bluuebunny/crossref_metadata_2025 huggingface dataset:
An end-to-end Novel Forecasting Model for Crime Prediction based on Big Data
Authors:   Assistant professor of Information technology in SRM IST,Chennai,Tamil Nadu,India, Vinodhini* M. , Srivastava Dhruv ,   Department of Information Technology,SRM IST,Chennai,Tamil Nadu,India., Hirani Sameer ,   Department of Information Technology,SRM IST,Chennai,Tamil Nadu,India, Arora Shubham ,   Department of Information Technology,SRM IST,Chennai,Tamil Nadu,India.
Published: April 2020

Big data analytics is a field in which we analyse and process information from large or convoluted data sets to be managed by methods of data-processing. Big data analytics is used in analysing the data and helps in predicting the best outcome from the data sets. Big data analytics can be very useful in predicting crime and also gives the best possible solution to solve that crime. In this system we will be using the past crime data set to find out the pattern and through that pattern we will be predicting the range of the incident. The range of the incident will be determined by the decision model and according to the range the prediction will be made. The data sets will be non-linear and in the form of time series so in this system we will be using the prophet model algorithm which is used to analyse the non-linear time series data. The prophet model categories in three main category and i.e. trends, seasonality, and holidays. This system will help crime cell to predict the possible incident according to the pattern which will be developed by the algorithm and it also helps to deploy right number of resources to the highly marked area where there is a high chance of incidents to occur. The system will enhance the crime prediction system and will help the crime department to use their resources more efficiently.
Social Media Marketing Strategies influencing Customer Engagement - Structural Equation Modelling.
Authors:   Part time PhD Scholar, Department of Commerce, Madras Christian College (Autonomous), Affiliated to the University of Madras, Hepziba* Mrs. R.Esther , John Dr.Mrs.Florence ,   Research Supervisor, Assistant Professor, Madras Christian College (Autonomous), Affiliated to the University of Madras
Published: April 2020

Retaining Customer attention and keeping them Engaged with brands and Products at the least has become a mammoth task in recent days. Customer Engagement has been explained as the bond between business or marketers with the Customers. The relationship between the customers and the Marketers, can happen through several platforms, out of which Social Media is a powerful one. Almost everyone uses Social media now and there is certainly, a continuous increase in the numbers. This platform is used by marketers to increase Customer Engagement through various marketing strategies. The marketing strategies in Social media include promotions and advertisements through various means such as videos, texts, Photos and web-links. These strategies elicit reaction, response or keep customers mentally engaged, which earlier studies on this have substantial arguments supporting this. The engagement can be Passive or active. The present study considers three factors of Customer Engagement and has established the structural relationship between the measured variables and the unmeasured using Structural Equation model. The measured being Personalised, Interactive and Ethical promotional strategies that lead to Customer Engagement. The top ten Social media such as Facebook, Whatsapp, Twitter, Youtube, Instagram, Pinterest, LinkdIn, Tumblr, Snapchat and Tiktok have been taken for the study .The result of the study gives insight to the Marketers on which is the most influential variable on Customer Engagement. The result reveals that Personalised Promotions play a prominent role in keeping Cutomers Engaged. Hence focus on this parameter by the marketers which has an effect on Customer loyalty will help in customer retention
File Management and Transparency System using Blockchain
Authors:   Computer Science Engineering, Excel Engineering College, Tamil Nadu, India., Acharya* Samjana , Sreethar Dr. S. ,   Computer Science Engineering, Excel Engineering College, Tamil Nadu, India., Thapa Pramod ,   Computer Science Engineering, Excel Engineering College, Tamil Nadu, India., Sonar Shweta Shah ,   Computer Science Engineering, Excel Engineering College, Tamil Nadu, India., Aarthi M. ,   Computer Science Engineering, Excel Engineering College, Tamil Nadu, India.
Published: April 2020

Modern India has had a strong focus on technology. There exists technology in all the field including government sector. The main objective of this paper is to provide the method to secure the file monitoring system. This application is to monitor every file movements of all the employee and timely informed via SMS, emails. For this purpose, each file contains the barcode and whenever file move out of the warehouse then the barcode are scanned to update its status. This system is build using blockchain technology. One of the reasons to choose the blockchain is because a blockchain is distributed, decentralized, secured, digital playscript which is use for recording the transaction over many computers so that records cannot be altered. The aim of this experiment is to provide file transparency and should provide estimated turnaround time at each stage.
Student Analysis System for Training and Placement
Authors:   CSE Department, GITAM University, Bengaluru, India., Kumar B* Navaneeth , Kandula Vamsi ,   CSE department, GITAM University, Bengaluru, India., Ambiti Praneeth ,   CSE department, GITAM University, Bengaluru, India., K Hema ,   CSE Department, GITAM University, Bengaluru, India., Buddha Dr. Kishore ,   Mechanical Department, GITAM University, Bengaluru, India.
Published: April 2020

