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Algorithm for Selecting the Optimal Technology for Rapid Manufacturing and/or Repair of Parts

Algorithm for Selecting the Optimal Technology for Rapid Man...

引用

International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering - Synergetic Engineering (ICTM)

作者： Sikulskyi, Valeriy Maiorova, Kateryna Shypul, Olga Nikichanov, Viacheslav Tryfonov, Oleg Voronko, Iryna Kapinus, Oleksandra Natl Aerosp Univ Kharkiv Aviat Inst 17 Chkalova St UA-61070 Kharkiv Ukraine Ukrainian Amer Joint Venture KODA Bahaliia St 22 Kharkiv Ukraine

ISBN: (纸本)9783031614149;9783031614156

The subject of the study is the technology of rapid production and/or repair of parts for which there is no design documentation, in order to return them to working state as soon as possible. Such technologies are built on the basis of reverse engineering operations, with the further use of additive and extractive technologies. The work is aimed at finding the optimal technology for rapid production and/or repair of parts. To achieve the goal, schemes of technological operations have been developed according to various methods of production of parts from specified metals and the mass of the workpiece. The labor intensity of work for each technological operation of part production and the total labor intensity of work in the manufacture of a single part and a batch of parts are calculated and compared. An experimental study of the production of the part using reverse engineering technologies, additive and extractive technologies was carried out, and different methods of its production were compared according to the parameter of labor intensity. An algorithm for selecting the optimal technology for rapid manufacturing and/or repair of parts is proposed, provided that labor intensity and manufacturing time are minimized, taking into account the accuracy and volume of manufacturing.

关键词： reverse engineering 3D printing additive manufacturing technology Digital Mock-Up labor intensity

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Integrating Spatial and Temporal Contextual Information for Improved Video Visualization 4th

Integrating Spatial and Temporal Contextual Information for ...

引用

4th Congress on Intelligent systems (CIS)

作者： Singh, Pratibha Kushwaha, Alok Kumar Singh Guru Ghasidas Vishwavidyalaya Dept Comp Sci & Engn Bilaspur India

ISBN: (纸本)9789819990399;9789819990405

Video representation learning is crucial for various tasks, and self-attention has emerged as an effective technique for capturing long-range dependencies. However, existing methods often neglect the distinct contextual information conveyed by spatial and temporal correlations by computing pairwise correlations simultaneously along both dimensions. To address this limitation, we suggest a novel module that sequentially models spatial and temporal correlations. This enables the efficient integration of spatial contexts into temporal modeling. By incorporating this module into a 2D CNN, we develop a self-attention module network tailored for video visualization. We evaluate the effectiveness of our approach on two benchmark datasets: Charades STA and QVHighlight, which are relevant for moment retrieval and highlight detection tasks. Through extensive experimentation, our findings show that on both datasets, the self-attention element network exceeds current methods. Notably, our models consistently surpass shallower networks and those with fewer modalities, highlighting the superiority of our approach. In summary, our proposed self-attention module contributes to advancing video representation learning by effectively capturing spatial and temporal correlations. The notable improvements achieved in moment retrieval and highlight detection tasks validate the efficacy and versatility of our approach.

关键词： Video visualization Moment retrieval Highlights detection Self-attention network

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Review on Recent Matrix Multiplication Optimization Using Deep Learning 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Mansour, Youssef Kaissar, Antanios Ansari, Sam Univ Sharjah Dept Comp Sci Sharjah U Arab Emirates Univ Sharjah Dept Comp Engn Sharjah U Arab Emirates Univ Sharjah Dept Elect Engn Sharjah U Arab Emirates

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

The use of deep learning techniques with matrix multiplication has transformed several fields, leading to notable breakthroughs and innovative uses. In this paper, we summarize the state-of-the-art and explain the many applications, approaches, and advancements resulting from the combination of matrix multiplication with deep learning. Examining a wide range of articles released since 2019, this evaluation focuses on the creative methods, strategies, and improvements that scholars in many domains have used. The review encapsulates significant strides in matrix multiplication optimization through deep learning methodologies, unveiling a spectrum of innovative approaches and their consequential impacts. These advancements span dynamic precision neural network inference on silicon photonic processors, adaptable templates for matrix multiplication across various architectures, and coherent analog computing engines for optical matrix multiplication. Furthermore, the exploration extends to unconventional accelerators like AI Engine tiles and low-power multi-layer perceptron accelerators, showcasing remarkable efficiency gains. The integration of machine learning frameworks, such as WISE, into sparse matrix operations further underscores the potential for substantial computational efficiency improvements. Collectively, these findings underscore the transformative potential of deep learning-driven optimization techniques in revolutionizing matrix multiplication performance, offering pathways to enhanced computational efficiency and energy savings across diverse application domains.

