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Design and development of driver’s driving pattern analysis for automatic license issuing system

AIP Conference Proceedings 2022年第1期2519卷

作者： R. Valarmathi G. Brindha S. D. Nandakumar P. Sudha Juliet 1Department of Computer Science and Engineering Sri Sairam Engineering College Chennai Tamil Nadu India 2Department of Electronics and Instrumentation Engineering Meenakshi College of Engineering Chennai Tamil Nadu India 3Department of Computer Science and Engineering KGiSL Institute of Technology Coimbatore Tamil Nadu India 4Department of Electronics and Instrumentation Engineering Meenakshi College of Engineering Chennai Tamil Nadu India

A new automatic system is being developed to prevent illegal licensing and, as a result, accidents. This system may be built using the Bayesian logic classification technique and extraction algorithm. The recommended system must build a wireless sensor network and a multi-sensor fusion sensor network to identify outcomes. To assess test data from the Vehicle Data Recorder, map management must also be compared to the data source (VDR). A remote server handles the combined transmission of the map-based and multi-fusion sensors. With data mining for results, the Bayesian classification technique is implemented. As a gateway is utilized the CC2500 wireless module, the system proposed is the removal of the existing Indian driving licensing process. The test vehicle will be assigned for this applicant with the number of sensors connected in the car that communicate data to remote servers using wireless sensor networks. The results of the study are compared to earlier data by comparing the received data.

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First inning score prediction of an IPL match using machine learning

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AIP Conference Proceedings 2022年第1期2555卷

作者： Raja Ahmed Prince Sareen Vikram Kumar Rachna Jain Preeti Nagrath Ashish Gupta Sunil Kumar Chawla 1Department of Electronics and Communication Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India 2Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India 3Department of Electronics Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India 4Department of Computer Science and Engineering Chandigarh University Mohali Punjab India

Cricket is an outdoor game which consists of 2 teams, each having 11 players, out of the two teams, one bats and the other one bowls and fields. There are various formats of cricket like Test cricket, ODI (One Day Internationals) cricket, and T-20 cricket. Test cricket format takes 5 days to reach to a decision which can be in Win, lose or Draw. Due to reduced playtime and speedy decision, nowadays T20 cricket is widely popular. Due to the popularity of T-20 across cricketing nations; many countries have started their own leagues. In India, IPL (Indian Premier League) is very much popular. Now-a-days team’s management is using various technologies to improve their team’s performance and also takes the help of various technologies to analyze the opposite team’s performance. Prediction of the score is one of the most important events in cricket. Once the score prediction is done, the chasing team prepares itself accordingly. We use deep learning and ML algorithms for finding the first inning’s predicted score. In the current work, we have used Linear Regression, Ridge Regression for model building and plot various graphs and find the errors to evaluate our model. In this model, we have used the IPL dataset taken from Kaggle and cleaned it using various available techniques. After building the model, we have analysed it by finding errors. Then we have deployed it in the graphical userinterface that was built with the help of HTML and Flask.

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Forecasting the outbreak and spread of COVID-19 in India and Tamilnadu using logistic growth and SIR models

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AIP Conference Proceedings 2022年第1期2444卷

作者： S. Geetha S. Rajeswari V. Gomathi V. Latha 1Department of Science and Humanities(Maths) National Engineering College Tamilnadu India 2Department of Computer Science and Engineering National Engineering College Tamilnadu India 3Department of Chemistry Sri. S.Ramasamy Naidu Memorial College Tamilnadu India

The whole world faces an uncommon situation in its history due to the spread of the novel coronavirus (COVID- 19). First impacted its existence during December 2019 in Wuhan City, Hubei Province, China. However, the spread of the disease is marginally visible and resulting in an epidemic distribution across capital cities of India. As of June 15, 2020, in India, 368705 are the confirmed cases, and 12280 people have deceased their lives. Collecting the statistics of daily infections, deaths and recovery data and predicting epidemic trends of COVID-19 in India has the most significant importance for developing and measuring the impacts of public intervention strategies. Based on India and Tamil Nadu's initial 105 days of COVID-19 statistics of (one of its states), we built the logistic growth model and compared their accuracy with the R2 coefficient measure. Based on the lockdown periods and severe protection measures, a scenario-based analysis of four different SIR models predicts the confirmed cases. This proposed scenario-based analysis is helpful to pre-estimate the maximum infection rate and maximum peak day of infection with the total percentage of the population being infected by the COVID-19 outbreak in India. This analysis suggests that the severe control measures are working well in India, despite the exponential growth of the outbreak situation.

