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arXiv 2022年

作者： Yao, Yuan Dong, Bowen Zhang, Ao Zhang, Zhengyan Xie, Ruobing Liu, Zhiyuan Lin, Leyu Sun, Maosong Wang, Jianyong Dept. of Comp. Sci. & Tech. Institute for AI Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology China Department of Computer Science National University of Singapore Singapore WeChat Search Application Department Tencent China Institute for Artificial Intelligence Tsinghua University Beijing China Institute Guo Qiang Tsinghua University Beijing China International Innovation Center Tsinghua University Shanghai China

Recent works have shown promising results of prompt tuning in stimulating pre-trained language models (PLMs) for natural language processing (NLP) tasks. However, to the best of our knowledge, existing works focus on prompt-tuning generative PLMs that are pre-trained to generate target tokens, such as BERT (Devlin et al., 2019). It is still unknown whether and how discriminative PLMs, e.g., ELECTRA (Clark et al., 2020), can be effectively prompt-tuned. In this work, we present DPT, the first prompt tuning framework for discriminative PLMs, which reformulates NLP tasks into a discriminative language modeling problem. Comprehensive experiments on text classification and question answering show that, compared with vanilla fine-tuning, DPT achieves significantly higher performance, and also prevents the unstable problem in tuning large PLMs in both full-set and low-resource settings. The source code and experiment details of this paper can be obtained from https://***/thunlp/DPT. Copyright © 2022, The Authors. All rights reserved.

关键词： Natural language processing systems

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Does Word2Vec encode human perception of similarityƒ A study in Bangla

Does Word2Vec encode human perception of similarityƒ A stud...

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2019 International Conference on Bangla Speech and Language Processing, ICBSLP 2019

作者： Sinha, Manjira Dutta, Rakesh Dasgupta, Tirthankar IIT Kharagpur Center for Education Technology Kharagpur India University of North Bengal Dept. of Computer Science and Application Siliguri India Tata Consultancy Services Innovation Lab Kolkata India

ISBN: (纸本)9781728152417

The quest to understand how language and concepts are organized in human mind is a neverending pursuit undertaken by researchers in computational psycholinguistics;simultaneously, on the other hand, researchers have tried to quantitatively model the semantic space from written corpora and discourses through different computational approaches-while both of these interacts with each other in-terms of understanding human processing through computational linguistics and enhancing NLP methods from the insights, it has seldom been systematically studied if the two corroborates each other. In this paper, we have explored how and if the standard word embedding based semantic representation models represent the human mental lexicon. Towards that, We have conducted a semantic priming experiment to capture the psycholinguistics aspects and compared the results with a distributional word-embedding model: Bangla word2Vec. Analysis of reaction time indicates that corpus-based semantic similarity measures do not reflect the true nature of mental representation and processing of words. To the best of our knowledge this is first of a kind study in any language especially Bangla. © 2019 IEEE.

关键词： Embeddings

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Comparative Study Of Efficient Data Hiding Techniques

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IOP Conference Series: Materials Science and Engineering 2021年第1期1022卷

作者： Lalan kumar Deepanjali Mishra Ayush Kumar Amit Kumar Ashish Bajpai Asst. Professor Dept. of Master of Computer Application G.L. Bajaj Institute of Technology and Management Gr.Noida UP India Scholar Dept. of Master of Computer Application G.L. Bajaj Institute of Technology and Management Gr.Noida UP India Asst.Professor Dept. of Master of Computer Application KIET Group of Institutions Ghaziabad UP India Asst.Professor Dept. of Computer Science KIET Group of Institutions Ghaziabad UP India

Data security is one of the fundamental concerns when it comes to modern networking and information sharing as any breach or data loss can end up causing major losses in terms of credibility, personal data and/or law suites. This paper studies data encryption and decryption techniques using algorithms like DES algorithm, 3 DES algorithm, AES algorithm and RSA algorithm. Cryptography was introduced for data security while transmitting data. However, only cryptography cannot give a robust security approach; as a result, a disorganized message can still be snooped [9]. This leads to a desire for information security. There are several techniques available, among those have taken a few of them and will review them considering cryptography measures. We will analyse the algorithm mentioned above, and try to find out better among them.

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Formulating an MVC Framework for Web Development in Java 2

Formulating an MVC Framework for Web Development in Java

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2nd International Conference on Trends in Electronics and Informatics, ICOEI 2018

作者： Singh, Aditya Chawla, Piyush Singh, Karan Singh, Ashutosh Kumar National Institute of Technology Dept. of Computer Application Kurukshetra India

ISBN: (纸本)9781538635704

The Rigidity of the traditional approach for web development made it difficult to maintain and extend the web applications. The emergence of Model, View and Controller design pattern changed this scenario. Through the research of Struts 2 framework and Spring MVC framework, with some related technologies, this paper aims at designing a lightweight MVC framework for facilitating the development process of small to medium size web applications. © 2018 IEEE.