关键词： Matrix Multiplication Deep Learning Optimization Applications

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Development of an Automated Feeder for Free Grazing Meat-Producing Animals 9th

Development of an Automated Feeder for Free Grazing Meat-Pro...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Yovkov, Stanislav Krastanov, Zhivko Chivarov, Nayden Petrova, Teodora Panev, Peter Petrov, Rosen Angelova, Teodora Bulgarian Acad Sci Inst Informat & Commun Technol Sofia Bulgaria Agr Inst Agr Acad Stara Zagora Bulgaria

ISBN: (纸本)9789819732982;9789819732999

This article examines the rearing of meat animals and their feeding regimes. Attention has been paid to their condition during the different seasons. Methods for the development of an automated feeder for free grazing animals are presented. The stages of development of the implemented project are described. Algorithms have been developed to perform the given task.

关键词： Automated feeder RFID reader RFID transponder Food hopper Algorithm Temperature sensor Microcontroller

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Exploring the Intersection of Fuzzy Logic and Machine Learning: Applications and Advancements

Exploring the Intersection of Fuzzy Logic and Machine Learni...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Imamguluyev, Rahib Imanova, Tunzala Hajiyev, Asian Farkhad, Durdana Rustamova Hajiyev, Ilham Baku Business Univ IT Dept 88a H Zardabi St AZ-1122 Baku Azerbaijan Azerbaijan Univ Architecture & Construct Dept Reclamat & Water Engn Construct Baku Azerbaijan Western Caspian Univ Mech & Math Dept Baku Azerbaijan Aydinoglu Acad November 8 AZ-1025 Baku Azerbaijan

ISBN: (纸本)9783031671913;9783031671920

This article delves into the synergistic realm where fuzzy logic and machine learning converge, uncovering their collaborative potential in various applications and showcasing the advancements achieved through their intersection. Fuzzy logic, known for handling uncertainty and imprecision, intertwines with machine learning algorithms to enhance decision-making processes in complex and dynamic environments. The exploration encompasses a survey of applications spanning diverse domains, elucidating how the fusion of fuzzy logic and machine learning brings about novel solutions. Furthermore, the article delves into the advancements made in methodologies, algorithms, and frameworks that leverage this intersection, paving the way for improved system performance and adaptability. Through comprehensive analysis and case studies, this work provides valuable insights into the evolving landscape of fuzzy logic and machine learning integration, emphasizing its significance in addressing contemporary challenges and fostering innovation.

关键词： Fuzzy Logic Machine Learning Synergistic Integration Decision-Making Applications Advancements

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Detection of Cyberbullying Text in Bangla Using N-Gram Analysis and Machine Learning Approaches 9th

Detection of Cyberbullying Text in Bangla Using N-Gram Analy...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Jahan, Busrat Chowdhury, Muntasir Karim Mazumder, Shazzad Hossain Akter, Mariam Abu Rayan, Muhammad Rahman, Mohammad Abdur Feni Univ Dept Comp Sci & Engn Feni Bangladesh

ISBN: (纸本)9789819732982;9789819732999

Facebook, Twitter, Instagram, and YouTube are the most widely accepted communities or social media in these present times. Users, from tiny toddlers to teenagers to adults, are responsible for increasing the attraction of these social media. Cyberbullying can produce the effect, anguish, disappointment, and harassment that has piqued the interest of many individuals. Cyberbullying detection on Bangla text is a new research area that is gaining popularity, although it faces certain problems due to the restricted resources available. While a variety of systems have been used to classify English texts, there have been comparatively few studies on Bangla text classification. In this research, we offer an automatic cyberbullying detection model based on gram analysis model and machine learning. This research aims to detect and classify bullying words using several classification algorithms like Logistic Regression, Decision Tree Classifier, Random Forest Classifier, Multinomial NB, K Neighbors Classifier, Linear SVM, Radial Basis Function SVM, SGD, XGB Classifier. Here, a total of 1088 records or comments are scrutinized. There is after, pre-processing techniques, word tagging like general tagging, and abusiveword tagging are used to extract features and construct the structure of comments. This research is then carried out utilizing several machine learning classifier algorithms and the Gram model. Thus, this paper shows the highest performance of accuracy with Unigram, Bigram, and Trigram which is achieved at 90.95, 88.99, and 86.96%. In whichMultinomial NB as a classifier givesmaximum accuracy value for Unigram and Bigram.

关键词： Bangla text Classification Cyberbullying Machine learning N-gram

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Exploratory Customer Discovery Through Simulation Using ChatGPT and Prompt Engineering 9th

Exploratory Customer Discovery Through Simulation Using Chat...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Ilagan, Joseph Benjamin Alabastro, Zachary Matthew Basallo, Claire Louisse Ilagan, Jose Ramon Ateneo Manila Univ Quezon City Philippines

ISBN: (纸本)9789819745807;9789819745814

Entrepreneurship and the tech startup journey are complex, dynamic, risky, and uncertain. Risk-taking needs to consider the complexity and interconnection of different aspects of the entrepreneurial and startup context. A simulation is a model of an existing complex system and experimenting with the model to understand the whole system's behavior. Computer simulations have been widely used to study complex environments such as entrepreneurship. Large language models (LLMs) such as ChatGPT, by nature of their training and design, are models of humans and likely possess latent social information. As such, LLMs could extend their usefulness from mostly being assistants to simulators of human behavior. Technology startups iteratively manage risks involving the uncertainty of their business models through Lean Startup Approaches (LSAs) combined with customer development. The first step in customer development involves customer discovery, where startup co-founders start with a vision and a set of assumptions (or "hypotheses") about their business model and seek feedback from their prospective customers. This study explores using ChatGPT as a simulation tool for customer development for technology startups. The validation of the simulator involves coming up with baseline behavior and feedback without prompt preparations, followed by preparing synthetic prospective customers as agents in the virtual environment. This involves endowment of demographic characteristics and getting behavior and feedback again afterward.

