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Social Media Mining For Suicidal Ideation 4

Social Media Mining For Suicidal Ideation

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Satya, Siddhant Jindal, Rajni Delhi Technological University Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9781665474368

Recent exponential rise of social media impact has resulted in significant changes in how people conduct their lives. Sharing one's ideas, thoughts, and feelings on a social platform like Facebook, Twitter and Reddit reveal a lot about a person's mental state, which is referred to as online behavior. Online behavior has been the subject of several studies and evaluations. Nowadays, people have begun to express their sentiments more on social media than in person with the introduction of social networking sites. this online accumulating data that users leave behind may be exploited to glean insights about their actions and mental state using machine learning. Different machine learning approaches have been employed, examined, and evaluated for suicidal inclination identification in this study to establish that Machine Learning Algorithms can properly identify a Social Media user's dwelling Suicidal Tendency. © 2022 IEEE.

关键词： Learning algorithms

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Aadhaar Secure: An Authentication System for Aadhaar Base Citizen Services using Blockchain 4

Aadhaar Secure: An Authentication System for Aadhaar Base Ci...

引用

4th international conference on Cognitive computing and Information Processing, CCIP 2022

作者： Veena, N. thejaswini, S. Siddaganga Institute of Technology Dept. of Computer Science Tumakuru India

ISBN: (数字)9781665456487

ISBN: (纸本)9781665456487

In the past decades, people had to carry a bunch of documents for acquiring citizen beneficiary services such as opening a bank account, issue of a new sim card, new gas connection, Pradhan Mantri Jan Dhan Yojana etc. In this digital era, Aadhaar is acting as the driving force to gain all citizen services. Unfortunately, lot of security breaches have been occurred on compromising the Aadhaar details which is stored in the database. Providing security to Aadhaar data and mitigate the misuse of other's Aadhaar data to gain citizen services by unauthenticated users is a main concern. Hence, a secure and authenticated system is required to store and use the Aadhaar details securely by authenticated user. In this paper, we are proposing a secure authenticated system which uses IPFS to store finger prints of the customers and blockchain is used to store the Aadhaar details of the registered citizens. In this system, the biometric is integrated with blockchain to secure Aadhaar details and authenticate the customers before providing any citizen services. the system also generates the Aadhaar card after passing redundancy check for customers who do not have Aadhaar card to access the citizen services. the system is tested and verified for multiple citizen services. © 2022 IEEE.

关键词： Smart contract

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Machine Learning Techniques for Intrusion Detection in Smart Healthcare Systems: A Comparative Analysis 4

Machine Learning Techniques for Intrusion Detection in Smart...

引用

4th international conference on Smart Sensors and Application, ICSSA 2022

作者： Basharat, Asma Mohamad, Mohd. Murtadha Bin Khan, Attiya Department of Computer Science Lahore Pakistan Universiti Teknologi Malaysia School of Computing Johor Bahru Malaysia Kinnaird College for Women Department of Computer Science Lahore Pakistan

ISBN: (数字)9781665499811

ISBN: (纸本)9781665499811

the Internet of things (IoT) has infiltrated nearly every aspect of life. Smart healthcare systems (SHS) are one of the most important sectors where IoT solutions are frequently deployed. With the usage of wearable devices, IoT-based smart healthcare systems have considerably improved the benefits of the healthcare industry. By combining IoT sensors with health monitoring equipment, smart healthcare minimises hospitalisation expenses and enables timely treatment for a variety of medical issues. Nonetheless, SHS is very vulnerable to a wide range of security breaches, including data leakage, data tampering, and forging. In this research, we present a comparative analysis of various machine learning-based techniques for successfully detecting intrusion in SHS. We use UNSW-NB15 network intrusion benchmark dataset to evaluate our proposed model. the evaluation results show that the AdaBoost classifier can detect network intrusion with an accuracy of 95%. © 2022 IEEE.

关键词： Intrusion detection

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Design of Energy Optimization Algorithm for Virtual Machine Scheduling in Cloud computing 4th

Design of Energy Optimization Algorithm for Virtual Machine ...

