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computer, Vision and Intelligent Technology (ICCVIT), International Conference on

作者： Ziye Wang Jianyu Xiao School of Computer Science and Technology Huaibei Normal University Huaibei China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior Huaibei China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

This essay introduces a new approach to address the challenges of applying Dempster-Shafer evidence theory to tackling high-conflict evidence. We first employed Jousselme’s distance and compatibility coefficients to measure confidence and support, then converted these values into vectors. Next, we applied game theory to convert the vectors into a system of linear equations,from which we obtained a corresponding combination of weight coefficients that we used to modify the initial evidence. Finally, we applied the Dempster-Shafer combination rule to achieve evidence fusion. A case analysis shows that our proposed method provides more sensible fusion results for high-conflict evidence.

关键词： computer vision Accuracy Evidence theory Data integration Reliability theory Vectors Game theory Convergence

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Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes

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OpenNano 2025年 21卷

作者： Makalew, Brilly Andro Abrori, Syauqi Abdurrahman Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta 11480 Indonesia

This study explores a comparative analysis of PLGA nanoparticles and liposomes as potential carriers for brain cancer drug delivery, with a special focus on how material informatics enhances their design, biocompatibility, and drug release profiles to improve treatment efficacy and contribute to sustainable health outcomes. The investigation employed a bibliometric analysis using Scopus and VOSviewer to uncover the role of material informatics in optimizing these nanocarriers. The analysis revealed that material informatics, particularly through the application of machine learning and molecular dynamics simulations, significantly optimizes the performance of both PLGA nanoparticles and liposomes. The results highlighted distinct strengths of each nanocarrier: PLGA nanoparticles excel in biodegradability, while liposomes offer superior drug encapsulation capabilities. However, material informatics techniques bridged these enhancing drug release kinetics, stability, and biocompatibility. These improvements are crucial for effective delivery across the blood-brain barrier, a major challenge in brain cancer treatment. The integration of computational modelling, machine learning, and high-throughput screening enabled by material informatics is shown to be a key factor in advancing the design and optimization of these nanocarriers. By leveraging these tools, researchers can develop more personalized and efficient drug delivery systems tailored to address the specific challenges of glioblastoma therapy, ultimately contributing to sustainable health outcomes © 2024 The Author(s)

关键词： Bibliometric analysis Brain cancer Drug delivery Liposomes Material informatics Nanocarriers PLGA nanoparticles VOSviewer

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2.3- μ m deep UV micro-LEDs fabricated by self-aligned selective thermal oxidation process

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Optics letters 2025年第11期50卷 3628-3631页

作者： Zhiyuan Liu Haicheng Cao Tingang Liu Patsy A Miranda Cortez Zixian Jiang Kexin Ren Na Xiao Yi Lu Xiao Tang Zuojian Pan Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering Program CEMSE Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia

Recently, techniques for fabricating micro-sized deep ultraviolet light-emitting diodes (DUV LEDs) have been gaining attention. In this work, we propose a selective thermal oxidation (STO) process to fabricate ultra-small DUV micro-LEDs. Annealed in the air at 900°C for 2 h, the p-layers without SiO protection are oxidized into insulating oxides, and oxygen penetrates into parts of the quantum wells. In contrast, the patterned SiO protects the LED structure in the pixel regions. Therefore, micro-LED pixels are formed by the patterned SiO and thermal oxidation process rather than the conventional reactive ion etching. The formed oxide in the unprotected region can function as the insulation layer between p-n electrodes. Meanwhile, the boundary between the pixel and the surrounding oxide is naturally formed during thermal oxidation, which is a "self-aligned" process. Dielectric deposition, precise lithography alignment, and aperture etching in the conventional process are no longer required in STO-based micro-LED fabrication, which reduces production complexity and cost. Based on the STO process, we have achieved 2.3-µm DUV micro-LED standalone pixels and arrays with a 270-nm emission wavelength. The standalone DUV micro-LED is possibly the smallest reported in the literature to date, which has a low-operation voltage of 4.9 and 6.75 V at 10 and 1000 A/cm. Meanwhile, the fabricated DUV micro-LED arrays show leakage current density 4 × 10 A/cm at -5 V and a peak EQE of 0.77% under unpackaged conditions. We hope this work provides a new insight into micro-LED fabrication and further promotes future performance growth of DUV LEDs.

关键词： Light emitting diodes Light extraction Lithography Multiple quantum wells Quantum wells Ultraviolet light emitting diodes

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Evaluating Fast Adaptability of Neural Networks for Brain-computer Interface

Evaluating Fast Adaptability of Neural Networks for Brain-Co...

