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Exploring the Synergy Between Traditional Markets and Tourism: An Inferential Analysis

Exploring the Synergy Between Traditional Markets and Touris...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Machado, Renata Goncalves Santos, Deborah Oliveira Fernandes, Paula Odete Inst Politecn Braganca UNIAG Braganca Portugal Ctr Fed Edu Tecnol Minas Gerais Belo Horizonte MG Brazil

ISBN: (纸本)9783031834349;9783031834356

The Feira das Cantarinhas and Feira do Artesanato in Braganca holds significant social and economic value for the city, its residents, and local tourism. However, despite its importance, there is a lack of research examining the event's impact on tourism and the marketing strategies employed. Considering that, this study seeks to analyse the influence of sociodemographic and professional variables on the satisfaction, loyalty, and motivation of the Feira das Cantarinhas and Feira do Artesanato visitors. Data was collected through a questionnaire survey during the 2023 edition of the fair, 222 valid responses were collected. An inferential analysis was conducted to meet the study's objectives. The analysis revealed that higher satisfaction with the event is linked to greater loyalty and motivation to attend future editions. However, the correlations between these factors and the number of times participants had participated in or planned to attend were moderate to weak. Additionally, no significant differences were found between sociodemographic variables and satisfaction, loyalty, or motivation.

关键词： Local tourism Promotion of events Handicrafts Traditional markets

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A Secure Self-Adaptive System in Applications of Cognitive Computing 8th

A Secure Self-Adaptive System in Applications of Cognitive C...

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2024 World Congress in computer science, computer Engineering and Applied Computing-CSCE

作者： Jung, Yong-Kyu Georgia Inst Technol Atlanta GA 30332 USA Gannon Univ Erie PA 16541 USA

ISBN: (纸本)9783031856273;9783031856280

In the realm of cognitive computing, integrating self-adaptive and self-organizing systems is pivotal for efficiency, autonomy, and security. Our paper, "A Secure Self-Adaptive System in Cognitive Computing," explores a robust system design tailored for dynamic environments. Leveraging natural language processing and machine learning, it adjusts to environmental changes and threats. Our approach enhances performance with feedback mechanisms and decentralized control, critical for healthcare, finance, and smart infrastructure. With adaptive security measures, the system maintains resilience against cyber threats without compromising functionality. Supported by empirical evidence, our findings demonstrate significant improvements in efficiency, resilience, and autonomy, marking a notable advancement in cognitive computing.

关键词： Self-Adaptive Security Efficiency Autonomy Language Processing Machine Learning Decentralized Control Cognitive Computing

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User Experience and information Security Heuristics for Digital Identity Wallets 1

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Sauer, Max Becker, Christoph Oberweis, Andreas Schork, Sabine Suemeli, Jan FZI Res Ctr Informat Technol D-76131 Karlsruhe Germany

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

In digital identity wallets, users can store and manage their digital identities and verification documents such as driving licences and membership cards. Current digital identity wallets face notable challenges in user experience and information security. Users struggle to understand the concept of digital identity wallets, resulting in personal information being either inadequately stored or inadvertently shared with untrustworthy parties. Thus, digital identity wallets should provide a sufficient level of user experience and information security. For evaluating and improving user experience and information security, heuristics can be used to check the degree of fulfilment for each heuristic and to improve digital identity wallets according to the respective heuristics. This paper reports on the development and evaluation of user experience and information security heuristics for digital identity wallets. To this end, an existing method for user experience heuristics was adapted to also cover information security heuristics. As particular evaluation methods, expert interviews and heuristic evaluations were applied. In total, twelve user experience and six information security heuristics were developed and evaluated.

关键词： User experience Usability information security Digital identity wallets Heuristics Heuristic evaluation

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GT-ACGAN: Graph Topology-Based Auxiliary Classifier GAN for Graph Long-Tailed Classification 5th

GT-ACGAN: Graph Topology-Based Auxiliary Classifier GAN for ...