According to the survey done by aspiring minds on Annual Employability in 2019, only 2.5% of students have the technical skills that are required for industry, and 80% of engineers do not possess the skills that are necessary for the industry. Engineering employability rates can be improved when we have student analysis data to understand their performance in every aspect. So, to decrease the unemployability rate, we are proposing a Student Analysis System that gives students a performance report for analyzing student strengths and weaknesses in various company’s recruitment exams. The system is entirely automated by using various techniques to minimize the work of the Training and Placement Department. The information about the student, which is available in the portal, can be shared with the various recruiters based on the eligibility criteria, skills, and requirements of the company. The front-end of the platform is developed by using HTML, CSS, JavaScript, backend of the platform by using PHP. And along with the Xamp web server.
Artificial Intelligence for early Detection of Breast Cancer and Classification of Mammographic Masses
Authors:   Associate Professor at KLE Dr.M.S.Sheshgiri College and Engg, Belagavi,India, Patil* Dr.Sujata N , Madiwalar Prof. Shweta M ,   Assistant Professor at KLE Dr.M.S.Sheshgiri College and Engg ,Belagavi, India, Aparanji Dr. V M ,   Assistant Professor at Siddaganga Institute of Technology, Tumkur, India.
Published: April 2020

Every single year thousands of women endure painful and invasive surgery to remove breast lesions. Most of the time the mammographic image analysis leads to false positive detection and the majority of this actions reveal the lesions to be benign. Refining present detection and diagnostic tool is a major priority of our work. MATLAB R2015a is been used to develop the algorithm, which aids in detection of breast cancer in its early stage. The algorithm comprises of image processing and applying artificial intelligence where in the system is trained with a set of images so that when the input or the test image is given, the algorithm performs the image processing techniques and then applies the Probabilistic Neural Network (PNN) technique for detection of cancer. The system performance is also been calculated in order to estimate its reliability.
Load Balancing at Fog Nodes using Scheduling Algorithms
Authors:   Computer Science Department, College of Arts and Science, Prince Sattam Bin Abdul-Aziz University,Wadi Al Dawassir, Riyadh, K.S.A, Muqeeth* Mr.Mujthaba Gulam , Kolhar Dr.Manjur ,   Computer Science Department, College of Arts and Science, Prince Sattam Bin Abdul-Aziz University, Wadi Al Dawassir, Riyadh, K.S.A., Ameen Dr.Aballa Al ,   Computer Science Department, College of Arts and Science, Prince Sattam Bin Abdul-Aziz University, Wadi Al Dawassir, Riyadh, K.S.A.
Published: April 2020

Cloud Computing proves to be most predominant innovative field in the area of Information technology. Cloud is best suited for small scale to large scale businesses and personal purposes such as storing, computing, managing data & resources, running applications and many more. Due to increasing large volumes of data over cloud servers created subsequent specific issues like data maintainability, network elasticity, managing Internet of Things (I.o.T’s) devices and many more. Recent progresses in Technology are given rise to fog computing or decentralized cloud to overcome cloud server issues called fog nodes. In this paper we present a brief note on how cloud issues can overcome using fog nodes benefits along with elaboration of load balancing factor. To maintain load balancing of fog nodes no much appreciable work took place in the field of fog computing. This paper proposes a scheduler which receives the devices in to a Job Queue to be connected over cloud. To apply scheduling algorithms like F.C.F.S, S.J.F, P.S, R.R and W.R.R. over fog nodes will be discussed along with their merits & demerits. At last we try to compare the various parameters of load balancing among various scheduling algorithms. In this paper we focus on how fog nodes perform functions like considerable storages, low latency, heterogeneity, allocation & interaction with limited IoT devices and Security along with architecture cloud to fog. During allocation of IoT devices to various fog nodes we will come across a serious issues i.e load balancing on fog nodes. Our detailed study presents the comparison of above mentioned scheduling algorithms load balancing factors such as rich resources allocations & Balancing among fog nodes, Identification of devices, Authentication of fog nodes, bandwidth consumption, location awareness, response time, cost maintenances, Intrusion detection, fault forbearances and maintainability.
Diabetic Retinopathy Diagnosing using Fuzzy Image Processing
Authors:   Department of Biomedical Engineering, U. V. Patel College of Engineering, Ganpat University, India., Chitara* Himal , Patel Prof. Raksha K ,   Department of Biomedical Engineering, U. V. Patel College of Engineering, Ganpat University, India., Bhatt Prof. Tejas V ,   Department of Biomedical Engineering, U. V. Patel College of Engineering, Ganpat University, India.
Published: April 2020

Aim: To design diagnostic expert system using fuzzy image processing for diabetic retinopathy, measures diabetic eye morbidity. Method: From this research paper, diagnosing diabetic retinopathy using fuzzy image processing for diabetic patients. Firstly collection of OCT images of the patient who has diabetic retinopathy. Author’s proposed method finds out the edge detection of the OCT image. Then fuzzy logic is applied on that result of image processing. Design a fuzzy rules and input- output parameter. This method gives accurate diagnosing the diabetic retinopathy from the image of the patient’s retina images. Result: This diagnostic system gives patient’s eye morbidity, vision threatening of the diabetic patients. In the result, edges of the retina images, and from that retinal ruptures, thickness of the proliferative in the retina. From these result, diagnostic of diabetic retinopathy conditions such as PDR, NPDR, and NORMAL, and CSME in the diabetic patients. Conclusion: author has design diagnostic system for endocrinologist and ophthalmology to diagnosed diabetic retinopathy in the patients. From this system doctors don’t need patients for diagnosing purposed.
Disease Prediction using Machine Learning
Authors:   Assistant Professors, Department of Information Technology, PVPSIT, Vijayawada, AP, India., Kumar* Dr.S.Sai , Rao Dr.B.V.Subba ,   Professor & Head, Department of Infromation Technology, PVPSIT, Vijayawada, AP, India., Sirisha J. ,   Assistant Professors, Department of Information Technology, PVPSIT, Vijayawada, AP, India., Anusha B. ,   B.Tech Students, Department of Information Technology,PVPSIT,Vijayawada,AP,India., Akhil Sai ,   B.Tech Students, Department of Information Technology,PVPSIT,Vijayawada,AP,India., Suhesh K.Venkata ,   B.Tech Students, Department of Information Technology,PVPSIT,Vijayawada,AP,India., Bhavana K. ,   B.Tech Students, Department of Information Technology,PVPSIT,Vijayawada,AP,India.
Published: April 2020