引用

4th international conference on data, Engineering, and Applications, IDEA 2022

作者： Shukla, Ram Narayan Chaturvedi, Anoop Kumar Department Computer Science and Engineering LNCT University Madhya Pradesh Bhopal India

ISBN: (纸本)9789819724505

Users can access and, in some cases, pay for a variety of resources, including software and server time, in a virtual setting thanks to cloud computing. data and storage are available on demand. the cloud's position between the user and the server also reduces wait times. As a result of the increased load, the servers are using more power than usual. Customers are free to use any vendor’s cloud services, including those offered by Google, Amazon, and others. Cloud services have been a huge boon to small enterprises. A large number of users access the resources and respond appropriately to requests. In this paper is proposed an Energy Optimization in Cloud computing technique (ECCO) for proper load distribution of users’ requests. By balancing and scheduling network traffic, we can alleviate strain on individual servers and speed up overall network operations. the ECCO technique, which has been presented, is a combination one that works to continuously assess the server's load while getting any server load higher than what it transfers to the other cloud server in order to balance the additional traffic. the proposed method is to increase energy utilization or decrease energy consumption on servers. When compared to DENS, Random, and Round Robin, the proposed ECCO scheme outperforms them all. the growing number of users places a greater strain on the cloud infrastructure. the relationship between the cloud provider and the cloud user is significantly impacted by the services. the performance of the service is degraded as a result of congestion in the network, and users do not receive timely responses. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cloud platforms

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Application of Digital Twins in Smart Grids 4

Application of Digital Twins in Smart Grids

引用

4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Zhang, Yiying Ma, Caixia Luo, Jian Zhu, Wenjun Wu, Yannian Zhang, Xiankun College of Artificial Intelligence Tianjin University of Science & Technology Simulation of Tianjin Enterprise Tianjin China Beijing China-Power Information Technology Co. Ltd Beijing China CHINA CRIDCOM CO. LTD. Beijing China College of Artificial Intelligence Tianjin University of Science & Technology Tianjin China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

Digital twin power grid can meet the needs of many kinds of scenarios, such as power production safety, stability, high efficiency, accurate positioning and so on, which is of vital importance to ensure the normal operation and development of smart power grid and improve the efficiency of power grid operation. Based on the physical and operational characteristics of smart grid, this paper constructs a digital twin power grid model from five dimensions: shape, data, business, energy flow and time. the full-state information perception, five-dimensional interactive mapping and three-state online deduction of power grid physical space and twin space are realized. At the same time, the corresponding digital twin models are given for some typical applications of smart grid, and the smart grid fault diagnosis model is analyzed emphatically. It is hoped that it can provide reference for the future development and ap-plication of digital twin technology in smart grid. © 2022 IEEE.

关键词： Smart power grids

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EDA and its Impact in dataset Discover Patterns in the Service Sector 4

EDA and its Impact in Dataset Discover Patterns in the Servi...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Harinakshi Lydia, Anjali A Poongundran, Mahizharuvi Masarath, Syeda Karthick, P.Vivek Zayats, Inna Mikhailovna St. Philomena's College Department of Computer Science India Sri Meenakshi Government Arts College for Women Department of Computer Science India Department of Computer Science India Sona College of Technology Department of Ece India International Education Corporation Department of Design Kazakhstan Kazakhstan

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

data scientists in order to analyse and investigate data set manly use exploratory data analysis and this process help them to summaries the main characteristics of the data set. Scientists use data visualization method under EDA system to detect the best possible way to manipulate data set in order to get the required answers they might need. this process makes the work of data scientists easier while identifying 'data pattern', 'spotting anomalies', 'testing hypothesis' and checking assumptions for the data set. EDA refers to the process, in which it can be analysed, what a data can reveal beyond any hypotheses testing and its formal modelling. EDA is effective for any data scientists to check the data set pattern before making any assumptions. the aim of this research is to develop idea regarding the use of EDA in order to discover pattern of large data set of the service sector of India and other countries. As per literature findings, it has been observed that EDA is used in different service sectors such as in insurance sector to analyse data, important to identify factors of claim filing. Different aspects of data visualization techniques under EDA system are developed in this research. Secondary data are collected in this research and data are interpreted with thematic analysis. As per the result, data analysis with EDA is effective in service sector to discover any missing link and patterns before using it to any ML model. A flow-chart for exploratory data analysis process has been developed in this study to identify the required steps under this model. Moreover, it has been found that, EDA is used to analyse data of people's health in a hospital based on remote monitoring system. © 2022 IEEE.