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Wu, Tianhao Dong, Minggang Tan, Ruoqi Zhao, Weixiao Xia, Lingfu Guilin Univ Technol Sch Informat Sci & Engn Guilin 541004 Peoples R China Guangxi Key Lab Embedded Technol & Intelligent Sy Guilin 541004 Peoples R China

ISBN: (纸本)9789819770007;9789819770014

Long-tailed classification on graphs is ubiquitous yet challenging in many real-world applications. Recently, oversampling approaches have shown promising performance on imbalanced classification tasks. However, most oversampling methods determine the edge based on the principle of similarity or edge generator, this leads to the generation nodes with poor topological diversity and high homogeneity, which seriously affects the performance of the classifier. To bridge this gap, this paper presents an oversampling method based on Graph Topology Assisted Classifier GAN, named GT-ACGAN. Unlike existing methods, we present a latent variable-based graph topology generation method, to learn the topology of the graph. This approach first pretrained a VGAE model using the original graph and gets the original graph's latent variables by the VGAE encoder. Then, the random noises are transformed into latent variables of the fake nodes by neural networks. Finally, the VGAE decoder reconstructs these latent variables into a new adjacency matrix. Then we use the latent variable-based generation method as GT-ACGAN's generator to generate balanced graph data, and GT-ACGAN's discriminator is trained to distinguish the authenticity of each node its category. This approach helps the model to generate graph data with typologies diversity and reconstruct erroneous data generation. To validate the effectiveness of the GT-ACGAN, extensive experiments were conducted on manual long-tailed graphs from three classic citation network datasets (Cora, Citeseer, and PubMed) for constructing long-tailed graphs and three different classic graph classifiers (GCN, GraphSAGE, and GAT). GT-ACGAN outperforms state-of-the-art oversampling algorithms for long tail node classification tasks.

关键词： Graph Neural Networks Long Tail Problem Imbalance Learning graph topology generation method

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Will Changing My Phone Make My Photographs Better? Exploring the Perception of the Quality of Photographs Shot on an iPhone and an Android Phone 15th

Will Changing My Phone Make My Photographs Better? Exploring...

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15th Indian Conference on Human-computer Interaction Design and Research

作者： Katiyar, Palak Sharma, Ishita Joshi, Anirudha Indian Inst Technol Mumbai Maharashtra India

ISBN: (纸本)9783031808289;9783031808296

As smartphone brands use strategic marketing practices to influence purchasing decisions, consumer perceptions become increasingly important. In this paper, we investigate the question: "Is there any difference in the perceived quality of photographs shot on smartphones from different brands?" In the current market, iPhones are perceived to be high-quality, high-price devices, while several Android phones are considered to be more moderate-price, moderate-quality devices. Through this study, we investigate whether photographs shot on an iPhone and on an Android phone have different Perceived Photograph Quality scores. Additionally, we explore whether the presence of a label indicating the brand of the device used affects the perception of the photograph. We present a systematic, within-subjects, counterbalanced study with 36 participants, each of whom assessed 36 photographs, 18 shot on an iPhone and 18 on an Android phone. The photographs were presented in three conditions: non-labelled, a label indicating the correct source device, and a label indicating the wrong source device. The results showed that in the non-labelled condition, there was no significant difference in the Perceived Photograph Quality scores based on the devices used (iPhone/Android) (p = 0.793). However, the scores increased significantly when any label (either correct or wrong) was present (p = 0.006). This indicates that the perceived value of a photograph increases when it is associated with a brand label.

关键词： HCI Perceived Value Smartphone Camera Mobile Photography Brand Perception Interaction Design

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Abusive Comment Detection from Bengali-English Code-Mixed Social Media Texts Using Ensemble of Deep Learning 4th

Abusive Comment Detection from Bengali-English Code-Mixed So...