As global population is increasing, life expectancy rises, and standards of living increases, and the causes of death across the world are changing. Now-a-days most of the deaths are occurring due to the lack of awareness among people about which disease may have the chance to occur for a particular symptom. So by taking the previous datasets of patients and analyzing it, we can predict which disease may have the scope to occur for a particular symptom. It creates an awareness among people about the disease and appropriate medication can be received. By this the death rate can be minimized. So, in this system, we are going to analyse the patient datasets by using machine-learning(linear regression) algorithms and python code to predict the diseases which have the chance to occur and so that we can reduce the death rate
Performance Analysis of Classifiers in Identifying NREM Sleep and Awaken Stages from EEG Signals
Authors:   Department of ECE, Bannari Amman Institute of Technology Sathyamangalam, Rajaguru* Harikumar , Khan N Sanjai ,   Department of ECE, Bannari Amman Institute of Technology Sathyamangalam., Krishnamoorthy Vinitha ,   Department of ECE, Bannari Amman Institute of Technology Sathyamangalam.
Published: April 2020

Electroencephalogram is a medical procedure which helps in analyzing the activities of the brain through electrical signals. In this paper a simple classification technique of EEG signal into two stages as NREM sleep and awaken stages had been undertaken. Classifying these stages helps the physician to understand the patient's sleep disorder by knowing whether the person's brain is in NREM sleep or awaken stages. Physionet EEG signals are samples of 256 signals per second for 10 seconds duration is used in this work. Then the EEG samples properties are analyzed through various parameters like statistical features, entropy Pearson correlation coefficient, Power spectral density, scatter plots and Hilbert transform plots. The classification of NREM sleep and awaken stage is performed by the ten different classifiers broadly grouped into non linear and hybrid one. The classifiers used include Linear Regression, Non Linear Regression, Logistic Regression, Principal Component Analysis, Kernel Principal Component Analysis, Expectation Maximization, Compensatory Expectation Maximization, Expectation Maximization with Logistic Regression Compensatory Expectation Maximization with Logistic Regression, and Firefly. The performances of the classifiers are analyzed using regular parameters like sensitivity, accuracy, specificity, performance index. The highest accuracy of 95.575% is achieved with linear regression for awaken signal and an accuracy of 95.315% is achieved using kernel PCA for sleep signal.
Development of Fire Exit Brick using Waste Candle Wax
Authors:   Assistant Professor, Department of Civil Engineering MEPCO Schlenk Engineering College, Sivakasi, India., Anuja* N. , Kumar A.Senthil ,   Students, Department of Civil Engineering MEPCO Schlenk Engineering College, Sivakasi, India., Manikandan M. ,   Students, Department of Civil Engineering MEPCO Schlenk Engineering College, Sivakasi, India., Yogesh G. ,   Students, Department of Civil Engineering MEPCO Schlenk Engineering College, Sivakasi, India.
Published: April 2020

Fire Exit Brick is a structural building material having sufficient crushing strength and it is generated from the combination of Waste Wax and Granite Powder. The aim of this research is to create a brick which is provided in the outer periphery of the windows and door to hold it. During the time of fire, these bricks will lose its strength and creates a fire escape pathway by just pushing the doors and windows towards outer side to save the people from fire accidents without affecting the structural aesthetic look at low manufacturing cost. It also helpful for the fire fighters to rescue the people from the fire.
Radio Frequency Identification (RFID) Integrated System for Security Measures in IoT Applications
Authors:   Cisco Systems, Senior Technical Leader, Cisco Systems, Senior Technical Leader, Upadhyaya* Santosh Kumar
Published: April 2020

This study presents a low frequency RFID (LF-RFID) sensing system integrated with Internet of Things (IoTs) to detect and characterize corrosion. The LF-RFID sensing sys-tem comprises of a tag and reader inductively linked with each other. Tag interacts with corroded metal through eddy currents and measure changes in corroded surface conductivity and per-meability. Sensitivity and impedance of LF-RFID sensor varies with distance between tag to reader; which is adjusted to find the optimum working range. The static and transient features of LF-RFID sensor signal is used to characterize corrosion at low com-putational rate. The size of commercial low frequency tags is very small compared to structures in practice. So, IoTs is used to make a wireless sensor network of proposed sensing system. Re-sults showed an enhancement in sensitivity to corrosion charac-terization at optimum distance between tag and reader. Using IoTs, several sensors are cascaded to make WSN and enable monitoring a wide structural area.
Financial Inclusion: An Application of Machine Learning in Collaborative Filtering Recommender Systems
Authors:   Research Scholar, Sri Sri University, Cuttack, Odisha, Das* Mr. Girija Sankar , Nayak Prof. (Dr.) Bhagirathi ,   Professor Sri Sri University, Cuttack, Odisha
Published: April 2020

