2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)最新文献_第2页

Detection of Wheat Crop Quality using Deep Convolution Neural Network 基于深度卷积神经网络的小麦作物品质检测

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10046820

Ranjana Sharma, Priyanka Suyal, Sarthika Dutt, S. Bharadwaj

引用次数: 0

Classification of Cyber Hate Speech from Social Networks using Machine Learning 使用机器学习从社交网络中分类网络仇恨言论

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047042

Monika Chhikara, S. Malik

{"title":"Classification of Cyber Hate Speech from Social Networks using Machine Learning","authors":"Monika Chhikara, S. Malik","doi":"10.1109/SMART55829.2022.10047042","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047042","url":null,"abstract":"Social networking sites like Twitter, Facebook, and others play a big part in social network analysis in the present Web 2.0 environment. Hate speech, which is abusive communication that singles out certain group traits like gender, religion, or race in order to incite violence, is growing in importance as social media platforms gain popularity. Hate speech on the internet is a relatively new problem in our society that is steadily growing by exploiting the flaws in the platforms that distinguish most social networking sites. The main source of this occurrence is offensive remarks, whether delivered during user contact or in the form of an uploaded multimedia context. Hateful and toxic content created by a portion of social media users is a growing phenomenon that has prompted researchers to devote significant resources to the difficult task of identifying hateful content. Some of the popular methods are the Support Vector Machine, the Logistic Regression Model, and Decision Trees. These strategies, however, frequently come under the umbrella of discriminative learning, which seeks to distinguish one class from others while taking into consideration the real world. First, this study has reviewed social networks and social network analysis. Second, the necessity of detecting hate speech and the distinction between it and abusive content are covered. Thirdly, several machine learning algorithms are being contrasted. The experimental findings demonstrate that the suggested strategy consistently outperforms the alternatives.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117242535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Qualitative Research on Wireless Body Area System Packet Size Improvement 无线体区系统数据包大小改进的定性研究

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10046899

A. Sengar, Anurag Gupta, Nupa Ram Chuhan, R. Shukla

引用次数: 0

The Performance Evaluation of Pre-trained CNN Architectures for Tumor Classification 预训练CNN体系结构在肿瘤分类中的性能评价

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047790

Chandni, Monika Sachdeva, Alok Kumar Singh kushwaha

引用次数: 0

Blockchain: Remaking the Healthcare Sector 区块链:重塑医疗行业

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047807

Bhawna Sharma, Kawalpreet

{"title":"Blockchain: Remaking the Healthcare Sector","authors":"Bhawna Sharma, Kawalpreet","doi":"10.1109/SMART55829.2022.10047807","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047807","url":null,"abstract":"Blockchain is used by the HRE (Healthcare Records Exchange) technology to satisfy the necessary requirements in line with the requirements of the public health system. Bitcoin, often known as a ledger occasionally, is a distributed system. a continually growing, linked to other bricks, protected store with lists of entries. Due to the decentralized characteristics of the system and the use of peer-to-peer (P2P) processor or network, it is ideal for the handling of critical material, such as patient information at a facility. The job is divided up across peers in a distributed application design for improved flow. Here, every peer is an equal participant in the programmed with the same privileges. the peer-to-peer or node-based network form A programmable contract containing the terms between the parties, incorporated inside the decentralized Blockchain network, is known as a smart contract. In the near future, agreements and Blockchain - based will be used to compare medical research data with other hospital databases where there is a larger chance of a data breach. Blockchains provides one of the safest ways to safeguard data with little restrictions, therefore this risk may be reduced.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121152964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Framework to Detect Crime through Twitter Data in Cyberbullying with EFFDT Model 基于EFFDT模型的网络欺凌Twitter数据犯罪检测框架