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4th International Conference on Artificial Intelligence and Knowledge Processing

作者： Fahim, Iftekhar Ahsan, Shawly Hoque, Mohammed Moshiul Chittagong Univ Engn & Technol Chattogram 4349 Bangladesh

ISBN: (纸本)9783031734762;9783031734779

Code-mixing, which involves seamlessly combining multiple languages within a single text, has become increasingly common on social media platforms. The pervasiveness of aggressive content and offensive language on social media presents significant challenges, necessitating the development of automatic detection methods. This problem becomes more complex when dealing with code-mixed text owing to the cultural nuances of different languages. Although efforts to identify abusive content in code-mixed text have primarily concentrated on high-resource languages, research on resource-constrained languages, such as Bengali mixed with English, still needs to be completed. Some studies have aimed at detecting abusive content in transliterated Bengali texts. However, there is a notable absence of research addressing the detection of abusive content in Bengali-English code-mixed texts. To address this gap, this paper presents a custom-built Bengali-English code-mixed dataset containing 2700 annotated comments categorized as abusive and non-abusive. To facilitate research in this area, this work proposes an ensemble of deep learning (DL) models: CNN (using GloVe embeddings), LSTM (implemented with Keras), and BiLSTM (utilizing FastText embeddings). The ensemble approach attained the most elevated weighted f1-score of 0.81. This research aims to tackle the growing issue of abusive content in code-mixed data, creating safer and more inclusive online environments.

关键词： Natural language processing Code-mixing Deep learning Text processing Abusive content detection

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Bearing Fault Diagnosis with Small Samples Based on Multi-scale Convolutional Kernels Attention Network 5th

Bearing Fault Diagnosis with Small Samples Based on Multi-sc...

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5th China Intelligent Robotics Academic Conference

作者： Xu, Yong Huang, Ruyi Xian, Shuai Zhong, Yong South China Univ Technol Shien Ming Wu Sch Intelligent Engn Guangzhou 511442 Peoples R China South China Univ Technol Sch Mech & Automot Engn Guangzhou 510641 Peoples R China Hong Kong Univ Sci & Technol Dept Ind Engn & Decis Analyt Hong Kong 999077 Peoples R China

ISBN: (纸本)9789819616138;9789819616145

Bearings are widely used in equipment such as robots. Therefore, timely diagnosis of their faults is the necessary basis for maintaining production safety. With the promotion of intelligence technology, deep learning has become an important tool for the intelligent diagnosis of bearing faults and has received much research attention. However, existing research models usually require many failure samples to achieve preset performance. In actual production, because of the rugged operating environment of bearings and the short operating time under abnormal conditions, failure data is missing. To address this problem, an intelligent fault diagnosis model called the multi-scale convolutional kernels attention network (MSCKAN) is proposed in this context. The model is grounded in a two-dimensional convolutional neural network (2D-CNN), which obtains input through the reconstruction of time-domain samples. Then, it combines multiscale convolution kernels and the efficient channel attention (ECA) mechanism to increase its feature extraction and recognition performance for small samples, thereby reducing the need for fault data. The performance of the MSCKAN was tested through the constructed small-sample experimental datasets and compared with that of other models. The testing results strongly prove that the MSCKAN has superior performance in small-sample diagnosis for bearing faults.

关键词： Bearing Fault Diagnosis MSCKAN Small Samples

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Optimizing Coverage and Energy in Underground Wireless Networks

Optimizing Coverage and Energy in Underground Wireless Netwo...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Galeas-Cutino, Ignacio Estela Zamora, Maria Soto, Ismael Univ Santiago Chile Elect Santiago 9170124 Chile Ctr Invest Multidisciplinario Tecnol Telecomunica Dept Ingn Santiago Chile

ISBN: (纸本)9783031834318;9783031834325

This paper presents a comprehensive theoretical analysis of light propagation in underground Visible Light Communication (VLC) systems. Focusing on channel model optimization, we explore both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) components to elucidate their roles and influences on system performance. Power received by any optical receiver is meticulously modeled, considering factors such as photodetector (PD) responsivity, DC channel gain components, and additive noise. Our findings indicate optimal conditions with received power (P-r) values of -55 dBm and V LCbitrate of 4500 kbps, yielding high Mean Opinion Scores (MOS) of 4.5. Conversely, suboptimal conditions yield P-r of - 75 dBm and V LCbitrate of 2000 kbps, with MOS of 2.8, reflecting the impact of poor alignment and scattering.

