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Microelectronics Technology and Devices (SBMicro)

作者： Reinaldo Velásquez Diego Tami Gilberto Medeiros-Ribeiro Cássio G. Rego Jhonattan C. Ramirez Graduate Program in Electrical Engineering UFMG Brazil Institute of Technological Sciences UNIFEI Brazil Department of Computer Science UFMG Brazil Department of Electronics Engineering UFMG Brazil

In this paper, we demonstrated a highly sensitive microwave-based resonator sensor capable of detecting variations in an aqueous medium of up to 0.94 mg/dL. In the presented device, the intrinsic resonant response (resonant amplitude, resonant frequency, and quality factor) is capacitively perturbed in reaction to the sample presence. To achieve higher sensitivity, the sample under testing generally is placed on the resonator surface, where the electric field is highly concentrated at the operating frequency. Thus, demonstrating excellent results in terms of sensitivity and reproducibility.

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RecurPocket: Recurrent Lmser Network with Gating Mechanism for Protein Binding Site Detection

RecurPocket: Recurrent Lmser Network with Gating Mechanism f...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Peiying Li Boheng Cao Shikui Tu Lei Xu Department of Computer Science and Engineering Center for Cognitive Machines and Computational Health (CMaCH) Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

It is an essential step to locate the binding sites or pockets of drug molecules on protein structure in drug design. This is challenging because the 3D protein structures are usually in complicated, irregular shape and the pockets are relatively small. Existing deep learning methods for this task are U-Net models, and they have forward skip connections to efficiently transfer features of different levels of 3D structure from encoder to decoder for improving pocket prediction. However, there is still room to improve prediction accuracy. In this paper, we propose RecurPocket, a recurrent Lmser (Least mean square error reconstruction) network for pocket detection. A gated recurrent refinement is devised in RecurPocket to enhance the representation learning on the 3D protein structures. This is fulfilled by feedback connections in RecurPocket network from decoder to encoder, recurrently and progressively improving the feature embedding for accurate prediction. Moreover, a 3D gate mechanism filters out irrelevant information through the feedback links that interfere with detection, making the prediction more precise and clear. Experiments show that RecurPocket improves by 3%-9% on top-n prediction compared with previous state-of-the-art on five benchmark data sets. The source code and trained model are available at https://*** CMACH508/RecurPocket.

关键词： Proteins Representation learning Drugs Protein engineering Solid modeling Three-dimensional displays Source coding

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SCANS: Mitigating the Exaggerated Safety for LLMs via Safety-Conscious Activation Steering

arXiv

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arXiv 2024年

作者： Cao, Zouying Yang, Yifei Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

Safety alignment is indispensable for Large Language Models (LLMs) to defend threats from malicious instructions. However, recent researches reveal safety-aligned LLMs prone to reject benign queries due to the exaggerated safety issue, limiting their helpfulness. In this paper, we propose a Safety-Conscious Activation Steering (SCANS) method to mitigate the exaggerated safety concerns in aligned LLMs. First, SCANS extracts the refusal steering vectors within the activation space and utilizes vocabulary projection to anchor some specific safety-critical layers which influence model refusal behavior. Second, by tracking the hidden state transition, SCANS identifies the steering direction and steers the model behavior accordingly, achieving a balance between exaggerated safety and adequate safety. Experiments show that SCANS achieves new state-of-the-art performance on XSTest and OKTest benchmarks, without impairing their defense capability against harmful queries and maintaining almost unchanged model capability. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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The importance of mobile applications for companies' brand image: A study using structural equations 9th

The importance of mobile applications for companies' brand i...

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9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Mariano, Ari Melo Silva, Marcel Carneiro Mello, Tarcilla Mariano Santos, Maíra Rocha Department of Production Engineering University of Brasília Brazil Department of Computer Science University of Brasilia Brazil Postgraduate Program in Communication University of Brasília Brazil Center for Advanced Multidisciplinary Studies University of Brasilia Brazil

Because of the advancement of new technologies and the popularity of mobile devices, this study was designed to identify whether apps have a representative influence on companies' brand image. To fulfill this objective, descriptive research based on the structural equation model was carried out with the help of the statistical software Adanco. The study was conducted in Brasilia and applied in a virtual environment in the Google forms platform. The link was made available and disseminated to students of one university and through the WhatsApp and Facebook social networks, having 350 mobile device users as participants. The questionnaire was validated with α=0.81. The results of this research suggest that applications can influence 30.5% of a brand's image, thus raising the discussion that mobile applications will soon have equal or even greater importance than a website and social networks, tools that were once trends and are now essential requirements for organizations. Thus, for a company to be successful, it must not only be seen as a company with high performance and quality standards, but it must also represent a solid brand with a good reputation in the market and create and cultivate an image that connects emotionally with its consumer public. © 2022 The Authors. Published by Elsevier B.V.