关键词： Struts

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Active feedback cooling of a SiN membrane resonator by electrostatic actuation

arXiv

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arXiv 2021年

作者： Borrielli, Antonio Bonaldi, Michele Serra, Enrico Sarro, Pasqualina Maria Morana, Bruno Institute of Materials for Electronics and Magnetism IMEM-CNR Trento unit c/o Fondazione Bruno Kessler Via alla Cascata 56/C Povo TrentoIT-38123 Italy Dept. of Microelectronics and Computer Engineering ECTM DIMES Delft University of Technology Feldmanweg 17 Delft2628 CT Netherlands Trento Institute for Fundamental Physics and Application Povo Trento38123 Italy

Feedback-based control techniques are useful tools in precision measurements as they allow to actively shape the mechanical response of high quality factor oscillators used in force detection measurements. In this paper we implement a feedback technique on a high-stress low-loss SiN membrane resonator, exploiting the charges trapped on the dielectric membrane. A properly delayed feedback force (dissipative feedback) enables the narrowing of the thermomechanical displacement variance in a similar manner to the cooling of the normal mechanical mode down to an effective temperature Te f f. In the experiment here reported we started from room temperature and gradually increasing the feedback gain we were able to cool down the first normal mode of the resonator to a minimum temperature of about 124mK. This limit is imposed by our experimental set-up and in particular by the the injection of the read-out noise into the feedback. We discuss the implementation details and possible improvements to the technique. Copyright © 2021, The Authors. All rights reserved.

关键词： Resonators

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Secure Analysis of Social Media Data

Secure Analysis of Social Media Data

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2019 International Conference on Automation, Computational and technology Management, ICACTM 2019

作者： Siddaramappa, Hareesha Katiganere Maradithaya, Sumana Kumar, Sampath Department of Computer Application Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka India Department of ISE MSRIT Bangalore Karnataka India Dept. of ECE Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka India

ISBN: (纸本)9781538680100

Confidentiality of the social media data during analysis is a major concern. Several real evidences show how the privacy and security of the data is compromised. One of the essential processes with social media data is to find the shortest paths between selected pair of nodes. This paper proposes a technique to modify the original data before analysis. The algorithm calculates shortest paths (data utility) between target nodes and then classifies edges into partially visited, all-visited and unvisited edges. Each category of edges is then perturbed using a dynamic variable value that is bound to satisfy specific constraints such that the shortest path as well as the shortest paths lengths, between the target node pairs remains the same. This paper proposes an approach to preserve the privacy of the weights and also generates an accurate length of the shortest path. It is also observed that the shortest path lengths between any target pairs of nodes are retained. The output is in the form of graphs, that shows that the proposed perturbation strategy perturbs the sensitive edge weights up to a maximum 72%, while keeping the difference in shortest path lengths minimum (up to 3%). It is hence demonstrated that along with preserving the sensitive information by perturbing the edge weights, the data utility is preserved i.e. the shortest path lengths are kept as near as potential to the original ones. © 2019 IEEE.

关键词： Perturbation techniques

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Deep learning-based multi-brain capsule network for Next-Gen Clinical Emotion recognition using EEG signals

Neuroscience Informatics

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Neuroscience Informatics 2025年第2期5卷 100203-100203页

作者： Dahiya, Ritu G, Mamatha Jawale, Shila Sumol Das, Santanu Choudhary, Sagar Rathod, Vinod Motiram Rajput, Bhawna Janghel Dept. of Chemistry Chhotu Ram Arya College Haryana Sonepat India Department of Management Studies Sri Siddhartha Institute of Business Management Karnataka Tumkur India Department of Computer Engineering Somaiya School of Engineering (formerly K J Somaiya College of Engineering) Somaiya Vidyavihar University Vidyavihar Maharashtra Mumbai India Department of Biotechnology Seshadripuram First Grade College Yelahanka New Town Bangalore India Department of Mathematics Bioinformatics and Computer Application MANIT Madhya Pradesh Bhopal India Bharati Vidyapeeth Deemed University Department of Engineering and Technology Maharashtra Navi Mumbai India Department of Computer Science and Engineering Rungta College of Engineering and Technology Chhattisgarh Bhilai India

Deep learning techniques are crucial for next-generation clinical applications, particularly in Next-Gen Clinical Emotion recognition. To enhance classification accuracy, we propose an Attention mechanism based Capsule Network Model (At-CapNet) for Multi-Brain Region. EEG-tNIRS signals were collected using Next-Gen Clinical Emotion-inducing visual stimuli to construct the TYUT3.0 dataset, from which EEG and tNIRS features were extracted and mapped into matrices. A multi-brain region attention mechanism was applied to integrate EEG and tNIRS features, assigning different weights to features from distinct brain regions to obtain high-quality primary capsules. Additionally, a capsule network module was introduced to optimize the number of capsules entering the dynamic routing mechanism, improving computational efficiency. Experimental validation on the TYUT3.0 Next-Gen Clinical Emotion dataset demonstrates that integrating EEG and tNIRS improves recognition accuracy by 1.53% and 14.35% compared to single-modality signals. Moreover, the At-CapNet model achieves an average accuracy improvement of 4.98% over the original CapsNet model and outperforms existing CapsNet-based Next-Gen Clinical Emotion recognition models by 1% to 5%. This research contributes to the advancement of non-invasive neurotechnology for precise Next-Gen Clinical Emotion recognition, with potential implications for next-generation clinical diagnostics and interventions. © 2025 The Author(s)