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047549

M. Nisha, J. Jebathangam

{"title":"A Framework to Detect Crime through Twitter Data in Cyberbullying with EFFDT Model","authors":"M. Nisha, J. Jebathangam","doi":"10.1109/SMART55829.2022.10047549","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047549","url":null,"abstract":"Due to enormous availability of internet, social networking and micro blogging websites such as twitter, instagram, are increased. The users registered with the website utilize the webpage as a platform to express their thoughts as comments and convey their opinions to the global users. Cyber bulling has become one of the serious issues in recent days because of controversial comments and thoughts exposed in the micro blogging websites that impacts the society and certain group of peoples in a negative way. The amount of negatively impacted comments on micro blogs are getting increased in recent days, it is required to identify those traits as a crime impacted feeds for police attention. Texting is a technique used to make a classification of large weights into clusters of related data. The proposed framework is focused on collecting various tweets from the micro blogs, further pre-processing it using natural language processing (NLP) for the features selection, is implemented using partial spam Optimization (PSO). Based on the feature extraction process, the classification model is developed using ensemble approach. The proposed approach considers Ensemble feed forward decision tree (EFFDT) model to classify different types of negative tweets from the given database. The machine learning algorithm namely Support vector Machine (SVM) algorithm and K-Nearest Neighbour (KNN) algorithm are used for comparison with the proposed method. The performance result of these algorithms are compared in terms of precision, F1Score, accuracy and further compared to the state of art approaches.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121191061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT Enabled RO Water Filter Indicator 物联网启用RO水过滤器指示灯

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047552

Prabhneet K. Sohanpal, Parneet S. Sarao, Paresh Goyal, N. K. Trivedi, R. Tiwari

引用次数: 0

The Impact of Prolonged Sitting on Sagittal Plane Postural Angle in School Going Adolescent through Photographic Method - A Study 用摄影法研究长时间坐着对上学青少年矢状面体位角的影响

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10046681

Somya Tiwari, Yamini Sharma, Karan Arya, Ritu Tomar, Deependra Rastogi

{"title":"The Impact of Prolonged Sitting on Sagittal Plane Postural Angle in School Going Adolescent through Photographic Method - A Study","authors":"Somya Tiwari, Yamini Sharma, Karan Arya, Ritu Tomar, Deependra Rastogi","doi":"10.1109/SMART55829.2022.10046681","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046681","url":null,"abstract":"Sitting for more than >8hrs is considered under prolonged sitting. Adults generally spend 6–8 hours of sitting/ per day or more than 8hrs per day. Adolescents spent most of their days in supervised institutions like schools. During school hours children have very fewer breaks. School children spend a considerable amount of their waking hours at school, mostly seated. Adolescence and Childhood are important times in the human body's growth and development. The objective of this study is to investigate that is there is any impact of prolonged sitting on sagittal plane postural angle in school-going adolescents as they spent a large amount of time in a sitting position. A questionnaire was developed using self-made questions having a details about the participant demographic data, their sitting hours, phone usage hours, physical activity, etc.198 healthy school going students of age 15–19 years (study had 121 males & 77 females) were taken for the study. Anatomical markers were placed on the C7 spinous process, ear tragus, eye can thus & greater tuberosity of humerus to measure three angles i.e CHA (Craniohorizontal angle), CVA(craniovertebral angle) & SSA(sagittal shoulder angle). Photographs were taken in the sagittal plane from the left side of the participant's body via digital camera. Angles were measured via MB ruler 5.4 software. From the result it was found that there is no impact of prolonged sitting on a sagittal plane postural angle on upper limb angle(CHA, CVA & SSA) which we had taken in the study.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124534322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Employing Adbdconvolutional KNN, Diagnosis of Irregular Driver Behavior 基于卷积KNN的违规驾驶行为诊断

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047370

Chandramma, M. R

引用次数: 0

A Province Time-Series Data Prognostication Model-based Unconventional Research 基于省份时间序列数据预测模型的非常规研究

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047609

Rati Sharma, M. Garg

引用次数: 0