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Blockchain meets healthcare: Architecture for secure data sharing in unobtrusive medical applications

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AIP Conference Proceedings 2022年第1期2405卷

作者： M. Jayasudha C. Vijayalakshmi 1School of Computing Science and Engineering Vellore Institute of Technology Chennai 600127 India 2Department of Computer Science and Engineering B S Abdur Rahman Crescent Institute of Science and Technology Chennai 600048 India

Modernages have perceived an exemplar swing in warehousing Electronic Health Records (EHRs) on cloud settings with the catholic solicitation of mobile healthcare systems, where mobile devices are assimilated by means of cloud computing to assistmedicinal data interactions amid patients and surgeons. The distribution of EHRs has prodigious optimistic connotation for investigation of disease and doctors’ diagnosis. This radical model empowers healthcare amenities with truncatedoperating charge, high flexibility, as well as EHRs accessibility. It is of paramount significance to hitch therapeutic evidence sprinkled through healthcare establishments to provision exhaustive data investigation and accomplishcustom-made healthcare. Nevertheless, this newfangledarchetype also nurtures apprehensions about data privacy in addition to network security for healthcare schemes. Exactly how to stead fastly stake data among mobile consumers while pledging sophisticated security echelons in cloud is a perplexing concern. Blockchain, by means of a public ledger pigeon holed through its transparency, tamper-evidence, decentralization, unforgeability, verifiability, as well as anonymity can supportin forming a secure healthcare scheme. Existing works primarily recompensed evotion to centralized in addition toblockchain-based mechanisms. Nonetheless they could not acclimatize to the snow balling volume of global medical records and agonize from multifaceted application encounters, singly. In this paper, we recommend a Diagonal Digital Signature Algorithm (DDSA) with Merkle Patricia Hash Trie (MPHT) algorithm which is aninnovative EHRs sharing framework that exploitsblockchain to expedite secure medical record sharing amiddissimilar patients and surgeons. The pragmaticoutcomesillustrate that our schemeaffords an operativeelucidation for unswerving data interactions on cloud while conserving delicate medical records in contrast to impending intimidations. The scheme assessment along with t

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Simultaneous identification of joint compliance and kinematic parameters with the joint compliance parameters determined by teaching learning based optimization

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AIP Conference Proceedings 2022年第1期2502卷

作者： Phu-Nguyen Le Van-Cuong Nguyen Hee-Jun Kang 1Department of Information Technology Specialization FPT University Hoa Lac High Tech Park Hanoi Vietnam 2Department of Electrical Electronic and Computer Engineering University of Ulsan Ulsan 44610 South Korea

The elastic of links and joints keep the industrial robotic from archiving the required precision when executing an operation with a payload. This article suggested a novel industrial robot manipulator calibration approach, which detects joint compliance and kinematic characteristics at the same time by combining kinematic calibration technique and teaching- learning-based optimization method. The proposed method combined the geometric and non-geometric calibration to consider the geometric errors and the shifting of joints together to enhance the positional precision of the industrial robotic manipulator. Due to the fusion of the two fundamental methods, the proposed calibration technique has many advantages such as fast convergence, less computing, accurate knowledge of error sources and significantly increase the accuracy of the robot. The proposed modeled-based calibration technique is also performed on YS100 robot to demonstrate its effectiveness and feasibility.