关键词： Social networking (online)

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Spectral-temporal-spatial customization via modulating multimodal nonlinear pulse propagation

arXiv

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arXiv 2023年

作者： Qiu, Tong Cao, Honghao Liu, Kunzan Yu, Li-Yu Levy, Manuel Lendaro, Eva Wang, Fan You, Sixian Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Department of Brain and Cognitive Sciences Massachusetts Institute of Technology CambridgeMA United States

Multimode fibers (MMFs) have recently reemerged as attractive avenues for nonlinear effects due to their high-dimensional spatiotemporal nonlinear dynamics and scalability for high power. High-brightness MMF sources with effective control of the nonlinear processes would offer new possibilities for a wide range of applications from high-power fiber lasers, to bioimaging and chemical sensing, and to novel physics phenomena. Here we present a simple yet effective way of controlling nonlinear effects at high peak power levels: by leveraging not only the spatial but also the temporal degrees of freedom of the multimodal nonlinear pulse propagation in step-index MMFs using a programmable fiber shaper. This method represents the first method that enables modulation and optimization of multimodal nonlinear pulse propagation, achieving high tunability and broadband high peak power. Its potential as a nonlinear imaging source is further demonstrated by applying the MMF source to multiphoton microscopy, where widely tunable two-photon and three-photon imaging is achieved with adaptive optimization. These demonstrations highlight the effectiveness of directly modulating multimodal nonlinear pulse propagation to enhance the high-dimensional customization and optimize the high spectral brightness of MMF output. These advancements provide new possibilities for technology advances in nonlinear optics, bioimaging, spectroscopy, optical computing, and material processing. © 2023, CC BY.

关键词： Multimode fibers

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Challenges on Cloud Computing Migration Strategy for Music Industry: A Systematic Literature Review

Challenges on Cloud Computing Migration Strategy for Music I...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Hijir Della Wirasti Henki Seta Deden Witarsyah Hamonagan K Prabu Ayu Azzahro Bayu Hananto Faculty of Engineering Industry Telkom University Bandung Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Veteran Jakarta

Cloud computing has emerged as a transformative technology that offers numerous benefits to various industries, including the music industry. Cloud computing has revolutionized the way businesses operate and has had a significant impact on various industries, including the music industry Cloud computing, with its scalability, flexibility, and cost-effectiveness, presents an opportunity for the music industry to leverage technology to enhance its operations and meet the evolving demands of the digital era. This paper presents a systematic literature review on cloud computing migration strategies specifically tailored for the music industry. The review aims to identify existing research, frameworks, and best practices related to cloud migration in the music industry, as well as highlight the challenges and opportunities associated with such migrations. Through an analysis of relevant literature, this study provides valuable insights to assist music industry stakeholders in developing effective cloud migration strategies.

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FTG: Score-based black-box watermarking by fragile trigger generation for deep model integrity verification

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Journal of Information and Intelligence 2024年第1期2卷 28-41页

作者： Heng Yin Zhaoxia Yin Zhenzhe Gao Hang Su Xinpeng Zhang Bin Luo Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui UniversityHefei 230000China Shanghai key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 200241China School of Communication and Electronic Engineering East China Normal UniversityShanghai 200241China Department of Computer Science and Technology Tsinghua UniversityBeijing 100000China School of Computer Science and Technology Fudan UniversityShanghai 200241China

Deep neural networks(DNNs)are widely used in real-world applications,thanks to their exceptional performance in image ***,their vulnerability to attacks,such as Trojan and data poison,can compromise the integrity and stability of DNN ***,it is crucial to verify the integrity of DNN models to ensure their *** research on model watermarking for integrity detection has encountered the issue of overexposure of model parameters during embedding and extraction of the *** address this problem,we propose a novel score-based black-box DNN fragile watermarking framework called fragile trigger generation(FTG).The FTG framework only requires the prediction probability distribution of the final output of the classifier during the watermarking *** generates different fragile samples as the trigger,based on the classification prediction probability of the target classifier and a specified prediction probability mask to watermark *** prediction probability masks can promote the generation of fragile samples in corresponding distribution *** whole watermarking process does not affect the performance of the target *** verifying the watermarking information,the FTG only needs to compare the prediction results of the model on the samples with the previous *** a result,the required model parameter information is reduced,and the FTG only needs a few samples to detect slight modifications in the *** results demonstrate the effectiveness of our proposed method and show its superiority over related *** FTG framework provides a robust solution for verifying the integrity of DNN models,and its effectiveness in detecting slight modifications makes it a valuable tool for ensuring the security and stability of DNN applications.