In the current scenario in finance, data play a major role for predicting stock market as well as verious financial instruments. For the estimation of financial data, the various algorithms and models have been used. The use of the advising method has been used in this paper. The advising programs are one of the main methodologies used in the present market scenario with machine learning technologies. This paper focuses on the impact of financial inclusion in Odisha using a machine learning approach such as the classification of k-Nearest Neighbors (k-NN). For financial inclusion systems, machine learning has become a commonly used method. The result takes into the ATMs, Banks and BCs ranking in different districts of Odisha. We used the k-Nearest Neighbor's machine learning methodology classification algorithm to characterize the recommendation system based on users of the mentioned populations. Using our approach we equate conventional collective filtering. Our results show that the linear algorithm is more reliable than the current algorithm and is more efficient and stable than current methods.
Optimisation and Reliability for Geometrical Tolerance Value against Positional Characteristic in Rotational Shaft System
Authors:   PhD student, Universiti Kebangsaan Malaysia., Jafri* K. , Ramli R. ,   PhD in Gifu University Japan., Azman A. H. ,   PhD from Univ. Grenoble Alpes, France
Published: April 2020

In the process of manufacture and installation, geometrical dimensions and tolerances (GD&T) should be taken into consideration to improve reliability and reduce the adverse impact on critical parts of the rotating system. GD&T must be considered by manufacturers and assembly worker. This paper presents an analysis of geometrical tolerance (GT) values in rotational shaft using the genetic algorithm (GA) method. GA optimization uses a geometric mathematical model. Mathematical models were developed using the offset and algebraic methods to calculate the ideal geometric features that best fit a set of positioning points based on the standard equations criteria. The calculation using the Matlab software application will use the optimal GA parameter. There is a combination of four genetic parameters associated with size population, crossover, mutation and stop state will develop algorithm performance which will produce optimum GT value. The geometric tolerance value for the position characteristic was analyzed to determine and predict the probability and reliability shaft in rotational system. Comparative values of each GT value are compared to find out the reliability values obtained can be used and verify the GT value requirements require mathematical representation. Tolerance analysis at the design stage to evaluate and predict quality by considering the probability of failure rates. The Actual value of the radius must be small from the allowable radius (Ract <Rallow) to cope with the high failure rate throughout the operating period. Due to dynamic nature of the shaft round and the possibility of a variable size of shafts, the GT value should be analyzed to ensure that the value obtained is correct and can be optimum solution to this problem. The GT value to be considered is at the center of the shaft involved which will affect the relevant components. Impact of GT value on the destruction of system critical component such as bearings, gear and couplers as benchmark for review for the optimization of shaft geometric tolerances in rotating machines to overcome the problem and improve concentricity shaft. The contribution of this study is to examine the effect of shaft size and the value of geometric tolerance on system reliability. Estimating and predicting levels of reliability more accurately improves system life, knows the system's impact accurately, knows the security level of a rotating system and also knows the quality of the mechanism at the design level.
A Novel Encryption Scheme for Securing Data in HDFS Environment Inspired By DNA
Authors:   M.Tech,computer science and security information brunch,School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar , India., Haidari* Shahrabanu , Dash Amiya Kumar ,   Assistant Professor in School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar , India, Rout Jitendra Kumar ,   Assistant Professor in School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar India.
Published: April 2020

Today, the majority of industries used Hadoop for processing their data. Hadoop is an open-source and programming based framework that has many components. One of them is HDFS (Hadoop Distributed Files System) that is used to stored data. Hadoop by default does not have any security mechanism. According to the previous study authentication, authorization, and Data encryption are the principal techniques to enhance the security in HDFS. As huge volume of data is stored in HDFS, encryption of massive data will consume more time and need more resources for operations. In this paper we have developed one DNA based that used confusion and Diffusion for securing data in HDFS. This proposed algorithm is efficient as compared to other encryption algorithm.
Smart Vehicular Parking System
Authors:   School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, India., Gupta* Nirbhay , Mishra Somnath ,   School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, India., Porwal Prateek ,   School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, India., Bhattacharyya Budhaditya ,   School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, India.
Published: April 2020

In today’s world, ever growing population adds up increasing numbers of cars. Especially, in metro cities with limited spaces for parking, innovative measures are the need of the hour. Our paper focuses on this specific aspect of acute shortage of parking spaces. In this paper, we are proposing a smart vehicular parking model, that takes into account registered or non-registered users parking at the same time. Additionally, it also takes help of image processing to classify the available space based on the size of the vehicle, making it an optimized real-time parking prototype. Using RFID to authenticate each user, the model uses Internet of Things (IoT), cloud storage to makes it convenient for each and every individual to locate and remotely book a parking spot via a smartphone. It works to its full potential by securing cashless transaction via e-wallet. The efficiency of our prototype has been further established by improving parking area by 28 % under any given circumstance. Hence this novel idea excels in every aspect by providing an optimized parking space.
Implementation of 5S to Improve the Productivity of Detergent Manufacturing Industry
Authors:   Assistant Professor, Kongu Engineering College, Perundurai, India., Sundharesalingam* Dr.P. , Hemalatha Ms.B. ,   pursuing Master of Business Administration in Kongu Engineering College, Perundurai, Priya Dr.P.Vidhya ,   Associate Professor, Kongu Engineering College, Perundurai, India., Mohanasundari Dr.M. ,   Assistant Professor, Kongu Engineering College, Perundurai, India.
Published: April 2020