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An Efficient and Robust Feature Selection Approach Based on Zentropy Measure and Neighborhood-Aware Model

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IEEE transactions on neural networks and learning systems 2025年 PP卷 PP页

作者： Kehua Yuan Duoqian Miao Hongyun Zhang Witold Pedrycz Tongji University School of Computer Science and Technology National Pilot Software Engineering School Shanghai 201804 China Silesian University of Technology (SUT) Department of Measurement and Control Systems Gliwice 44-100 Poland University of Alberta Department of Electrical and Computer Engineering Edmonton T6G 2R3 AB Canada Istinye University Research Center of Performance and Productivity Analysis Istanbul 21589 Turkey

The feature selection based on the rough set (RS) theory has been an active research topic in data mining and knowledge discovery. Fuzzy RSs (FRSs), an efficient tool to process the inconsistency between features and decisions, have attracted attention to the problems of feature selection. However, most FRSs-based feature selection methods pay much attention to the approximation space while ignoring the interaction between different levels. Note that the single-level feature selection method, depending on the boundary objects, is easily influenced by the noise data and cannot integrate multiple granular levels to evaluate features accurately. Therefore, this article proposes an efficient and robust feature selection approach based on the neighborhood-aware model and zentropy measure. Specifically, we first define a neighborhood-aware FRS (NAFRS) with weighted fuzzy relation to improve the antinoise ability of FRSs. Then, we propose a fuzzy granule zentropy (FGZE) measure based on zentropy by analyzing the granular level relation in NAFRS. Moreover, a significance measure with FGZE is designed and applied to feature selection. Finally, the experimental results of our method on 22 datasets by comparing it with 12 representative feature selection methods demonstrate the antinoise and the classification ability of the proposed method.

关键词： Feature selection fuzzy granule zentropy (FGZE) fuzzy rough set (FRS) granular computing uncertainty measure

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Automation in vertical gardening using LABVIEW

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AIP Conference Proceedings 2021年第1期2378卷

作者： M. Lohitha E. J. Priyadharsini K. Sangeetha J. E. Jeyanthi T. Ananth Kumar 1Department of Electronics and communication Engineering National Engineering College Kovilpatti India 2Department of Computer Science & Engineering IFET College of Engineering Tamilnadu India

The method of cultivating plants and developing them is called Gardening as a part of horticulture. Vertical gardens are another way of maintaining gardens and implanting them in unexpected locations within the cities. Vertical wall plants used when there is not much space for gardening in an area like on a porch or a balcony. The method of growing plants without soil is called Hydroponics while using a nutrient solution. In the hydroponic, the nutrients used can come from many different sources, such as duck manure and artificial nutrient solutions. The main advantage of hydroponics is the less usage of water for agriculture. Unlike horticultural crops, several species within unique expectations are considered by the method and are subject to complex environmental conditions. The oscillations of temperature, light, and humidity need to consider. This technique used to remind the farmer of the schedules of ripping, fertilize spraying, pesticides, and irrigation things through mobile. The proposed work reduces the cost of gardening as well as the amount of water and soil to maintain gardening. The proposed method is very helpful in maintaining a garden using fewer pesticides but also can focus on providing the plant with sufficient water, nutrients, and light at all stages. All the simulations have been performed using LABVIEW software.

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Application of machine learning techniques for an evaluation of hazardous chemical assessment in firework industry

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AIP Conference Proceedings 2022年第1期2520卷

作者： N. Indumathi R. Ramalakshmi N. Selvapalam 1Department of Computer Applications Kalasalingam Academy of Research and Education Tamil Nadu India 2Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamil Nadu India 3Department of Chemistry Kalasalingam Academy of Research and Education Tamil Nadu India

Occupational Health Hazard is prevalently on the rise as industrialization increases in the global world. In the fireworks industry, manufacturing procedures for fireworks utilize hazardous chemicals for producing light, color, and sound. Fireworks manufacturing often necessitates human handling of dangerous chemicals, for all manufacturing processes where employees come into close contact with dangerous substances that cause illness to heath. It produces health implications that could result in diseases and sicknesses. Machine learning supervised algorithms were a dominating approach in the field of data mining. Recently, predictions on the health effects associated with hazardous chemicals have proven that these strategies may be applied. Each algorithm's experimental outcomes on the dataset have been examined. The purpose of this study is to discover major trends between different types of supervised machine learning algorithms and their performance and use to prevent ailment risk based on the work process. In comparison between the Support Vector Machine with Random Forest algorithm predicts that the severity level of disease would have the highest accuracy (90.7%), Sensitivity (88.8%) and specificity (92.6%).

