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检索条件"任意字段=23rd International Conference on Computer Systems and Technologies, CompSysTech 2022"

共 802 条记录，以下是321-330 订阅

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Chain-of-Factors: A Zero-Shot Prompting Methodology Enabling Factor-Centric Reasoning in Large Language Models 23

Chain-of-Factors: A Zero-Shot Prompting Methodology Enabling...

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23rd IEEE international conference on Machine Learning and Applications, ICMLA 2024

作者： Hussain, Musarrat Ur Rehman, Ubaid Nguyen, Tri D.T. Lee, Sungyoung Kim, Seong Tae Bae, Sung-Ho Kim, Jung Uk UiT The Arctic University of Norway Department of Computer Science Tromso Norway Kyung Hee University Dept. of Computer Science & Engineering Yongin Korea Republic of Kyung Hee University Department of Computer Science and Engineering Yongin Korea Republic of

ISBN: (纸本)9798350374889

Large language models (LLMs) have significantly improved numerous natural language processing tasks. However, their performance relies heavily on the provided instructions or prompts. Recently, several prompting methodologies have been developed to enhance the reasoning abilities of LLMs. Notably, the Chain-of-Thought (CoT) approach provides examples that help break down tasks into sub-steps, resulting in more accurate solutions. However, the process of generating detailed examples may not be user-friendly, as end users prefer providing task descriptions rather than a set of examples. In this study, we introduce Chain-of-Factors (CoF), an innovative zero-shot prompting methodology that incorporates task-specific instructions as a chain of factors into the prompt, aimed at enhancing the factor-centric reasoning abilities of LLMs. Experiments on three LLMs, including ChatGPT-3.5, Gemini, and GPT-4, show performance improvements ranging from 0.01% to 40.2% in accuracy on various symbolic reasoning and logical reasoning tasks compared with zero-shot and few-shot CoT. In summary, CoF enhances LLMs' reasoning abilities by including task-specific steps and instructions, while also decreasing the necessity for fine-tuning specific to each task. © 2024 IEEE.

关键词： Natural language processing systems

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23rd international conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2022

23rd International Conference on Verification, Model Checkin...

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23rd international conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2022

ISBN: (纸本)9783030945824

The proceedings contain 24 papers. The special focus in this conference is on Verification, Model Checking, and Abstract Interpretation. The topics include: Lightweight Shape Analysis Based on Physical Types;fast Three-Valued Abstract Bit-Vector Arithmetic;satisfiability and Synthesis Modulo Oracles;bisimulations for Neural Network Reduction;NP Satisfiability for Arrays as Powers;STAMINA 2.0: Improving Scalability of Infinite-State Stochastic Model Checking;generalized Arrays for Stainless Frames;Making PROGRESS in Property Directed Reachability;scaling Up Livelock Verification for Network-on-Chip Routing Algorithms;relational String Abstract Domains;stateful Dynamic Partial Order Reduction for Model Checking Event-Driven Applications that Do Not Terminate;Verifying Solidity Smart Contracts via Communication Abstraction in SmartACE;out of Control: Reducing Probabilistic Models by Control-State Elimination;mixed Semantics Guided Layered Bounded Reachability Analysis of Compositional Linear Hybrid Automata;bit-Precise Reasoning via Int-Blasting;fanoos: Multi-resolution, Multi-strength, Interactive Explanations for Learned systems;loop Verification with Invariants and Contracts;EPMC Gets Knowledge in Multi-agent systems;high Assurance Software for Financial Regulation and Business Platforms;gradient-Descent for Randomized Controllers Under Partial Observability;Automata-Driven Partial Order Reduction and Guided Search for LTL Model Checking;verifying Pufferfish Privacy in Hidden Markov Models.

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Visual Novels as a Means of Business Communication Skills Development for computer Science Students 23rd

Visual Novels as a Means of Business Communication Skills De...

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23rd international conference on Professional Culture of the Specialist of the Future, PCSF 2023

作者： Borschenko, Galina Rubtsova, Anna Zhelezniakova, Olga Peter the Great St. Petersburg Polytechnic University St. Petersburg195251 Russia Minsk State Linguistic University Minsk22003427 Belarus

ISBN: (纸本)9783031480157

The use of information and communication technologies, which has already become an integral part of the educational process, accelerated its pace significantly during the COVID-19 pandemic and formed certain trends that will undoubtedly continue influencing further transformations. Analyzing the COVID-19 pandemic and post-pandemic studies, we highlight some changes in the following aspects: the choice of equipment for learning activities and preferable teaching methods. This new social demand is making such learning formats as gamification and educational games more and more popular. Visual novels (VNs) could become an educational resource. The research task is to test the effectiveness of a visual novel as a means of teaching business communication to computer science students considering current trends and limitations since observation shows that business communication is left out of consideration in technical specialists training programs. Corresponding closely to modern trends in education, VNs not only implement the ideas of alternative teaching methods (gamification) productively, but also provide educational organizations with the opportunity to intensify the process of learning and optimize technical resources involved in the educational process. Another confirmed important factor is the effectiveness of VNs and gamification in general in terms of keeping up students’ learning motivation and interest while studying a minor subject. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Visual languages

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Critical Analysis and Evaluation of Current Digital Healthcare Solutions 23

Critical Analysis and Evaluation of Current Digital Healthca...