关键词： Neural network Sensitive sample Fragile watermarking Model integrity Fragile trigger

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Churn Prediction in Financial Risk Management using Deep Learning Techniques 2

Churn Prediction in Financial Risk Management using Deep Lea...

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2nd IEEE International Conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication engineering, ICATIECE 2022

作者： Kumar, V Sunil Sowmyashree, S. Pareek, Piyush Kumar Khanna, Ashish Costa De Albuquerque, Victor Hugo Gupta, Deepak Nitte Meenakshi Institute of Technology Department of Artificial Intelligence & Machine Learning Bengaluru India Computer Science & Engineering East West Institute of Technology Bengaluru India Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Cearά Fortaleza Brazil Maharaja Agrasen Institute of Technology GGSIPU CSE Dept India Federal University of Cearά Department of Teleinformatics Engineering Brazil

ISBN: (纸本)9781665493963

It is essential to develop an efficient Client Relationship Model in order to make use of the estimations about customer turnover (CRM). Finding and breaking down the facts surrounding the business information understanding is necessary for client produce prediction, which should be made possible effectively by altering the strategies used for business insight. The tools that are provided by company insight allow for the historical, current, and prospective perspectives of business activity to be anticipated and dissected. It is possible to deal with it in an efficient way by providing the information mining approaches that choose the data from the created informative index that is the most helpful. Fundamental leadership should be possible to achieve in a fruitful way if one has this information. The actions that consumers have taken in the recent past are going to be analyzed, and an accurate forecast is going to be formed about those customers who are likely going to get unhappy in the near future based on the results of that prediction. The problem is that deciding on a certain period to investigate the client's activities and also establishing on a specific day and age for each of the clients won't be appropriate6. This is due to the fact that the problem is caused by the fact that deciding on a certain period to investigate the client's activities will take too long. The challenge lies just in this aspect. How to decide on a certain amount of time to spend researching the activities of the customer. For instance, when planning a model, 100 customers are used, 70 of those customers are considered 'active,' which indicates that they are still conducting business with the organisation, and the remaining 30 customers are considered 'agitate,' which indicates that they have severed their ties with the organisation. The primary purpose of the work that has been suggested is to carry out exploratory research and management as a multicriteria basic leadership issue, a

关键词： Forecasting

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A Preliminary Study on the Collaborative Playing Piano Automatic with Deep Learning

A Preliminary Study on the Collaborative Playing Piano Autom...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Varinya Phanichraksaphong Karuna Yampray Department of Electronic Engineering International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan College of Creative Design and Entertainment Technology Dhurakij Pundit University Bangkok Thailand

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

A great number of deep learning-based models have been recently proposed for automatic piano classification. In this paper, we describe our contribution to the challenge of automatic piano classification when the performer performs at the concert or stage. Among these models in deep learning, we use init-1D-WaveNet and init-2D-MLNet for comparison the accuracy in the piano beginning level of the Christmas song (Jingle bells). Our experimental results show that the assessment using the init-2D-MLNet still achieve high accuracy of 87.5%.

关键词： Deep learning Accuracy Instruments Collaboration Consumer electronics

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Statistical Consequences of Dueling Bandits

arXiv

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arXiv 2021年

作者： Saxena, Nayan Chen, Pan Liu, Emmy Department of Statistical Sciences University of Toronto Department of Computer Science University of Toronto Department of Computer Science Cognitive Science Program University of Toronto

Multi-Armed-Bandit frameworks have often been used by researchers to assess educational interventions, however, recent work has shown that it is more beneficial for a student to provide qualitative feedback through preference elicitation between different alternatives, making a dueling bandits framework more appropriate. In this paper, we explore the statistical quality of data under this framework by comparing traditional uniform sampling to a dueling bandit algorithm and find that dueling bandit algorithms perform well at cumulative regret minimisation, but lead to inflated Type-I error rates and reduced power under certain circumstances. Through these results we provide insight into the challenges and opportunities in using dueling bandit algorithms to run adaptive experiments. © 2021, CC BY.

关键词： Sampling

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