this work is carried out to apply the lean tools i.e., 5S to solve the problems in a detergent manufacturing industry. The lean tools are one of the most effective and efficient method for eliminate the waste, improve the quality, overall performance of the machine and improves the annual profit. Their main aim is to reduce the cycle time. The objective of this work is to increase the productivity and eliminate the unwanted steps. Primary method is used for the data collection i.e., Observation method. The stopwatch is used to calculate the time taken for each job. The improvement of work process was executed by eliminating and combining the work process, which reduce the production time, number of process, increases the production rate and also provides the free space. 5S is used to achieve the objectives. The time taken to complete the work has been noted down before and after implementation of 5S. When we reduce the cycle time, the productivity will increase. When we implement the 5S the cycle time will reduce from 190 sec to 110 sec.
Ambient Air Pollution Forecasting System using Deep Neural Networks
Authors:   Computer Science program at VR Siddhartha Engineering College. affiliated to JNTUK University, Kakinada., Jujjavarapu* Geethika , Duggirala Siddhartha ,   Bachelor of Technology in Computer Science and Engineering at VR Siddhartha Engineering College afflicted to JNTUK University, Kakinada., Kavutarapu Anulekha ,   B.Tech final year in Computer Science and Engineering at VR Siddhartha Engineering College affiliated to JNTUK University, Kakinada., Surapaneni Mr. Ravikishan ,   Associate Professor, CSE department at VR Siddhartha Engineering College
Published: April 2020

Air pollution is a major problem that has been recognized throughout the world. Harmful impacts of air contamination include hypersensitive reactions such as throat irritation, itchy eyes, nose, and some other serious problems. In recent years, the number of fatalities occurred due to air pollution has been increasing dramatically. In this paper, various air pollutants such as Carbon Monoxide, Methane or natural gas, LPG, and air quality at different places of city are measured using sensors. Further, the detected values are then used in the prediction of future values. The evolution of deep neural networks and Internet of Things made this possible to detect and forecast the concentration of pollutants underlying in the air. We use a special module called pyFirmata firmware which is used to connect the Arduino with python and upload the data into csv file on Jupyter Notebook. Here, the data collected is univariate i.e. it varies with only time. Though there are many statistical models to predict time series datasets such as ARIMA, their efficiency is low. Deep Neural Networks works well for predicting univariate as well as time series datasets. Hence, the Keras sequential model is employed to predict the hourly future values of air pollutants based on previous readings. The final results of prediction are compared with the actual values and error is calculated. As a result, the level of air pollutants at a particular hour can be predicted. The concentration of air pollutants in coming years, month or week helps us to reduce its concentration to lesser than the harmful or toxic range.
Iterative SARSA: The Modified SARSA Algorithm for Finding the Optimal Path
Authors:   B. Tech in Computer Science and Technology from Vellore Institute of Technology, Vellore, India, Mohan* Prajval , Narayan Pranav ,   B. Tech in Computer Science and Technology from Vellore Institute of Technology, Vellore, India, Sharma Lakshya ,   B. Tech in Computer Science and Technology from Vellore Institute of Technology, Vellore, India, Jambhale Tejas ,   B. Tech in Computer Science and Technology from Vellore Institute of Technology, Vellore, India, Koul Simran ,   B. Tech in Computer Science and Technology from Vellore Institute of Technology, Vellore, India
Published: April 2020

This paper presents a thorough comparative analysis of various reinforcement learning algorithms used by autonomous mobile robots for optimal path finding and, we propose a new algorithm called Iterative SARSA for the same. The main objective of the paper is to differentiate between the Q-learning and SARSA, and modify the latter. These algorithms use either the on-policy or off-policy methods of reinforcement learning. For the on-policy method, we have used the SARSA algorithm and for the off-policy method, the Q-learning algorithm has been used. These algorithms also have an impacting effect on finding the shortest path possible for the robot. Based on the results obtained, we have concluded how our algorithm is better than the current standard reinforcement learning algorithms.
Performance Based Seismic Analysis of Steel Frames
Authors:   Department of Civil Engineering, SVERI’s College of Engineering, Pandharpur, India., Bagal* Srushti , Pawar Dr. Prashant ,   Department of Civil Engineering, SVERI’s College of Engineering, Pandharpur, India., Kshirsagar* Vidyarani ,   Department of Civil Engineering, SVERI’s College of Engineering, Pandharpur, India., Kokare* Avinash ,   Department of Civil Engineering, SVERI’s College of Engineering, Pandharpur, India.
Published: April 2020

The Civil Engineering profession has been changing the structural engineering design paradigm from life safety (LS) to Performance Based Seismic Design (PBSD) to tackle catastrophic damage caused by recent earthquakes worldwide. This paper is about the PBSD analysis of steel frame subjected to earthquake loading. Steel is by far the most versatile building material in the world and steel structure has played a major role in construction industry in the last decades. In this a multistoried bare and braced steel frames are analyzed by PBSD procedure in STAAD Pro Advanced following nonlinear static analysis. Frame components (beam, columns, etc.) are progressively adjusted to account for nonlinear elastic–plastic behavior under constant gravity loads and incrementally increasing lateral loads. Capacity curve is obtained for each frame and comparatively studied to decide which type of frame can meet the desired performance level during earthquake. The results of the analysis performed to meet required performance are presented in terms of displacement, shear forces, plastic hinges and capacity curve.
Design and Simulation of High-Gain DC-DC Converter using P&O Algorithm with Bi-Directional Converter for Minimum Voltage Standalone Solar PV System
Authors:   Department of Electrical and Electronics Engineering, Kongu Engineering College, Erode, India., K S* Rajesh Kumar , S Usha ,   Associate Professor, Department of Electrical and Electronics Engineering, Kongu Engineering College, Erode, India., M Karthik ,   Associate Professor, Department of Electrical and Electronics Engineering, Kongu Engineering College, Erode, India.
Published: April 2020