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23rd international conference on Control systems and computer Science technologies, CSCS 2021

作者： Ianculescu, Marilena Alexandru, Adriana Pop, Florin Systems and Applications for Society Department National Institute for RandD in Informatics Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Department of Computer Science and Engineering University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665439398

Digitalization of health, healthcare and healthcare delivery unequivocal have positive consequences contributing to health system goals, but they also might have some negative ones which have to be avoided or mitigated. The scope of this paper is to introduce the necessity of the assessment of Health Technology Assessment (HTA) and to identify the most appropriate and important criteria needed for the evaluation and comparison of functional digital healthcare solutions. It aims to outline consistent criteria against which digital health technologies and services can be evaluated during the prototyping phase, but also during long-term operation. © 2021 IEEE.

关键词： Health care

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Condition Monitoring of Manufacturing Production Lines Using Fractal Analysis of Energy Consumption Datasets 23

Condition Monitoring of Manufacturing Production Lines Using...

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23rd international conference on Control systems and computer Science technologies, CSCS 2021

作者： Mihai, Viorel Dragana, Cristian Popescu, Dan Ichim, Loretta University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9781665439398

Many plants use a combination of maintenance strategies across their production facilities. Under condition monitoring strategy, a continuous analyze of a combination of machine health parameters is performed, aiming the observation of changing trends. Online condition monitoring systems generally include measure of vibration, thermography, ultrasound, oil analysis or energy parameters. In the case of energy analysis, an abnormal behaviour of the manufacturing units generates deviations from the reference models by altering the energy consumption footprint. In this paper an approach based on fractal analysis of energy consumption datasets is evaluated on a real testbed assembly line. By computing the Hurst exponent for each data subset which corresponds to different assembly operations, for several manufacturing cycles, it was found that it is possible to perform an energy consumption pattern matching for each operation. © 2021 IEEE.

关键词： Energy utilization

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AI-Enabled Personalized Interview Coach in Rural India 23rd

AI-Enabled Personalized Interview Coach in Rural India

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23rd international conference on Artificial Intelligence in Education (AIED)

作者： Nayak, Shriniwas Kumar, Satish Agarwal, Dolly Parikh, Paras UBS Mumbai Maharashtra India Pratham Educ Fdn Mumbai Maharashtra India

ISBN: (纸本)9783031116476;9783031116469

Soft skills are one of the highly-valued skills integral in one's personal as well as professional life. Recent advancements in technology and the penetration of the internet enable new ways to build systems to identify and help learners who need assistance in improving their soft skills. This paper presents the design, development and evaluation of a prototype intelligent system for training youth in rural areas. The system assesses a personal interview of a learner using their audio/video captured from a mobile phone or web camera. Verbal and non-verbal cues are evaluated using speech processing, computer vision and natural language processing and a detailed feedback is generated using Natural language generation. The real-world data used for training the machine learning models for the system were collected from rural areas in India and were annotated by reliable experts. We validated the performance of the system on an out-of-sample data-set which included 100 interviews collected by piloting the application.

关键词： computer vision NLP AI in education

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END-TO-END FULL-PAGE OPTICAL MUSIC RECOGNITION FOR MENSURAL NOTATION 23

END-TO-END FULL-PAGE OPTICAL MUSIC RECOGNITION FOR MENSURAL ...

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23rd international Society for Music Information Retrieval conference, ISMIR 2022

作者： Ríos-Vila, Antonio Iñesta, José M. Calvo-Zaragoza, Jorge U.I for Computer Research University of Alicante Spain

ISBN: (纸本)9781732729926

Optical Music Recognition (OMR) systems typically consider workflows that include several steps, such as staff detection, symbol recognition, and semantic reconstruction. However, fine-tuning these systems is costly due to the specific data labeling process that has to be performed to train models for each of these steps. In this paper, we present the first segmentation-free full-page OMR system that receives a page image and directly outputs the transcription in a single step. This model requires only the annotations of full score pages, which greatly alleviates the task of manual labeling. The model has been tested with early music written in mensural notation, for which the presented approach is especially beneficial. Results show that this methodology provides a solution with promising results and establishes a new line of research for holistic transcription of music score pages. © A. Ríos-Vila, J. M. Iñesta, and J. Calvo-Zaragoza.

