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Artificial intelligence for All: Challenges and Harnessing Opportunities in AI Democratization

Artificial Intelligence for All: Challenges and Harnessing O...

引用

2024 IEEE international conference on Machine Learning and Applied Network Technologies, ICMLANT 2024

作者： Castro, Keylin Alessandra Siwady, Joselyn Alvarado Castillo, Erika Alonzo, Alberto Cardona, Manuel Perdomo, María Elena Facultad de Ingeniería Universidad Tecnológica Centroamericana San Pedro Sula Honduras POSFACE Universidad Nacional Autónoma de Honduras Tegucigalpa Honduras STEAM Robotics Academy San Salvador El Salvador Facultad de Ingeniería Industrial Universidad Tecnológica de Panamá Panamá Ciudad de Panamá Panama Research Department Universidad Don Bosco San Salvador El Salvador

ISBN: (纸本)9798350389180

This study analyzes the technical, economic, and social barriers limiting access to artificial intelligence (AI) in less developed regions. Using a non-experimental, quantitative approach, methods such as interviews and content analysis are employed to understand perceptions and contexts surrounding AI democratization. The research design does not aim to manipulate variables but rather to analyze existing relationships. Only 30% of countries, mainly in North America, Europe, and parts of Asia, have significant access to advanced technologies, while less than 20% have implemented national AI policies. Barriers include a lack of infrastructure and high costs, restricting AI adoption in underdeveloped areas. Additionally, ethical implications, such as privacy, transparency, and fairness, are highlighted. To democratize AI, it is crucial to include diverse communities in its design and establish policies that promote equitable access. © 2024 IEEE.

关键词： Accessibility AI policies Artificial intelligence Democratization Economic barriers Ethics

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analysis of Industry 4.0 Barriers: A Fuzzy DEMANTEL Approach

Analysis of Industry 4.0 Barriers: A Fuzzy DEMANTEL Approach

引用

2024 IEEE international conference on Industry 4.0, Artificial intelligence, and Communications Technology, IAICT 2024

作者： Gurrala, Kavitha Reddy Choudhary, Sharuti Operations & Marketing Woxsen University India Woxsen University India

ISBN: (纸本)9798350353464

The fourth Industrial Revolution (4th IR) i.e., Industry 4.0 features the deployment of extensive automation in the form of smart factories and smart machines facilitating improved information and data flows across the value chains. It facilitates the integration of intelligent digital technologies into the production processes for enhanced productivity, efficiency, flexibility, quality, transparency, intelligent decision making, and customization. Consequently, research has been embarked on studying the main elements of the 4th IR i.e., technology pillars (Autonomous Robots/Advanced robotics, Augmented Reality/Virtual Reality, Smart Sensors, Big Data Analytics/Machine Learning, Cloud Computing/Cognitive Computing/Edge Computing, Additive Manufacturing etc.), role of people within the highly automated environments, level of mass personalization/adaptability, sustainability performance, and the economic prospects. In this pursuit, a few studies also concentrated on listing common challenges associated with Industry 4.0 deployment within Manufacturing Systems. Nonetheless, a dearth of research is observed with regards to listing, comprehensive analysis, and prioritization of barriers towards the implementation of the 4th IR within small to medium-sized enterprises. Hence, this study aims at identifying and prioritizing an exhaustive set of barriers for successful deployment of Industry 4.0 within Manufacturing Systems through Fuzzy DEMANTEL analysis towards making the manufacturing processes more intelligent, efficient, and precise. ©2024 IEEE.

关键词： Smart manufacturing

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ChatGPT as a Negotiator: An analysis of its Adherence with Proportionality and Equality 7

ChatGPT as a Negotiator: An Analysis of its Adherence with P...

引用

7th international conference on Algorithms, Computing and Artificial intelligence, ACAI 2024

作者： Aksoy, Meltem Tsishetska, Veronika Computer Science Research Center Trustworthy Data Science and Security Technical University Dortmund Dortmund Germany Computer Science Technical University Dortmund Dortmund Germany

ISBN: (纸本)9798331529314

This study examines the adherence of ChatGPT (GPT-3.S and GPT-4) to fairness principles, specifically proportionality and equality, in negotiation scenarios. Three distinct negotiation contexts were explored: work-study program funding, company sale proceeds division, and employee bonus allocation. The models were prompted to prioritize proportionality, equality, or no specific fairness principle to assess how they respond in different ethical frameworks. A combination of qualitative and quantitative methods, including dialogue analysis, sentiment tracking, and fairness scoring, was used to evaluate their ne-gotiation behaviors. Results indicate that both models tend to favor proportionality by default, with GPT-4 showing greater adaptability compared to GPT-3.S. When explicitly directed to prioritize equality, the models followed these instructions but maintained a largely assertive negotiation style with limited engagement in dynamic exchanges. Sentiment analysis revealed that both models adopted increasingly positive tones as nego-tiations progressed. However, both versions were susceptible to prompt manipulation, potentially compromising fairness in some outcomes. This research highlights the potential of LLMs like ChatGPT in automating fair negotiations, though improvements in consistency, adaptability, and safeguards against manipulation are necessary for more robust, ethical applications in real-world scenarios. © 2024 IEEE.