The inexhaustible source of energy which produced from sun through radiation and it is readily available source at free of cost. Solar Photo Voltaic (PV) systems are used as a primary source to produce power. The solar PV system needs DC-DC converter with enhanced voltage gain as well as efficiency. A typical DC-DC converter provides constrained gain and productivity as increase in requirements. For organization of battery Bidirectional converter is used which allows the energy flow in both the direction. The complete working of below voltage PV system and battery that is used are worked by using various dc converters from which the efficiency and gain level can be improved. Maximum Power Point Tracking (MPPT) is employed to receive peak power from solar PV by sustaining DC line voltage and satisfy power requirements. The perturb and observe (P&O) algorithm is mostly used to obtain the high voltage from solar PV. The entire framework is designed and simulated using MATLAB-Simulink toolbox.
Utilization of Topographic Imagery using Watershed Transformation in Watersheds Prone to Natural Disasters
Authors:   Department of Civil Engineering, Faculty of Engineering, University of Muhammadiyah Jember, Jember, 68121, Indonesia., Muhtar*  , Hanafi  ,   Faculty of Teacher Training and Education, University of Muhammadiyah Jember, Jember, 68121, Indonesia, Manggala Aditya Surya ,   Department of Civil Engineering, Faculty of Engineering, University of Muhammadiyah Jember, Jember, 68121, Indonesia., Suhartinah  ,   Department of Civil Engineering, Faculty of Engineering, University of Muhammadiyah Jember, Jember, 68121, Indonesia., Irawati  ,   Department of Civil Engineering, Faculty of Engineering, University of Muhammadiyah Jember, Jember, 68121, Indonesia., Priyono Pujo ,   Department of Civil Engineering, Faculty of Engineering, University of Muhammadiyah Jember, Jember, 68121, Indonesia.
Published: April 2020

Indonesia is an archipelago that has abundant natural resources, however, problems arise in the process of utilizing natural resources, namely the emergence of natural disasters that have the potential to cause serious damage in several areas. The threat of floods and landslides in watersheds has become the main focus to be addressed as early as possible with the best solutions and planning. The use of topographic imaging in the field of remote sensing is one solution that is very useful in developing better natural disaster management systems. With the support of the use of the watershed transformation method, this study aims to obtain geographical situation data, both from the flow dimensions and slope conditions that affect the watershed discharge capacity. Thus, the risk of natural disasters can be minimized both from the level of material and non-material damage as early as possible.
Air Quality Measurement using Computer Vision and CCTV Footage of Road Traffic
Authors:   Computer Engineering, Dwarkadas Jivanlal Sanghvi College of Engineering, Mumbai, India., Tagdiwala* Viral , Siddiqui Muhammad Umair ,   Computer Engineering, Dwarkadas Jivanlal Sanghvi College of Engineering, Mumbai, India., Shah Juhi ,   Computer Engineering, Dwarkadas Jivanlal Sanghvi College of Engineering, Mumbai, India., Bhuta Maithili ,   Computer Engineering, Dwarkadas Jivanlal Sanghvi College of Engineering, Mumbai, India., Shrivastava Kriti ,   Computer Engineering, Dwarkadas Jivanlal Sanghvi College of Engineering, Mumbai, India.
Published: April 2020

Air Quality is at a steady state of decline throughout the world. While the Indian government, in particular, has been deploying monitoring stations across multiple cities to not only monitor but also establish a cause and effect relationship when it comes to air pollution, these monitoring stations clearly, don’t suffice the actual demands for building a robust model for Air Quality Index. Our goal here is to reduce costs in terms of hardware deployment while, at the same time, provide a higher number of data points of collection on pre-existing infrastructure. The project aims at calculating the air pollution factors at the suburban level using Vehicular Emissions. The idea is to identify the number and type of vehicles from a video feed and then estimate the vehicular pollution levels using the data collected.
Design of Multi Tool Holding Attachment for Radial Drill Machine
Authors:   Asst. Professor, Mechanical Engineering Department, Dr. Babasaheb Ambedkar , College Of Engineering & Research Nagpur, Khawale* Vijay , Mandaogade Abhishek ,   Pursuing Degree, mechanical engineering, Rashtrasant Tukadoji Maharaj Nagpur University, Mishra Abhishek ,   Pursuing Degree, mechanical engineering, Rashtrasant Tukadoji Maharaj Nagpur University, Wakalkar kartik ,   Pursuing Degree, mechanical engineering, Rashtrasant Tukadoji Maharaj Nagpur University, Khobragade Mayur ,   Pursuing Degree, mechanical engineering, Rashtrasant Tukadoji Maharaj Nagpur University
Published: April 2020