关键词： Semantics

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Broad Learning Inference Based on Fully Homomorphic Encryption 23rd

Broad Learning Inference Based on Fully Homomorphic Encrypt...

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23rd international conference on Parallel and Distributed Computing, Applications, and technologies, PDCAT 2022

作者： Deng, Xinru Sang, Yingpeng Li, Zhaojue School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9783031299261

Distributed big data computing environments such as machine learning are widely deployed and applied on the cloud. However, since cloud servers can easily access user data, it leads to serious data leakage problems. As a potential technology, Fully Homomorphic Encryption (FHE) is often used in the field of privacy-preserving machine learning. However, in order to reduce the multiplicative depth of FHE, the neural network prunes the number of network layers, resulting in low inference accuracy. A learning model named Broad Learning System (BLS) has the characteristics of shallow model depth and low complexity. Based on this mode, we propose a privacy-preserving inference algorithm with low multiplicative depth, namely broad learning inference based on fully homomorphic encryption. We also extend the algorithm to the BLS model with incremental learning. We implement the privacy-preserving BLS for the first time using TENSEAL’s CKKS scheme, and also verify the effectiveness of BLS inference with incremental learning. Experimental evaluations demonstrate the inference accuracy of 0.928 and 0.672 for datasets of MNIST and NORB, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Overcoming Limitations of Statistical Methods with Artificial Neural Networks 23

Overcoming Limitations of Statistical Methods with Artificia...

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23rd international Arab conference on Information Technology, ACIT 2022

作者： Grebovic, Marko Filipovic, Luka Katnic, Ivana Vukotic, Milica Popovic, Tomo University of Donja Gorica Faculty for Information Systems and Technologies Podgorica Montenegro Finances and Business University of Donja Gorica Faculty of International Economics Podgorica Montenegro

ISBN: (纸本)9798350320244

Traditional statistical models as tools for summarizing patterns and regularities in observed data can be used for making predictions. However, statistical prediction models contain small number of important predictors, which means limited informative capability. Also, predictive statistical models that provide some type of pseudo-correct regular statistical patterns, are used without previous understanding of the used data causality. Machine Learning (ML) algorithms as area in Artificial Intelligence (AI) provide the ability to interpret and understand data in more sophisticated way. Artificial Neural Networks as kind of ML methods use non-linear algorithms, considering links and associations between parameters, while statistical use one-step-Ahead linear processes to improve only short-Term prediction's accuracy by minimizing cost function. Disregarding that designing an optimal artificial neural network is very complex process, they are considered as potential solution for overcoming main flaws of statistical prediction models. However, they will not automatically improve predictions accuracy, so several artificial neural networks and traditional statistical methods are evaluated and analyzed through accuracy measures for prediction purposes in various fields of applications. Based on gained results, couple of techniques for improving artificial neural networks are proposed to get better accuracy results than statistical predictive methods. © 2022 IEEE.

关键词： Machine learning

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Bluetooth Communications in Educational Robotics 23

Bluetooth Communications in Educational Robotics

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23rd international conference on Control systems and computer Science technologies, CSCS 2021

作者： Oprea, Marin Mocanu, Mariana University Politehnica of Bucharest Calarasi Romania Faculty of Automatic Control and Computer Science Computer Department University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665439398

In a world in a continuous and rapid change, it is absolutely necessary for our students to keep up with the rapid progress of new technologies: Internet of Things (IoT), Robotics, Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR) etc. The rapid evolution and diversification of these emerging technologies has recently led to their introduction into the educational offer of the school curriculum for the gymnasium. The discipline of Information and Communication Technology (ICT) has already been implemented, a discipline that involves both the formation of skills to use new technologies and the formation of computational thinking necessary for the efficient and intelligent use of these technologies. In order to teach and learn Physics from a STEM (Science, Technology, Engineering and Mathematics) educational perspective, we initiated optional school courses of IoT, Robotics and AI (approached through Machine Learning). These courses stimulate, at the level of students, computational thinking, creativity and innovation and lead, from an interdisciplinary perspective, to the development of emerging specializations such as Mathematics-Physics-Automation, Mathematics-Physics-Electronics, Mathematics-Physics-Informatics-Robotics etc. In this paper we presented a method of approaching, in the school educational space, the study of wireless communication technologies between smart devices, through an Educational Robotics project. The project consisted of creating a wireless controlled mobile robotic platform (robot car) via a Bluetooth module connected to an Arduino Uno board. © 2021 IEEE.

关键词： Students

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