关键词： Capsule network Clinical emotion recognition Deep learning EEG Transactional NIRS

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A Glimpse on Key applications of Smart City under M2M Communication

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IOP Conference Series: Materials Science and Engineering 2021年第1期1022卷

作者： Sonam Kaushik Gaurav Aggarwal Sanjay Tejasvee Asst. Professor/Research Scholar Dept. of Engineering & Technology Gurugram Univ. Gurugram -122001-India Professor Dept. of Computer Science JIMS Bahadurgarh-124507-India Asst. Professor Computer Application Dept. Govt. Engineering College Bikaner 334004-India

In India, It is very necessary to make normal cities as smart cities near future. So, Develop a smart city is one of the most recent fields in today's digital era to researches. Machine to Machine (M2M ) communication is the latest innovative-fangled type of communiqué that enables full automation with the help of integrated applications to make a normal city to a smart city. Many devices are connected in a smart city to monitoring many tasks and it is a very challenging task to integrate and manage these connected devices. Interconnection of several devices and machines using the internet to form an M2M Area Network (M2MAN) provides controlling and monitoring smart applications like smart-metering, weather, environment, home, air quality, water supply with quality management, power supply with bill monitoring, traffic, and healthcare, etc. under M2M communication and integrated single level umbrella structured applications. Out of several M2M monitoring and controlling applications towards smart cities, few key applications are presented in this paper with their basic approach, workflow, and concerning issues and used technologies for the implementation with the brief growth analysis.

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Investigation on agricultural land selection using hybrid fuzzy logic system ∗

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Scalable Computing 2020年第4期21卷 569-582页

作者： Sengan, Sudhakar Vijayakumar, V. Krishnamoorthy, Sujatha Gunasekaran, S. Kumar, C. Sathiya Palani, Saravanan Subramaniyaswamy, V. Department of CSE Sree Sakthi Engineering College Coimbatore641 104 India School of Computer Science and Engineering University of New South Wales Sydney Australia Department of Computer Science Wenzhou Kean University Wenzhou Zhejing China Dept. of Computer Application King College of Arts & Science Tiruchengode637 215 India Department of Computational Intelligence Vellore Institute of Technology Vellore India School of Computing SASTRA Deemed University Thanjavur India

For maintaining the horticultural generation, Land Selection Investigation (LSI) is essential. Though incorporates estimation of the criteria assortment from the soil, territory to financial, market, and foundation, and these components are considerably enigmatically characterized and described by their inherent ambiguity. Multi-criteria basic leadership systems like positioning, rating, and so on are utilized for reasonableness examination. Master learning and judgment by leaders at different levels is integrated into this process. In the field of farming sciences, the Fuzzy Logic (FL) strategy has been effectively used to take care of numerous issues. Fuzzy with AHP is a Hybrid Fuzzy Logic (HFL) methodology. The policies Analytic Hierarchy Process (AHP), Fuzzy Numbers, Fuzzy Degree Investigation, Alpha Cut, and Lambda capacity are associated with it. As expressed, the procedure of necessary leadership includes a scope of criteria and a considerable measure of master learning and decisions. The components result from impacts extraordinarily. The capacity of three methods to demonstrate the affectability of the necessary leadership procedure is researched. Alpha cut and lambda esteem give and encourage considerable affectability investigation. All techniques are actualized to examine the reasonableness of the crop in the Indian nation. Test results when performed on Various Datasets, demonstrate that the proposed procedure removes more highlights just as gives more exactness when contrasted with existing techniques. © 2020 SCPE.

关键词： Fuzzy logic

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Development of GUI for text-to-speech recognition using natural language processing 2

Development of GUI for text-to-speech recognition using natu...

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2nd International Conference on Electronics, Materials Engineering and Nano-technology, IEMENTech 2018

作者： Mukherjee, Partha Santra, Soumen Bhowmick, Subhajit Paul, Ananya Chatterjee, Pubali Deyasi, Arpan Dept. of Computer Application Techno India College of Technology Kolkata India Dept. of Electronics and Comm. Engg. RCC Institute of Information Technology Kolkata India

ISBN: (纸本)9781538655498

N atural language processing is a widely used technique by which systems can understand the instructions for manipulating text or speech. In the present paper, a Text-to-speech synthesizer is developed that converts text into spoken word, by analysing and processing it using Natural Language Processing (NLP) and then using Digital Signal Processing (DSP) technology to convert this processed text into synthesized speech representation of the text. Here we developed a useful text-to-speech synthesizer in the form of a simple application that converts inputted text into synthesized speech and reads out to the user which can then be saved as an mp3 file. © 2018 IEEE.

关键词： Digital signal processing

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