In many small scale industries General Purpose radial drill machine is used for drilling. On which many jobs are performed by just changing the tool. A special table is required to place the tool. Tables consume a large floor space. To overcome this problem there is a need to design a multi tool holding attachment for radial drill machine. The main purpose of this paper is to design a multi tool holding attachment for radial drill machine. The best solution for this is use of multi tool holding attachment. Here the multiple tools holding attachment can be fixed on the column of the radial drill machine. At a time four tools can be placed on the tool holder. The attachment can revolve about the axis of the column of the radial drill machine. Installing this attachment will reduce the required of floor space. The analysis of the multi tool holding attachment was done on Ansys software. It will also reduce the fatigue to worker which is caused due to regular bending, for changing the tool. Reduction in fatigue improves the decision making quality of the worker and improve his productivity. It’s easy installation and rigid design make it durable and cost efficient.
Voice Assistant and Security based Smart Mirror
Authors:   Asst. Professor, Department of IT, MGIT, Hyderabad, India., Chaitanya* Mrs. U. , Sunayana Ms. K.V. ,   PG student, IT Department, MGIT, Hyderabad, India.
Published: April 2020

Now-a-days the internet has become more common in our lives. It can connect us more easily to information and other people in a virtual world. Mobile phones turned into smart phones and since then this concept has erupted and morphed into Internet of Things (IOT). IOT is a network of objects or things that are embedded and enables the objects to collect and exchange data. So the objects can become even smarter day-by-day. For example, mirrors provide a large surface to display information and to interact with. Everyone have mirrors at homes, schools, offices etc., thus the concept of smart mirror can be attractive and also been fantasized in futuristic movies. A smart two-way mirror is a science fiction and a part of optimistic vision of future and imagines a world which has screens and data that are available everywhere, ready to provide whatever information is needed at any moment. The main purpose of the system is to use it as a hands free product with an electronic display. When voice or camera is enabled, the smart mirror is used to view different kinds of information such as weather, time, date and news feed automatically. Voice assistant system is used to enable Google search engine, Google calendar and notifications based on user’s commands. Camera controlled system is used as a security surveillance camera. So, the voice assistant along with camera is integrated to the two-way mirror converts the functionality of normal mirror into an Interactive Smart Mirror.
Conversion of Sign Language to Text and Speech and Prediction of Gesture
Authors:   Bachelor’s Degree in Computer Science, Mathematics and Electronics., A* Bharath
Published: April 2020

People with the inability to speak, use sign language for communication. Ordinary people usually find it very difficult to communicate with mute people due to their lack of understanding of the universal sign language. This paper aims to provide a solution for this very problem through a device that uses an Arduino Uno board, some flex sensors and an Android application to facilitate interaction amongst the users. The flex sensors detect the movements and gestures of the wearer and based on the established conditions for the different values generated, respective messages are sent using a Global System for Mobile (GSM) Module to the user’s android device which translates the text message to speech. The GSM module also attempts to create parameters for gesture predictions by sending sensor inputs to a cloud-based server for future reference. The application is ever learning and continues to evolve to be more reliable by examining user behaviours at all times. The use of this device allows mute people to convert sign language to speech, thereby making it significantly easier to talk to others, especially those who do not know sign language. This device empowers mute people and opens them up to previously unattainable opportunities.
Efficient Ultra-Elastic Resource Provisioning through Hyper-Converged Cloud Infrastructure using Hybrid Machine Learning Techniques.
Authors:   Research scholar, Dept. of Computer Science VISTAS, Pallavaram Chennai, Tamilnadu, India, G* Bharanidharan. , Jayalakshmi Dr.S. ,   Professor, Department Of Computer Applications VISTAS, Pallavaram Chennai, Tamilnadu, India
Published: April 2020

Ultra-flexibility is future asset provisioning method so as to deftly meet the clients' prerequisite in powerful way. Be that as it may, more components are required for execution improvement, for example, CPU and the capacity. It is trying to decide a reasonable edge to effectively scale the assets up or down. In this paper, we propose an efficient resource provisioning using hybrid machine learning techniques (ERP-HML) that emphasis on mutually advance the vitality utilization of servers and system. Here, the proposed asset provisioning is utilized for ultra-versatile cloud benefits in hyper-joined cloud framework. In a Hyper-converged Infrastructure the resources such as CPU, storage and Network will be virtualized and software-defined as pools to meet the current demand. The principal commitment is to present an artificial plant optimization algorithm to improve the administration inertness and lessening over-provisioning of flexible cloud administrations. The subsequent commitment is to delineate a deep Q neural network (DQNN) for anticipating the server's preparing load. At that point, an improved hunting search (IHS) calculation is use to register the quantity of assets that must be provisioned dependent on the anticipated burden. The principle target of proposed ERP-HML strategy is precisely foresee the handling heap of a conveyed server and gauge the proper number of assets that must be provisioned to decrease vitality utilization. At last, the presentation of the proposed ERP-HML strategy is contrast and the current condition of-craftsmanship strategies as far as energy consumption, infrastructure costs and QoS.
Profitability of Indian Public and Private sector Banks - Empirical Evidence
Authors:   Professor, School of Business and Management, CHRIST (Deemed to be University), Bangalore, Mathew* Jain , Davis C.J. ,   Research scholar, CHRIST (Deemed to be University), Bangalore
Published: April 2020