关键词： Computer simulation Simulation Large language models LLM ChatGPT GPT Startup Customer development Lean startup Agent-based modeling Agent-based simulation

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Virtual Reality in the Pain Management of Pediatric Burn Patients, A Scoping Review 12th

Virtual Reality in the Pain Management of Pediatric Burn Pat...

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Santos, Joana Marques, Jorge Pacheco, Joao Rocha, Nelson Pacheco Univ Aveiro Dept Med Sci Aveiro Portugal Univ Aveiro Dept Med Sci IEETA Aveiro Portugal

ISBN: (纸本)9783031602177;9783031602184

Burn care procedures are a major cause of pain, stress and anxiety, and pharmacological methods such as opioids are often insufficient for pain management. This scoping review aimed to understand how virtual reality (VR) might help in the management of pain of pediatric patients suffering from burn wounds. An electronic search was conducted, and thirteen studies were included after the selection process. The studies used various immersive games such as SnowWorld, Dreamland, Virtual River Cruise, Bubbles, Chicken Little or Need for Speed to reduce pain intensity during the wound dressing change procedures, skin stretching exercises, and hydrotherapy or physical therapy sessions. The results showed the feasibility of using VR to support pain management of burn pediatric patients and pointed for the reduction of pain intensity when using VR, as compared with control groups. Future research should include the customization of the VR solutions to improve the motivational relevance and increase treatment variants, the definition of standardized protocols for clinical implementation, or to determine if it is possible to reduce opioids as a primary outcome.

关键词： Pediatric Burn Patients Pain Management Virtual Reality Clinical Research Scoping Review

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Automatic Target Generation for Electronic Data Interchange using Sequence-to-Sequence Models 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Baysan, Mehmet Selman Kizilay, Furkan Gundogan, Haluk Harun Ozmen, Ayse Irem Ince, Gokhan MDP Grp TR-34742 Kadikoy Istanbul Turkiye Istanbul Tech Univ TR-34485 Sariyer Istanbul Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Electronic Data Interchange (EDI) integration is crucial as it streamlines electronic data exchange between companies, enhancing efficiency and accuracy in business processes. This research aims to generate the corresponding target EDI format for given input data in a manner akin to the machine translation problem. The study explores various sequence-to-sequence models and encoder-decoder architectures to identify the most effective outcomes. The impact of these encoder-decoder and data input-output representation techniques on EDI integration is investigated using crowd-sourced datasets. The effectiveness of the proposed approach is demonstrated using different performance evaluation metrics. The findings revealed that using a Multi-Layer Seq2Seq model achieves an accuracy score of 90.21%, BLEU Score of 83.36% and ROUGE-L score of 88.5%, for enhancing EDI integration processes in businesses.

关键词： EDI Integration Artificial Intelligence Natural Language Processing

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A Content-Based System for Discrimination Detection of Ecuadorian Text

A Content-Based System for Discrimination Detection of Ecuad...

引用

Intelligent systems Conference

作者： Vallejo-Huanga, Diego Vallejo, Alexis Contreras, Gustavo Univ Politecn Salesiana IDEIAGEOCA Res Grp Quito Ecuador Univ Politecn Salesiana Dept Comp Sci Quito Ecuador

ISBN: (纸本)9783031663352;9783031663369

The increase in Internet users and the widespread use of social networks has led to higher rates of discrimination. The lack of technological tools and the inability of social networks to identify cyber-bullying has generated psychological affection in minority social groups. This research compiled a glossary of segregative terms in the Ecuadorian context, according to four types of discrimination defined by the United Nations. The discriminatory dictionary was constructed using information from various blogs, research papers, and texts containing segregative expressions. This dictionary allowed the development of a content-based software prototype, using NLP-derived techniques and similarity metrics, to classify the type and degree of discrimination of texts in the Ecuadorian context. The prototype includes a web user interface, which allows for analyzing the corpus of a text and shows the degree of discrimination according to its taxonomy. The prototype's performance was validated through functional tests by experimenting with a dataset of 40 sentences labeled as discriminatory and non-discriminatory. The experimental process used the pre-trained artificial intelligence ChatGPT model as an external validation method. The experiments showed that the cosine vector approach of the proposed prototype has an accuracy of 88%, in contrast to 50% of ChatGPT, for classifying a discriminative text in the Ecuadorian domain.

关键词： Dissimilarity metrics Natural language processing Cyberbullying Artificial intelligence ChatGPT

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