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27th International Conference on Pattern Recognition, ICPR 2024

作者： Park, Nokyung Chae, Daewon Shim, Jeongyong Kim, Sangpil Kim, Eun-Sol Kim, Jinkyu Department of Computer Science and Engineering Korea University Seoul Korea Republic of Department of Artificial Intelligence Korea University Seoul Korea Republic of Department of Artificial Intelligence Application Hanyang University Seoul Korea Republic of Department of Computer Science Hanyang University Seoul Korea Republic of

ISBN: (纸本)9783031781919

Learning domain-invariant visual representations is important to train a model that can generalize well to unseen target task domains. Recent works demonstrate that text descriptions contain high-level class-discriminative information and such auxiliary semantic cues can be used as effective pivot embedding for domain generalization problems. However, they use pivot embedding in a global manner (i.e., aligning an image embedding with sentence-level text embedding), which does not fully utilize the semantic cues of given text description. In this work, we advocate for the use of local alignment between image regions and corresponding textual descriptions to get domain-invariant features. To this end, we first represent image and text inputs as graphs. We then cluster nodes within these graphs and match the graph-based image node features to the nodes of textual graphs. This matching process is conducted both globally and locally, tightly aligning visual and textual semantic sub-structures. We experiment with large-scale public datasets, such as CUB-DG and DomainBed, and our model achieves matched or better state-of-the-art performance on these datasets. The code is available at: https://***/noparkee/Graph-Clustering-based-DG. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantics

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Cyber-Crime and Digital Forensics: Challenges Resolution

Cyber-Crime and Digital Forensics: Challenges Resolution

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Singh, Arpita Singh, Nilu Singh, Sanjay K. Nayak, Sandeep K. AIIT Amity University Lucknow India Koneru Lakshmaiah Education Foundation Vaddeswaram Department of Computer Science and Engineering Andhra Pradesh Guntur India Integral University Department of Computer Science & Application Lucknow India

ISBN: (纸本)9798350348217

In this technology-friendly era, technology and science govern the world so much. No matter what sector it is, here or somewhere all sectors depend on technology. This technical dependency helps all sectors to grow fast but also invites criminals to take advantage. Criminal cases which are based on technology are getting to hike drastically day by day. Cybercrime is now these days one of the key problems of mankind. There are so many organizations from different sectors which are facing down because of cyber-crime, so many individuals/private or governments facing problems due to cyber-crimes. Digital/computer forensics is a new pattern to find cyber-crimes. Digital forensic science requires new forensic tools and technology to overcome such kinds of crimes. In this paper, the authors discussed different scenarios of cybercrime and the crime rate of different states of India. In addition, the paper is focused on some preventive measures to reduce the risk of cybercrime and will also analyze statistical data provided by government organizations and forecast cybercrime for the next few years. © 2023 IEEE.

关键词： Cybersecurity

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Code-Mixed Sentiment Corpus of Customer Reviews in Malayalam and English for Enhanced Local Market Analysis in India

Code-Mixed Sentiment Corpus of Customer Reviews in Malayalam...

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Sree S Bhagya Hrishiraj G L NaderaBeevi S Dept. of Computer Application TKM College of Engineering Kollam APJ Abdul Kalam Technological University Kerala India Dept. of Computer Application TKM College of Engineering Kallam Kerala India

The popularity of online shopping has boosted the volume of customer reviews, which is crucial for business growth and decision-making as they influence consumers' purchasing decisions. Indians frequently engage in code-mixing, a social media practice where multilingual users publish comments that give information about consumer preferences, cultural relevance, and product or service improvement. Businesses with an Indian market emphasis should consider this factor to improve the consumer experience. Indian languages often face resource constraints, making it difficult to create precise language models and carry out operations like sentiment analysis, spam filtering, offensive text recognition, etc. Through this work, we draw the researcher's attention to the relevance of processing code-mixed customer reviews for e-commerce sites in linguistically diverse regions like India and how it helps to serve customers better, improve goods and services, and stay competitive in a globalised and multicultural market. This work aims to expand Malayalam-English (Manglish) code-mixed literature in the commercial domain by constructing a sentiment corpus featuring customer reviews in Manglish related to commercial products annotated by voluntary annotators. The performance of different machine learning (ML) and deep learning (DL) models for the sentiment identification task is then assessed using the new corpus, and a comprehensive analysis of the results is also presented.