关键词： Wireless sensor networks Smart directional antennas Visible Light communications

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Comparative Analysis of Machine Learning Based Soil pH Prediction Using Spectral Bands and Indices 2nd

Comparative Analysis of Machine Learning Based Soil pH Predi...

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2nd International Conference on Agriculture-Centric Computation

作者： Jain, Shagun Sethia, Divyashikha Tiwari, Kailash Chandra Delhi Technol Univ Dept Software Engn Delhi India Delhi Technol Univ Multidisciplinary Ctr Geoinformat Delhi India

ISBN: (纸本)9783031744396;9783031744402

Soil pH is vital in agriculture and environmental science, affecting plant growth, nutrient availability, and soil health. Remote sensing and Machine Learning (ML) accurately predict and map soil pH, guiding effective soil management for optimized yields and environmental conservation. This paper compares ML-based soil pH prediction using multispectral bands and various spectral indices derived from remote sensing data. It uses indices such as vegetation indices, soil indices, temperature, and thermal indices individually and in combination to predict soil pH. Three primary ML models, namely Partial Least Square Regression (PLSR), Support Vector Regression (SVR), and Multilayer Perceptron (MLP), are utilized for predicting soil pH. The findings suggest that spectral indices yield marginally superior predictions compared to spectral bands alone. This finding highlights the significance of using spectral indices, especially vegetation indices, to estimate the soil pH. The incorporation of spectral indices improves the forecast precision because of the subtle data they record about the characteristics and composition of the soil. This research advances remote sensing in soil science by shedding light on the viability and effectiveness of using satellite data for soil pH prediction.

关键词： Soil pH Spectral bands Spectral Indices Machine Learning

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Leveraging Artificial Intelligence in Education: Analyzing Academic Engagement, Application, and Challenges 4th

Leveraging Artificial Intelligence in Education: Analyzing A...

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4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Al-Hadrami, Ahmed Alyahmadi, Hamed Al-Khatib, Khalil Muhammad Boukhalkhal, Ali Al Rashidi, Said Al Habsi, Khoula Salim ASharqiyah Univ Ibra Oman AOU Oman Seeb Oman Sanaa Univ Sanaa Yemen Al Razi Univ Sanaa Yemen Univ Amar Telidji Laghouat Laghouat 03000 Algeria Islam Educ Seeb Oman

ISBN: (纸本)9783031821493;9783031821509

The objective of the study is to examine the referencing behavior of a group of academic university members in relation to the utilization of artificial intelligence in the educational process, as well as the difficulties associated with its implementation. The study employed a descriptive methodology, using interviews as a means to analyze the reference activity of a selected group of Arab university academics. The investigation produced the subsequent findings: The study sample estimated that there are numerous and different uses of artificial intelligence in the educational process at universities. The arithmetic means of these applications, as determined by the study of reference activity, fell within the range of 5.61 to 6.01, indicating relatively high levels for both. The scale levels for the use of reference activity were as follows: observance (mean = 5.72), specification (mean = 5.43), clarity (mean = 6.16), and conception (mean = 5.94).The interviews revealed a variety of difficulties and barriers (including human, technical, financial, cognitive, and social factors) encountered by university instructors when incorporating artificial intelligence into the teaching process. These challenges varied from an arithmetic mean of 5.6 to 6.17, indicating moderately high and moderately high levels, respectively. The research suggests the incorporation of artificial intelligence application technology into the higher education teaching process.

关键词： Reference Activity Analysis Artificial Intelligence Educational Process

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