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International Joint Conference on Neural Networks (IJCNN)

作者： Anupam Sharma Krishna Miyapuram Department of Computer Science & Engineering Indian Institute of Technology Gandhinagar Gujarat India Department of Cognitive & Brain Sciences Indian Institute of Technology Gandhinagar Gujarat India

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Electroencephalography (EEG) classification is a versatile and portable technique for building non-invasive Brain-computer Interfaces (BCI). However, the classifiers that decode cognitive states from EEG brain data perform poorly when tested on newer domains, such as tasks or individuals absent during model training. Researchers have recently used complex strategies like Model-agnostic meta-learning (MAML) for domain adaptation. Nevertheless, there is a need for an evaluation strategy to evaluate the fast adaptability of the models, as this characteristic is essential for real-life BCI applications for quick calibration. We used motor movement and imaginary signals as input to Convolutional Neural Networks (CNN) based classifier for the experiments. Datasets with EEG signals typically have fewer examples and higher time resolution. Even though batch-normalization is preferred for Convolutional Neural Networks (CNN), we empirically show that layer-normalization can improve the adaptability of CNN-based EEG classifiers with not more than ten fine-tuning steps. In summary, the present work (i) proposes a simple strategy to evaluate fast adaptability, and (ii) empirically demonstrate fast adaptability across individuals as well as across tasks with simple transfer learning as compared to MAML approach.

关键词： Training Adaptation models Transfer learning Brain modeling Motors Electroencephalography Brain-computer interfaces

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Work-in-Progress: Preliminary Work Introducing Automated Code Critiques in First-Year engineering MATLAB programming 53

Work-in-Progress: Preliminary Work Introducing Automated Cod...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Albrant, Laura Pendse, Pradnya Brown, Laura E. Sticklen, Jon Jarvie-Eggart, Michelle Ureel, Leo C. Michigan Technological University Department of Engineering Fundamentals HoughtonMI United States Michigan Technological University Dept. of Cognitive and Learning Sciences HoughtonMI United States Michigan Technological University Dept. of Computer Science HoughtonMI United States

ISBN: (纸本)9798350336429

This Work-in-Progress paper presents WebTA, a code critiquer developed using Java, currently being expanded to MATLAB for first-year engineering students. It outlines the modification process of the existing WebTA software for MATLAB and shares the results of three beta tests conducted with 52 students. The paper highlights the significance of providing an automated tool that helps students identify and improve coding errors is highlighted (addressing the gap between computer science and engineering education). WebTA's feedback-on-demand feature addresses the challenge of providing timely and personalized feedback to a large number of students, contributing to the enhancement of first-year engineering education. © 2023 IEEE.

关键词： auto critiquer first-year engineering MATLAB novice programming

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Comprehensive study and analysis for StarGAN and StarGAN-v2 in the task of image generation 2

Comprehensive study and analysis for StarGAN and StarGAN-v2 ...

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2nd International Conference on Computing Innovation and Applied Physics, CONF-CIAP 2023

作者： Cai, Yuanan Li, Yepeng Zhang, Zhenyu Department of Computer Engineering Baskin School of Engineering University of California Santa CruzCA95064 United States Department of Cognitive Science University of California - San Diego La Jolla CA92092 United States Department of Information Technology Monash University Wellington Rd ClaytonVIC3800 Australia

With the continuous development of deep learning and artificial intelligence industry, more and more neural networks have been developed. Among them, one typical network widely used is StarGAN. It solves the problem of requiring multiple generators and discriminators for multiple domains and style transitions. In this article, we will analyze and explore StarGAN v1 and StarGAN v2. including StarGAN's development history, advantages and disadvantages in the application, etc. At the same time, we will compare StarGAN with other neural networks such as CycleGAN and MSGAN through some discrimination criteria, and clearly demonstrate the influence of different networks on the generation of image data sets through quantitative and qualitative analysis. In addition, we also found a representative code on some of the actual uses of StarGAN for hair replacement through online sources. Since this code may be used to confuse the use of StarGAN v1 and v2, we will also improve this code in the article and put forward suggestions for changes. In this paper, we carried out the specific analysis of StarGAN's loss function based on the existing data and put forward some relevant insights. By taking the data we searched for StarGAN, it can be found that StarGAN could use as few resources as possible to achieve clearer and more varied results during the image generation task © Published under licence by IOP Publishing Ltd.