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Analysis of Nutritional Status of Children in Karnataka Based on Machine Learning Techniques Using Indian Demographic and Health Survey Data 1

Analysis of Nutritional Status of Children in Karnataka Base...

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1st International Conference on Computational Intelligence for Information, Security and Communication applications, CIISCA 2023

作者： Sharma, Anjali Rohitaksha, K. JSS Academy of Technical Education Bangalore Dept. of Computer Science and Engineering Karnataka Bengaluru India JSS Academy of Technical Education Bangalore Dept. of Master of Computer Application Karnataka Bengaluru India

ISBN: (纸本)9798350339727

Malnutrition is caused when an individual gets very little or too many nutrients, resulting in health problems. In particular, 'a deficit, excess, or imbalance of energy, protein, and other nutrients' negatively impacts the body's tissues and form. Malnutrition significantly contributes to infant mortality rates in developing nations, and India, as a developing country, experiences challenges associated with malnutrition in children under the age of five. The primary objective of this study is to analyze the factors influencing the nutritional status of under-five children in Karnataka, India, using data from the 2015-2016 Indian Demographic and Health Survey (IDHS). Logistic regression (LR), k-nearest neighbors (k-NN), support vector machines (SVM), random forest (RF), and Naïve Bayes (NB) are five prominent techniques in machine learning that are being utilized to successfully predict the factors affecting children's nutritional status. Body Mass Index (BMI), Height for Age Z score (HAZ), Weight for Age Z score (WAZ), and Weight for Height Z score (WHZ) are the main factors considered. Additionally, accuracy is used to do a systematic evaluation of the algorithms. Finally, the key factor impacting nutritional status in children was discovered to be HAZ based on accuracy, and the Random Forest produced the greatest findings and it was moderately superior to any other ML algorithms applied in this analysis. © 2023 IEEE.

关键词： Support vector machines

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A Multimodal Fusion and Ensemble Approach for Robust Fake News Detection through Deep Learning, Reinforcement Learning, and Using Blockchain to Enhance Security and Authorization

Recent Advances in Computer Science and Communications

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Recent Advances in computer Science and Communications 2025年第2期18卷

作者： Kumar, Vivek Satveer Ahmad, Waseem Kumar, Satendra Department of Computer Application Quantum University U.K Roorkee India Department of Computer Science & Engineering Meerut Insitute of Engineering and Technology U.P Meerut India

Background: computer science significantly influences modern culture, especially with the rapid breakthroughs and technology in social media networking. Social media platforms have become significant channels for sharing and exchanging daily news and information on many issues in the current digital environment, which is known for its massive data collection and transmission capabilities. While there are many benefits to this environment, there are also many false reports and information that deceive readers and users into believing they are receiving correct information. Objective: Nowadays, all users use social media to obtain news content, but sometimes some malicious users tamper with real news and then spread fake news, which may reduce the reputation of social media. Therefore, many existing models have been introduced to detect fake news, but these models are based on traditional machine learning algorithms, such as decision tree (DT), multilayer perceptron (MLP), random forest (RF), etc. These models Lack of performance, security, and authorization. Our proposed model can solve existing model problems using reinforcement learning and blockchain technology. Methods: In this research paper, we explain a new way to identify fake news. This new approach, combined with policy-based heuristic reinforcement learning (PHRL), where the model dynamically adjusts through iterative learning, is the key innovation and gradually improves classification accuracy. The same as our smart contract authorization method, which enhances the authenticity of content posted safely by authorized users and improves the transparency and accountability of information. Results: Our model was tested on real-time information collected from various sources with 70% accuracy and valid authentication. Conclusion: Our proposed model produced better results with a Mean Absolute Error (MAE) of 0.0811 and Root Mean Squared Error (RMSE) of 0.2847, both significantly lower values. Our proposed mode

关键词： Deep reinforcement learning

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Time-stretching and genetic zooms in OutGene: Detecting Undefined Network Attacks 5

Time-stretching and genetic zooms in OutGene: Detecting Unde...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Shekhawat, Jyoti Khurana, Rashmi Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350398267

The study introduces OutGene, a method for detecting malicious behaviour in real time without prior knowledge of assaults or training data. OutGene gathers hosts with comparable behaviour via clustering. We offer the idea of genetic zoom, which involves utilizing a genetic algorithm which select the attributes that is more pertinent to characterize cluster in order to aid human analysts in locating malevolent clusters. Attacks carried out slowly or below thresholds are frequently successful in evading machine learning-based attack detection. We offer the idea of time stretching as a way to identify such stealth attacks. The goal is to discover assaults regardless of how quickly they are carried out by analyzing the stream of events over various time frames. We evaluated OutGene experimentally using data sets currently publicly available and data sets collected at critical military installations. Both genetic zoom and temporal stretching achieved high recall and precision scores, indicating that both are effective. © 2022 IEEE.