Banking sector reforms in the last 25 years has made the Indian banking sector vibrant and strong. Banking reforms rationalized banking system by opening new private sector banks, prudential norms for quality of asset, deregulation of interest rates and digital banking. Major players in Indian banking sector are the public sector banks. Study explores fundamental profitability determinants of public and private sector banks in India. The study selected eight banks each from public and private sector banks in India for eighteen years, from year 2000- 2001 to 2017- 2018.The Global banking benchmark on profitability, ROA is considered as the dependent variable. Bank specific, Industry level and Macro level Independent variables were analyzed to find out the fundamental variables significant to the profitability of banks in public and private sector. Study uses fixed effect and Pooled OLS model to explore fundamental variables determining the profitability.
排水工艺问题和对策分析
Authors: 曲 佳乐
Published: April 2020

在新时期的快速发展中，建筑行业生产工艺呈现出新工艺、新材料、高参数的发展方向。目前，人民群众对建筑排水工程设计、施工、维修、运行和管理提出了更加严格的要求，相关部门需要引进先进的排水工艺。文章主要对排水工艺问题和对策进行了分析。
建筑工程技术管理中的控制要点与优化措施分析
Authors: 郭 锡钦
Published: April 2020

随着中国现阶段的经济条件以及技术条件的不断发展，建筑管理领域逐渐朝着更加现代化和科技化的方向发展，做好建筑工程的技术管理工作对于提升中国建筑管理质量具有重要的作用。基于此，文章首先研究了在建筑工程管理当中存在的各种问题，之后从四个方面研究了能够有效提升建筑工程技术的管理方案，并分析了建筑管理的重要意义，以供有关人士进行参考。
基于香菇切块机的设计与研究
Authors: 马 胜宾 , 张 朋 , 王 俊翔
Published: April 2020

由于香菇营养丰富，能提高机体免疫力，香菇菌盖部分含有双链结构的核糖核酸，进入人体后，会产生具有抗癌作用的干扰素。2015 年中国出口香菇近 10 万吨，同比增长 9%，产业发展潜力巨大，传统的加工方式产量低而且容易发生危险，因此，亟须一种小型机械满足中小企业的发展需求。
预防深填土区大面积地坪发生沉降的处理方法
Authors: 赵 帅
Published: April 2020

地坪的沉降将直接影响地表建筑物的安全性和稳定性，影响居民的生活。文章根据仓库现场回填土的施工情况，结合项目的特点对深填土区的沉降进行了初步分析，并采用将弱基础的加固与钢筋混凝土结构相结合的地板处理方法实现对地坪沉降的预防。
高地震烈度区高层剪力墙结构抗震设计分析
Authors: 王 晓可
Published: April 2020

河北燕郊某高层办公楼，采用钢筋混凝土剪力墙结构，场地类别Ⅲ类、抗震设防烈度为 8 度（0.3g），抗震等级为二级，抗震构造措施等级为一级，采用 YJK2.0 进行多遇地震下的结构计算分析。文章针对本工程设计中出现的难点，提出有效的解决办法，可供类似工程参考。
地铁工程施工中通信设备安装方法研究
Authors: 张 家铷
Published: April 2020

近年来，地铁工程建设规模逐渐扩大，文章分析了地铁通信设备的安装技术要点以及保障安装质量的控制方法，为相关工作提出参考意见。
岩土工程边坡的稳定性及其设计分析
Authors: 杨 锋
Published: April 2020

目前中国对于岩土边坡的施工过程还是不够完善，虽然按照地质勘探、分析设计、实际施工这种单一的思路在不断地检查勘测并改进，但是在施工过程中总会出现多样的变化，许多不确定因素带来了十分明显的缺陷。文章通过深度剖析影响边坡稳定性的各类因素，总结了几种较为常见且实用的加固及防护设计的方法。
水利工程建设管理信息化的支撑技术
Authors: 凡 晓祥
Published: April 2020

近年来，在经济技术持续发展的大背景下，有关部门加大了对水利工程技术的研究力度。在此发展阶段，水利建设的相关信息建设、管理支持技术的具体开发及应用已经成为人们比较广泛关注的话题。文章从相关技术的重要性出发，对中间件及网络技术进行了比较详细的讨论，以期更好地提高中国水利工程的具体质量。
ANALYTICAL JUSTIFICATION OF EFFICIENCY OF IMPLEMENTATION OF THE PRINCIPLES OF CORPORATE GOVERNANCE OF BANK (ON THE EXAMPLE OF JSC CB «PRIVATBANK»)
Authors: Strikha А.
Published: April 2020

The article is devoted to assessing the effectiveness of the implementation of corporate governance principles. The tools and features of the implementation of the corporate model of banking institution management were investigated. Due attention was paid to determining the quantitative impact of each principle on financial performance.
Leveraging Data Science To Combat COVID-19: A Comprehensive Review
Authors: Latif Siddique , Usman Muhammad , Manzoor Sanaullah , Iqbal Waleed , Qadir Junaid , Tyson Gareth , Castro Ignacio , Razi Adeel , Boulos Maged N. Kamel , Weller Adrian , Crowcroft Jon
Published: April 2020

COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organisation (WHO) in March 2020. At the time of writing, more than 2.8 million people have tested positive. Infections have been growing exponentially and tremendous efforts are being made to fight the disease. In this paper, we attempt to systematise ongoing data science activities in this area. As well as reviewing the rapidly growing body of recent research, we survey public datasets and repositories that can be used for further work to track COVID-19 spread and mitigation strategies.

As part of this, we present a bibliometric analysis of the papers produced in this short span of time. Finally, building on these insights, we highlight common challenges and pitfalls observed across the surveyed works.