关键词： Deep learning

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AI Recommendations: Friend or Foe? Unraveling the Impact on Consumer Benefits and Privacy 11

AI Recommendations: Friend or Foe? Unraveling the Impact on ...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Dewanthi, Desyra Sukma Kristopo, Hari Qomariyah, Nunung Nurul Axel, Muhammad Business Management & Marketing Program Binus Business School International Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Food Technology Department Jakarta11480 Indonesia School of Computing and Creative Arts Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350389654

Artificial Intelligence (AI) and marketing have transformed consumer behavior and shopping experiences, especially through Recommender Systems (RSs) in e-commerce. RSs use algorithms to provide personalized recommendations, enhancing shopping convenience. However, this raises data privacy and ethical concerns, as RSs rely on user data. This research explores the quality determinants of RSs and their impact on consumer behavior, focusing on privacy awareness and its effect on repurchase intentions. Using a qualitative approach with semi-structured interviews, the study targets Indonesian respondents aged 18-40 with e-commerce experience. Findings reveal that recommendation quality, especially self-reference and vividness, significantly influences purchasing decisions. Respondents prefer recommendations that match their preferences and are visually appealing. Positive shopping experiences are linked to efficient and accurate RSs, but there's a need for improvements in transparency, novelty, diversity, and advanced technologies like AR. Respondents are aware of digital data storage but have limited understanding of privacy concerns. They trust e-commerce platforms with basic personal details but are hesitant to share sensitive information. Despite privacy issues, e-commerce remains vital, with respondents emphasizing the need for transparency, robust security, and clear explanations for data use to maintain trust. Addressing these issues not only enhances customer experience but also demonstrates that consumer trust directly impacts the sustainability and success of the business. © 2024 IEEE.

关键词： Differential privacy

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Preliminary Evaluation of Kyokko for Inter-FPGA Communication Framework CIRCUS

Preliminary Evaluation of Kyokko for Inter-FPGA Communicatio...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Kaito Kitazume Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

In recent years, Field-programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz... 详细信息

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

关键词： Conferences High performance computing Circuits Cluster computing Low latency communication Field programmable gate arrays

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Leveraging Sound Localization to Improve Continuous Speaker Separation

Leveraging Sound Localization to Improve Continuous Speaker ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hassan Taherian Ashutosh Pandey Daniel Wong Buye Xu DeLiang Wang Department of Computer Science and Engineering The Ohio State University USA Meta Reality Labs USA Center for Cognitive and Brain Sciences The Ohio State University USA

Continuous speaker separation aims to separate overlapping speakers in real-world environments like meetings, but it often falls short in isolating speech segments of a single speaker. This leads to split signals that adversely affect downstream applications such as automatic speech recognition and speaker diarization. Existing solutions like speaker counting have limitations. This paper presents a novel multi-channel approach for continuous speaker separation based on multi-input multi-output (MIMO) complex spectral mapping. This MIMO approach enables robust speaker localization by preserving inter-channel phase relations. Speaker localization as a byproduct of the MIMO separation model is then used to identify single-talker frames and reduce speaker splitting. We demonstrate that this approach achieves superior frame-level sound localization. Systematic experiments on the LibriCSS dataset further show that the proposed approach outperforms other methods, advancing state-of-the-art speaker separation performance.

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Telematics Work Field Review Text Classification Using the Naïve Bayes Method

Telematics Work Field Review Text Classification Using the N...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Aries Maesya Yaya Heryadi Yulyani Arifin Lukas Wayan Suparta Computer Science Department BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Reseach Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Indonesia

Indonesia will benefit from a demographic boom in 2030 with a higher labor supply than in earlier decades. Then in industrial revolution 4.0 robotics and artificial intelligence will take the place of low-skilled or menial employment that don't require specialized expertise (AI). To aim research is Telematics Work Field Review Text Classification Using the Naïve Bayes Method. The method using Multinomial Naïve Bayes model which is trained to learn from patterns in training data set without being programmed explicitly. Then, based on the Term Frequency - Inverse Document Frequency, consider the weighting of the word used (TF-IDF). The text classification stage is then carried out using the multinominal nave bayes classification method with evaluation using the confusion matrix, following the acquisition of the TF-IDF value. In the study it took data with web crawling techniques on social media sites twitter. The data collected was 936 data consisting of 7,8% negative sentiments, 26,4% positive sentiments, and 65,8% neutrals. The results of accuracy testing using the Confusion Matrix. And from the results of such tests resulted in an accuracy of 66%, precision 73%, and recall 85%.

关键词： Social networking (online) Service robots Text categorization Blogs Training data Telematics Data models

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