 2023

作者： Kumar, Tarun Khosla, Cherry Vashistha, Kartikey Lovely Professional University Computer Science and Engineering Phagwara India Power System Engineer Independent Researcher India

ISBN: (纸本)9798350323795

Optical Character Recognition (OCR) technology is essential in converting printed or handwritten documents into machine-readable text. This paper provides an overview of machine learning based OCR technology, including its history, principles, and applications. The paper discusses the challenges and limitations of machine learning based OCR and presents various OCR models based on different feature extraction and classification methods. Specifically, it covers feature extraction methods such as Euclidean distance, HOG, Fourier descriptor, and directional chain code, which are used to improve the accuracy of classification models such as CNN, KNN, ANN, and SVM. The paper also discusses recent advancements in OCR for different languages and how OCR can be integrated with machine learning and AI to understand ancient scripts and convert them to modern languages. The paper concludes with a discussion on the future of multi-lingual OCR and integration with AI and machine learning models, which have the potential to revolutionize the field of OCR. In summary, this paper provides a comprehensive overview of OCR technology, its advancements in various languages and potential for future development. © 2023 IEEE.

关键词： Support vector machines

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PAIR: Protein-aptamer interaction prediction based on language models and contrastive learning framework

PAIR: Protein-aptamer interaction prediction based on langua...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Jun Yan, Zhiqiang Zeng, Hao Zhu, Zexuan Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (纸本)9798350386226

Aptamers are single-stranded DNA or RNA oligonucleotides that selectively bind to specific targets, making them valuable for drug design and diagnostic applications. Identifying the interactions between aptamers and target proteins is crucial for these applications. The systematic evolution of ligands by exponential enrichment process, traditionally used for this purpose, is challenging and time-consuming. The resulting aptamers often suffer from limitations in stability and diversity. Computational approaches have shown promise in aiding the discovery of high-performance aptamers, but existing methods are usually constrained by insufficient training data and limited generalizability. Recently, advancements in pre-training large language models have offered a new avenue to mitigate the dependency on large datasets. In this study, we propose a novel method to predict aptamer-protein interactions using large language models within a contrastive learning framework. Experimental results demonstrate that our method exhibits superior generalization and outperforms existing approaches. This method holds promise as a powerful tool for predicting aptamer-protein interactions. © 2024 IEEE.

关键词： Contrastive Learning

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An optimized Parkinson’s disorder identification through evolutionary fast learning network

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International Journal of Intelligent Computing and Cybernetics 2022年第3期15卷 383-400页

作者： Bouslah Ayoub Taleb Nora LRI Laboratory Computer Science DepartmentUniversity of BadjiMokhtar AnnabaAnnabaAlgeria Complex System Engineering Laboratory Computer Science DepartmentUniversity of Badji Mokhtar AnnabaAnnabaAlgeria

Purpose-Parkinson’s disease(PD)is a well-known complex neurodegenerative ***,its identification is based on motor disorders,while the computer estimation of its main symptoms with computational machine learning(ML)has a high exposure which is supported by researches ***,ML approaches required first to refine their parameters and then to work with the best model *** process often requires an expert user to oversee the performance of the ***,an attention is required towards new approaches for better forecasting ***/methodology/approach-To provide an available identification model for Parkinson disease as an auxiliary function for clinicians,the authors suggest a new evolutionary classification *** core of the prediction model is a fast learning network(FLN)optimized by a genetic algorithm(GA).To get a better subset of features and parameters,a new coding architecture is introduced to improve GA for obtaining an optimal FLN ***-The proposed model is intensively evaluated through a series of experiments based on Speech and HandPD benchmark *** very popular wrappers induction models such as support vector machine(SVM),K-nearest neighbors(KNN)have been tested in the same *** results support that the proposed model can achieve the best performances in terms of accuracy and ***/value-A novel efficient PD detectionmodel is proposed,which is called *** A-W-FLN utilizes FLN as the base classifier;in order to take its higher generalization ability,and identification capability is alsoembedded to discover themost suitable featuremodel in the detection ***,the proposedmethod automatically optimizes the FLN’s architecture to a smaller number of hidden nodes and solid connecting *** helps the network to train on complex PD datasets with non-linear features and yields superior result.

关键词： Parkinson’s disease(PD) Fast learning network(FLN) Genetic algorithm(GA) Speech and handwriting patterns PD identification system

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Images2Poem in different contexts with Dual-CharRNN

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CAAI Transactions on Intelligence Technology 2022年第4期7卷 685-694页

作者： Jie Yan Yuxiang Xie Xidao Luan Department of System Engineering National University of DefenseChangshaHunanChina Department of Mathematics and Computer Science Changsha UniversityChangshaHunanChina

Image to caption has attracted extensive research attention ***,image to poetry,especially Chinese classical poetry,is much more *** works mainly focus on generating coherent poetry without taking the contexts of poetry into *** this paper,we propose an Images2Poem with the Dual-CharRNN model which exploits images to generate Chinese classical poems in different ***,we first extract a few keywords representing elements from the given image based on multi-label image ***,these keywords are expanded to related ones with the planning-based ***,we employ Dual-CharRNN to generate Chinese classical poetry in different contexts.A comprehensive evaluation of human judgements demonstrates that our model achieves promising performance and is effective in enhancing poetry's semantic consistency,readability,and *** present an Images2Poem with the Dual-CharRNN model exploiting images to generate Chinese classical poems in different contexts,which effectively improves the semantic consistency,readability and aesthetics of the generated poetry.