关键词： Python

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Hotel Recommendation System Based on Customer's Reviews Content Based Filtering Approach 4

Hotel Recommendation System Based on Customer's Reviews Cont...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Shah, Hill Jacob, Lija Christ University Lavasa Pune Department of Data Science Pune India

ISBN: (纸本)9781665474368

Recommendation systems are fantastic tools for remembering people's ideas in order to gain knowledge more efficiently and selectively. Recently, booking and searching for hotels online has become more common. As it takes more time, online hotel research is growing more quickly. In addition, the amount of knowledge accessible online is continuously expanding. User preferences have a big impact on hotel recommendations. the most effective recommendations may be made by recommendation systems by utilising historical user preference data. To solve this problem, recommender systems have suggested content-based filtering methods. Product recommendations, recommendations for websites, news articles, restaurants, and TV series are all examples of applications for content-based recommender systems. the dataset for this project includes client evaluations of the offered Kaggle profile. Word embedding, word2vec, and TF-IDF natural language processing methods were used for feature extraction. the algorithm shows the user the top 10 suggested hotels based on the user's past knowledge of the hotel's location. © 2022 IEEE.

关键词： Recommender systems

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the 4th Workshop on Modeling Socio-Emotional and Cognitive Processes from Multimodal data In-the-Wild (MSECP-Wild) 22

The 4th Workshop on Modeling Socio-Emotional and Cognitive P...

引用

24th ACM international conference on Multimodal Interaction (ICMI)

作者： Dudzik, Bernd Kuester, Dennis St-Onge, David Putze, Felix Delft Univ Technol Delft Netherlands Univ Bremen Bremen Germany Ecole Technol Super Montreal PQ Canada

ISBN: (纸本)9781450393904

the ability to automatically infer relevant aspects of human users' thoughts and feelings is crucial for technologies to adapt their behaviors in complex interactions intelligently (e.g., social robots or tutoring systems). Research on multimodal analysis has demonstrated the potential of technology to provide such estimates for a broad range of internal states and processes. However, constructing robust enough approaches for deployment in real-world applications remains an open problem. the MSECP-Wild workshop series serves as a multidisciplinary forum to present and discuss research addressing this challenge. this 4.h iteration focuses on addressing varying contextual conditions (e.g., throughout an interaction or across diferent situations and environments) in intelligent systems as a crucial barrier for more valid real-world predictions and actions. Submissions to the workshop span eforts relevant to multimodal data collection and context-sensitive modeling. these works provide important impulses for discussions of the state-of-the-art and opportunities for future research on these subjects.

关键词： User-Modeling Multimodal data Afective computing Social Signal Processing Ubiquitous computing Context-awareness

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A Novel Double-threshold Neural Classifier for Non-Linearly Separable Applications 4

A Novel Double-Threshold Neural Classifier for Non-Linearly ...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Kashif, Mohd. Rahman, Syed Atiqur Ansari, Mohammad Samar Aligarh Muslim University Department of Electronics Engineering India University of Chester Faculty of Science and Engineering United Kingdom

ISBN: (纸本)9781665474368

Classification of data finds applications in various engineering and scientific problems. When real-time operation is desired, hardware solutions tend to be more amenable as compared to algorithmic/heuristic solutions. this paper presents a novel current-mode dual-threshold neuron designed and implemented at 32nm CMOS technology node. Subsequently, a current-mode double-threshold classifier is presented which is capable of classifying input patterns of non-linearly separable problems. thereafter, application of the current-mode dual-threshold neuron in the realization of the XOR function using only a single neural unit is discussed. the proposed neuron as well as both the applications discussed are capable of operating from sub-1V power supplies. Computer simulations using HSPICE yield promising results with the values of delay and power consumption estimated to be lower than existing circuits. © 2022 IEEE.

关键词： Neural networks

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Explainable AI and Deep Learning techniques for Colon Cancer Detection 4

Explainable AI and Deep Learning techniques for Colon Cancer...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Sholapur, Prashant Narayan Indiramma, M. B.M.S. College of Engineering Department of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9781665474368

Cancer is the most common disease in the world. Cancer is a disease in which some somatic cells grow out of control and spread to other parts of the body. Of the types of cancer, colon cancer is the third most frequent cancer in the world. Artificial Intelligence is being used to diagnose cancer and deep learning techniques are used for prediction. the motive of this paper is to propose a model to implement a deep learning-based Convolution Neural Network (CNN), InceptionResNetV2 Network, and InceptionV3 transfer learning model to predict cancer and non-cancerous. the model helps in the classification and prediction of two types of colon cancer: colon adenocarcinoma and colon benign cancer. We experimented with the histopathological image data set. Along with the deep learning model, Explainable AI (XAI) technique is used for the representation of the black-box model of deep learning. © 2022 IEEE.

关键词： Forecasting

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