关键词： Economic and social effects

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Velocity Field-Based Surveillance Video Frame Deletion Detection Using Siamese Network 27th

Velocity Field-Based Surveillance Video Frame Deletion Detec...

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27th international conference on pattern Recognition, ICPR 2024

作者： Su, Yang Tan, ShunQuan Huang, Jiwu College of Information Engineering Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9783031783111

Surveillance videos play a crucial role in providing evidences. However, the deletion of even a few frames can significantly impact the interpretation of events, while the deletion can be performed easily using video editing softwares without leaving visual traces. This paper introduces a novel method to detect video frame deletion based on velocity field characteristics. The main idea is to convert long videos into a feature sequence, which appears as a sequence containing outlier values for videos with frame deletions, and as a sequence without outlier values for original videos. The proposed approach employs a siamese network to distinguish frame deletions between adjacent frames. A video can be transformed into a feature sequence through the siamese network, and the resulting sequence is fed into a binary classifier for final classification. Experimental results demonstrate the effectiveness of our proposed approach, even for longer videos (e.g., 2000 frames) with minimal frame deletions (e.g., 1 frame). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Digital forensics

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A Novel Machine Learning Model for Sarcasm Detection on Facebook Comments 3

A Novel Machine Learning Model for Sarcasm Detection on Face...

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3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Puvvada, Soumya Kusuma Shaik, Mastan Valli Galla, Karthik Venkatrama Phani Kumar, S. Venkata Krishna Kishore, K. Vfstr Deemed to Be University Department of Cse Andhra Pradesh Guntur India

ISBN: (纸本)9798350375190

This research focuses on identifying sarcasm in online comments using a combination of machine learning techniques, including feature extraction, pattern recognition, and analysis of emojis. Various methods were utilized to categorize comments into sarcastic and non-sarcastic categories, aiding computers in understanding the sentiment expressed. The experiments have yielded positive results, particularly with hierarchical clustering, which exhibited higher Silhouette Scores and improved cluster quality compared to other techniques. The study used a dataset containing 5,471 comments, labeled with sarcasm as (0 for sarcastic, 1 for non-sarcastic), with sentiment analysis facilitating comment categorization. By categorizing comments based on sentiment, computers can easily identify the underlying sentiment of each comment. The combination of features, including emojis and text, adds an extra layer of meaning, helping the system to identify the type of comment easily. The objective is to help computers understand human language better, enabling them to grasp the real meaning behind a joke and sarcastic sentence, there by making online communication more accurate and effective. © 2024 IEEE.

关键词： Sentiment analysis

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A Regression analysis and Prediction Method for Assembly Error of Aviation Product Components 7

A Regression Analysis and Prediction Method for Assembly Err...

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7th international conference on pattern Recognition and Artificial intelligence, PRAI 2024

作者： Yan, Zhang Yuan, Zhou Pengfei, Ma Co. Ltd Beijing China Co. Ltd Aircraft Engineering Division Beijing China

ISBN: (纸本)9798350350890

There are many factors that would affect the assembly error in aircraft assembly process, and the coupling rules are complex among those factors. The existing numerical methods cannot effectively analyze the assembly error, resulting in poor assembly accuracy and long development cycle. This paper aims at the small sample size of aircraft assembly site data. By measuring and analyzing the data on the assembly sites, the error modeling method and information feedback mode based on assembly site data were established. On this basis, an assembly tolerance prediction method based on artificial intelligence is proposed. Then, taking typical aircraft parts assembly as an example, the error prediction results of the proposed method in this paper and the traditional neural network method were compared. The prediction accuracy of this paper's method (0.003 mm) is obviously higher than that of the latter (0.011 mm), which verifies the effectiveness and reliability of the proposed method. Finally, the predicted assembly error probability was used to guide the adjustment of the assembly tolerance scheme, thereby improving the assembly accuracy and shortening the assembly cycle. © 2024 IEEE.

关键词： Fits and tolerances

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analysis of AI Design Creation Based on Generative Digital Construction of Sichuan Stone Carving Plant patterns 24

Analysis of AI Design Creation Based on Generative Digital C...