关键词： Intrusion detection

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Impact Of Social Media Apps On Public Health: An Overview with Analysis

Impact Of Social Media Apps On Public Health: An Overview wi...

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2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

作者： Rawat, Vandana Amoli, Mohit Ruwari, Shalini Rajput, Suraiya Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Application Dehradun India Glocal University Department of Business and Commerce Saharanpur India

ISBN: (纸本)9798350323917

Social media has grown to be a significant element of modern life and has both beneficial and harmful effects on people's health. Several parents and activists have recently voiced their worries about the potentially negative influence of social media use. Some research indicates that using social media would use very well result in poor mental health outcomes including suicidality, loneliness, and a significant decrease in empathy. Other trials either didn't establish any risk or suggested that some people might be benefited from social media. Amongst the consequences of high usage of Social media, mental illness, panic disorder, and diminished tolerance is being increased. According to the findings of different age groups concluded that it is giving several advantages but it is harmful also so in this research, an analysis is being done of social media usage in several generations. However, unclear registration revealed lifelong suicidal ideation, demonstrating that this particular posture may be a sign of more serious issues. This research focuses on how social media affects people's life. © 2023 IEEE.

关键词： Diseases

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Implementing a Smart Monitoring System with Wireless Sensor and Actuator Networks 11

Implementing a Smart Monitoring System with Wireless Sensor ...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Sharma, Garima Tanisha Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9781665487320

In this article, we investigate how to build an intelligent network unit over a wireless network. To do so, we make use of a resilient routing strategy made available by the Protocol for power (RPL), the definition of which is currently being considered. Our architecture is based on a simple binary web service execution of the RE presentational State Transfer (REST) paradigm and an executing strategy in which every node makes a collection of components (such as atmospheric sensors) available to parties who are concerned with them. We present an evaluation of RPL by means of an experimental inquiry, with the focus being on how well it creates the routing structure to highlight how the efficiency of routing is influenced by the fundamental properties of RPL. © 2022 IEEE.

关键词： Web services

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Construction of PCOS Prediction Model based on BP Neural Network 6

Construction of PCOS Prediction Model based on BP Neural Net...

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Hu, Xianqing Yadav, Amit Khan, Asif Sah, Abhishek Pratap Azam, Sami School of Computer and Software Chengdu Neusoft University Chengdu China Faculty of Science and Technology Charles Darwin University NT Australia Department of Computer Application Integral University Lucknow India School of Management Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798331522667

Polycystic ovary syndrome (PCOS), a common endocrine-metabolic disorder affecting about 10-13% of women during reproductive age worldwide, often leads to irregular menstruation, infertility, obesity, and long-term health risks such as diabetes and cardiovascular disease. In this paper, clinical data from PCOS patients and healthy control group were collected from ten hospitals containing 37 key indicators such as age, weight, BMI, menstrual cycle, etc. BP (Back Propagation) Neural Network prediction models were constructed and compared using the collected data and the cross-validation method was used for parameter tuning. It was found that BP Neural Network performed particularly well on the test set, and both demonstrated high prediction accuracy and generalization ability which provided strong evidence for the early identification and early valuable intervention opportunities for PCOS patients. © 2025 IEEE.

关键词： Prediction models

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Complete Review of IoT Solutions for Sustainably Agricultural Production 11

Complete Review of IoT Solutions for Sustainably Agricultura...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Yadav, Aarti Kaur, Amandeep Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9781665487320

That both type and amount of food demanded have increased, necessitating farming technology through expansion. Adopted a new strategy is booming thanks to social media and Items (IoT), a prospective technique. Universities and climate scientists are creating Smart goods and resolve a range of agronomic concerns. This research offers a thorough literature assessment by looking at IIoT and their present use in a wide range of industries. The whole review conducted for this study was predicated on a question of research published in recognized papers over the last ten years. A broad range of articles were carefully chosen or sorted among courses. Its report's main goal will be to compile every pertinent data about IoT crop monitoring, electronic systems, tcp / ip, & public types. Secondly, it is dealing with major issues and obstacles that are now explored there in agricultural industry. © 2022 IEEE.

关键词： Data Analytics

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