关键词： computer vision deep learning image captioning poetry generation

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Pilot Study on Aerial Wireless Superdirectional Sound Sources Utilizing Parametric Array Loudspeakers via Local 5G Networks

Pilot Study on Aerial Wireless Superdirectional Sound Source...

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2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023

作者： Iihoshi, Yohei Okubo, Kan Department of Electrical Engineering and Computer Science Faculty of System Design Tokyo Metropolitan University Hino Tokyo Japan

ISBN: (纸本)9798350341140

This study presents a pilot study on the potential future use of aerial sound sources utilizing parametric array loudspeakers (PALs) in drones via fifth-generation (5G) networks. Integrating superdirectional loudspeakers with high-speed wireless communication is essential for projecting sound from the air to specific locations using drones. Herein, as an experimental approach, we have evaluated the performance of wireless communication, specifically local 5G, for realizing aerial sound sources. The results demonstrated the high performance of the local 5G connection intended for PALs in the air. © 2023 IEEE.

关键词： 5G networks aerial sound source millimeter wave band parametric array loudspeaker wireless communication

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BAV-DSS: Blockchain Assisted Verifiable Data Sharing Scheme with Fast Encryption and Outsourced Decryption for IoT 24th

BAV-DSS: Blockchain Assisted Verifiable Data Sharing Scheme ...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Huang, Yao Yu, Zhongyuan Wang, Guijuan Chai, Baobao Zhang, Hongliang Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan250353 China School of Information Science and Engineering Lanzhou University Lanzhou730000 China School of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9789819615414

Many sophisticated cloud platforms are available to provide services such as storage and computation for Internet of Things (IoT) applications. However, with the concerns about the semi-trusted nature of cloud platforms, data security and privacy have been gaining broad attention. In this paper, we propose a blockchain-assisted verifiable data sharing scheme (BAV-DSS) for IoT. The BAV-DSS features fine-grained access control, fast encryption, and outsourced decryption with verifiability. Specifically, with the application of ciphertext-policy attribute-based encryption (CP-ABE), flexible access control is enabled. Blockchain is employed to store public keys, generate account addresses, and perform data verification. Furthermore, the selective replayable chosen ciphertext attacks (sRCCA) security of BAV-DSS is proved, and the simulation results indicate that BAV-DSS obtains high efficiency and practicality compared to other schemes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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Light Shift Detection Using a Multiple Photodetection Method Suitable for a Chip-Scale Atomic Clock

Light Shift Detection Using a Multiple Photodetection Method...

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2023 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium, EFTF/IFCS 2023

作者： Fukuoka, Masahiro Goka, Shigeyoshi Tokyo Metropolitan University Graduate School of System Design Department of Electrical Engineering and Computer Science Tokyo Japan

ISBN: (纸本)9798350311426

In this study, we demonstrated light shift detection in a running atomic clock using the multi-photodetection method. This method enables the observation of atomic resonances with different intensities using the intensity distribution of the laser beam. As it requires only two photodiodes to detect light shifts, it is easily applicable to miniature vapor-cell-based atomic clocks such as chip-scale atomic clocks and miniature atomic clocks. © 2023 IEEE.

关键词： chip-scale atomic clock coherent population trapping intensity distribution laser light shift VCSEL

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A Non-Sequential Steganography Method Using Perfect Square Quotient Differencing (NSPSQD)

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SN computer science 2025年第5期6卷 1-26页

作者： Basak, Ratan Kumar Chatterjee, Ritam Dasgupta, Kousik Dutta, Paramartha Computer Science and Engineering Institute of Engineering and Management (IEM) University of Engineering and Management Kolkata Kolkata India Computer Science and Engineering Kalyani Government Engineering College Kalyani India Computer and System Science Visva-Bharati University Bolpur India

In today’s digital world, keeping data safe is a top priority. Two common methods used to protect data are steganography and cryptography. Steganography hides secret data within everyday files (like images, GIFs or videos), while cryptography scrambles the data into an unreadable format. This paper introduces a new way to hide data using a technique called Perfect Square Quotient Differencing. Instead of embedding data in a straight sequence, the method hides information in two steps within the components of an image pixel (called the quotient and remainder). In the first step, a perfect square quantization technique is applied to the quotient part. In the second step, the Two Least Significant Bit (2LSB) method is used on the remainder part. A new range-table is also introduced to help determine how much data can be hidden in the first step. This two-step approach allows a large amount of data to be hidden (about 3 bits per pixel on average). The method was tested on many animated color images, and its performance was measured using tools like Peak-Signal-to-Noise-Ratio (PSNR), Mean Square Error (MSE), Universal Image Quality Index (UIQI), and Payload Curve. The results show that this method works better than several modern steganography techniques. Additionally, tests were conducted to ensure the method is secure against potential attacks. This new algorithm could be particularly useful for protecting digital documents stored in cloud-based platforms, offering a robust and efficient way to keep data safe.

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