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2024 international conference on Digital Society and Artificial intelligence, DSAI 2024

作者： Liu, Lijuan Zhou, Sicheng Sun, Yan Zheng, Yi Tianfu College of Swufe Sichuan China Sichuan Normal University Sichuan Chengdu China

ISBN: (纸本)9798400709838

Based on the complementary advantages of data model analysis of Generating Adversarial Network(GAN) algorithm and theoretical model analysis of art cognition, with the possibility of AI imagination as the research problem, and the intelligent design concept and research method for the future audience are constructed. Through Sichuan stone carving plant pattern intelligent generative image experiment to data analysis, then based on art cognitive cognitive flexible view, cognitive comprehensive view of theory model of further validation analysis, reveal AI content production process curing and production results of hardening mechanism, explore the motivation of AI digital art lack of art. © 2024 Copyright held by the owner/author(s).

关键词： Generative adversarial networks

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Image Classifications Methods analysis with Differen Methods to for Identifying best Image Layout with High Resolution

Image Classifications Methods Analysis with Differen Methods...

引用

2023 international conference on Artificial intelligence and Smart Communication, AISC 2023

作者： Mahesh, T.R. Vivek, V. Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350322309

This researcher investigated effective much eye opening and pattern detection algorithms. Finally, this article used two frameworks to argue that geospatial investigation systems for patterns are necessary. One of most popular method for analyzing photographs using image processing and analysis math is probably visual configuration methods. Imagery description is also necessary for the evaluation of remote sensing tools used for thorough land investigation. The three main image configuration techniques that are often used for far detection are opinion piece visual analysis, controlled groupings, and solos visual categorization. The approach used in these image layout techniques is combined in the present study. The present study also briefly summarizes each approach's use in exploring distant sensing info while also outlining the steps for each way using stream outlines and frameworks. Generally speaking, a quick overview of image layout techniques is included in the test. © 2023 IEEE.

关键词： Image classification

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Enhancing ECG Classification through Individual 12-lead analysis and fQRS pattern based on Deep Learning technique 18

Enhancing ECG Classification through Individual 12-lead Anal...

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18th international Joint Symposium on Artificial intelligence and Natural Language Processing (ISAI-NLP) / 4th international conference on Artificial intelligence and Internet of Things (AIoT)

作者： Suriyachay, Kitiya Yagi, Kunimasa Shikida, Mikifumi Kochi Univ Technol Grad Sch Engn Kochi Japan Kanazawa Med Univ Dept Internal Med Kanazawa Ishikawa Japan Kochi Univ Technol Sch Informat Kochi Japan

ISBN: (纸本)9798350371215

Diabetes patients can experience congestive heart failure due to diastolic dysfunction from its early phases. This study addresses a crucial challenge by proposing a novel methodology for predicting this complication. We introduce an innovative approach by examining the Fragmented QRS (fQRS) pattern within the individual leads of the 12-lead Electrocardiogram (ECG) data. Our approach employs a specialized deep learning model, ResNet1D, trained on each lead separately. The outcomes from these leads are then combined using a Random Forest classifier for more accurate predictions. The experiment results show that our proposed model outperforms other models utilizing combined 12-lead ECG signals. Each lead encapsulates specific and pivotal diagnostic insights, enhancing the model's performance in predicting ECG signal anomalies.

关键词： ECG classification ECG electrocardiogram fQRS ResNet Random Forest Deep learning

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Crowdsensed Data-oriented Distributed and Secure Spatial Query Scheme 22

Crowdsensed Data-oriented Distributed and Secure Spatial Que...

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IEEE 22nd international conference on Trust, Security and Privacy in Computing and Communications (TrustCom) / BigDataSE conference / CSE conference / EUC conference / ISCI conference

作者： Li, Yuxi Zhou, Fucai Chen, Jingjing Ji, Dong Northeastern Univ Sch Comp Sci & Engn Shenyang Peoples R China Northeastern Univ Software Coll Shenyang Peoples R China Northeastern Univ Natl Frontiers Sci Ctr Ind Intelligence & Syst Op Shenyang Peoples R China

ISBN: (纸本)9798350381993;9798350382006

Focusing on the privacy concerns and leakage abuse of sensory data collection in mobile crowdsensing (MCS) environment, we propose a crowdsensed data-oriented distributed and secure spatial query scheme while ensuring data privacy as long as query patterns. To cater to the demands of real-world MCS workloads, we designed a distributed multi-layer architecture and leveraged distributed hash functions(DHT) and broadcast encryption(BE) to achieve load-balancing and enforce access control. Our scheme incorporates a recently developed cryptographic tool-function secret sharing (FSS) to safeguard the query pattern and sensory data from potential compromises at the server layer. The analysis demonstrates that our scheme achieves affordable query complexity while satisfying adaptive L-semantic security. Encouraging experimental results substantiate the efficacy of our scheme, the growth rates of query cost diminishes as the number of records and participants increases. These findings emphasize the suitability of our scheme for crowdsensing applications with fine-grained access control requirements and establish it as an efficient cryptographic tool that holds promise for diverse MCS applications.

关键词： mobile crowdsensing secure data sharing spatial queries query pattern access control

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