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Interactions between invasive plants and heavy metal stresses:a review

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Journal of Plant Ecology 2022年第3期15卷 429-436页

作者： Jian Li Zhanrui Leng Yueming Wu Yizhou Du Zhicong Dai Asim Biswas Xiaojun Zheng Guanlin Li Esawy Kasem Mahmoud Hui Jia Daolin Du Institute of Environment and Ecology Institute of Environmental Health and Ecological SecuritySchool of the Environment and Safety EngineeringJiangsu UniversityZhenjiang 212013China Key Laboratory of Original Agro-Environmental Pollution Prevention and Control Ministry of Agriculture and Rural Affairs/Tianjin Key Laboratory of Agro-Environment and Agro-Product SafetyAgro-Environment Protection InstitutionMinistry of Agriculture and Rural AffairsTianjin 300191China Faculty of Engineering School of Computer ScienceUniversity of SydneyDarlingtonNSW 2008Australia School of Environmental Sciences University of GuelphGuelphON N1G 2W1Canada Department of Soil and Water Science Faculty of AgricultureTanta UniversityTantaEgypt

Global changes have altered the distribution pattern of the plant communities,including invasive *** contamination may reduce native plant resistance to the invasive ***,the focus of the current review is on the contaminant biogeochemical behavior among native plants,invasive species and the soil within the plant-soil ecosystem to improve our understanding of the interactions between invasive plants and environmental *** studies together with synthesis of the literature showed that(i)the impacts of invasive species on environmental stress were heterogeneous,(ii)the size of the impact was variable and(iii)the influence types were multidirectional even within the same impact ***,invasive plants showed self-protective mechanisms when exposed to heavy metals(HMs)and provided either positive or negative influence on the bioavailability and toxicity of *** the other hand,HMs may favor plant invasion due to the widespread higher tolerance of invasive plants to HMs together with the‘escape behavior’of native plants when exposed to toxic HM ***,there has been no consensus on whether elemental compositions of invasive plants are different from the natives in the polluted regions.A quantitative research comparing plant,litter and soil contaminant contents between native plants and the invaders in a global context is an indispensable research focus in the future.

关键词： environmental stresses heavy metals plant invasion biogeochemical cycle mechanisms

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Email notifier using named entity extraction

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AIP Conference Proceedings 2023年第1期2523卷

作者： K. Anand M. Vijay Anand R. Saravanan 1Department Information Technology Center for Artificial Intelligence and Research Chennai Institute of Technology Chennai Tamil Nadu India 2Department of Computer Science and Engineering Saveetha Engineering College (Autonomous) Chennai Tamil Nadu India 3Department Information Technology Center for Artificial Intelligence and Research Chennai Institute of Technology Chennai Tamil Nadu India

Email plays an essential role in communication and its flexibility, simplicity, diversified types, and low cost of information in the modern world. Therefore handling out a large volume of emails takes are mark able amount of human power and time. To quickly extract the named entities from an email requires an automated solution. So we proposed a tool to extract named entities from emails. This solution incorporates the latest technologies like NLP (Natural Language Processing) and IR (Information Retrieval). This would perform named entities extraction of email automatically organizes and notifies the user. The proposed mechanism can be used in many organizations. Named Entity Recognition (NER) will be a vital language processing tool for information retrieval from texts like newspapers, blogs, and emails. NER performs the classification of words and sensing the expression of text from unstructured data. Spa Cy may be a free, open-source python library for advanced language Processing. It is well known for production use and helps build the system that performs understanding of a text. It helps in information extraction, understanding the plans, and preprocesses the text for deep learning.

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