bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Cleaning Techniques for Large Data Sets
Authors:   MCA department, Jagan Institute of Management studies, Delhi, India, Bansal Yogita , Chopra* Ankita ,   MCA department, Jagan Institute of Management studies, Delhi, India.
Published: May 2020

In today’s emerging era of data science where data plays a huge role for accurate decision making process it is very important to work on cleaned and irredundant data. As data is gathered from multiple sources it might contain anomalies, missing values etc. which needs to be removed this process is called data pre-processing. In this paper we perform data pre-processing on news popularity data set where extraction , transform and loading (ETL) is done .The outcome of the process is cleaned and refined news data set which can be used to do further analysis for knowledge discovery on popularity of news . Refined data give accurate predictions and can be better utilized in decision making process.
Impact of HRM Development: A Prospective of NCR Chain Hotels
Authors:   Research Scholar : Dr A.P.J Abdul Kalam Technical University , Lucknow , India, Kumar* Deepak , Girdharwal Dr. Nitin ,   Ph.D Supervisor & Associate Professor – Research KIET Group of Institutions , Delhi -NCR , India . Affiliated to Dr A.P.J Abdul Kalam Technical University , Lucknow , India
Published: May 2020

Human resource development playing a crucial role in the hospitality industry as the human resource department putting effort into hotel growth to recruit experienced, knowledgeable and motivational stuff to grow more and more. The HR department not only recruits the best employees, but also allow the employees to grow and shave their career.The purpose of the study is to find out how and which HR practices play an important role in increasing hotel staff satisfaction. This study focuses on a selected five-star hotel in the National Capital Region (Ghaziabad, Gurugram, Faridabad, and Noida). A Pilot study was conducted on hotel staff or employees, HR executives, managers of the hotels were interviewed. Based on these interview factors that affect hotel staff satisfaction were identified: and the questionnaire was designed for hotel employees. This study shows that most of the hotel staff are satisfied with the working conditions and somewhat the salary and other benefits that they are receiving. The employee turnover rate was observed in the hotel industry is relatively high . The management of the hotels needs to take some strong decisions.
Earthquake Prediction using Machine Learning Algorithm
Authors:   Department of Information Technology, Jayawantrao Sawant College Of Engineering, Pune, India, Banagr* Pratiksha , Gupta Deeksha ,   Department Of Information Technology, Jayawantrao Sawant College Of Engineering, Pune, India, Gaikwad Sonali ,   Department Of Information Technology, Jayawantrao Sawant College Of Engineering, Pune, India, Marekar Bhagyashree ,   Department Of Information Technology, Jayawantrao Sawant College Of Engineering, Pune, India, Patil Jyoti ,   Ph. D. Research Scholar, Department of CSE, Koneru Lakshmaiah Education Foundation (KLEF), Guntur, A.P.India.
Published: May 2020

Per the statistics received from BBC, data varies for every earthquake occurred till date. Approximately, up to thousands are dead, about 50,000 are injured, around 1-3 Million are dislocated, while a significant amount go missing and homeless. Almost 100% structural damage is experienced. It also affects the economic loss, varying from 10 to 16 million dollars. A magnitude corresponding to 5 and above is classified as deadliest. The most life-threatening earthquake occurred till date took place in Indonesia where about 3 million were dead, 1-2 million were injured and the structural damage accounted to 100%. Hence, the consequences of earthquake are devastating and are not limited to loss and damage of living as well as non-living, but it also causes significant amount of change-from surrounding and lifestyle to economic. Every such parameter desiderates into forecasting earthquake. A couple of minutes’ notice and individuals can act to shield themselves from damage and demise; can decrease harm and monetary misfortunes, and property, characteristic assets can be secured. In current scenario, an accurate forecaster is designed and developed, a system that will forecast the catastrophe. It focuses on detecting early signs of earthquake by using machine learning algorithms. System is entitled to basic steps of developing learning systems along with life cycle of data science. Data-sets for Indian sub-continental along with rest of the World are collected from government sources. Pre-processing of data is followed by construction of stacking model that combines Random Forest and Support Vector Machine Algorithms. Algorithms develop this mathematical model reliant on “training data-set”. Model looks for pattern that leads to catastrophe and adapt to it in its building, so as to settle on choices and forecasts without being expressly customized to play out the task. After forecast, we broadcast the message to government officials and across various platforms. The focus of information to obtain is keenly represented by the 3 factors – Time, Locality and Magnitude.
Dual Band Compact Hexagonal Microstrip Antenna with Quadrangular Slot and I Shaped DGS
Authors:   Electronics and Telecommunication Engineering, BMS Institute of Technology and Management, Bengaluru, Visvesvaraya Technological University, Belagavi, India., R* Banuprakash , S A Hariprasad ,   Electronics and Communication Engineering, School of Engineering and Technology , Jain University, Bengaluru, India.
Published: May 2020

Here an hexagonal printed antenna is reported. The antenna has measurement volume of 800 mm3. It operates at the frequencies 2.9 GHz, and 6.3 GHz with S11 of -10.17 dB and -14.49dB respectively. It has produced acceptable gain of 2.065dB for 2.9 GHz and 3.45dB for 6.3 GHz. The frequencies obtained are useful for aeronautical radio location and satellite applications. The antenna is designed using HFSS software and tested using ZVH vector network analyzer.
Task scheduling Algorithms in Multi cloud Environment
Authors:   Lecturer, (Integrated MCA , UTAL UNIVARSITY), Priyadarshini Aliva
Published: May 2020

One of the most commonly used technology with massive demands in the field of distributed computing is cloud computing. Cloud computing has evolved in various forms like single cloud, hybrid cloud and multi-cloud. The evolution of cloud to handle hundred and thousands of user demands, at a time, thereby facilitating resource sharing, reduction in loss of information, elimination of data storage on server side and many many more the topic of task scheduling will be prominent in all forms of cloud computing and in distributed architecture. Here, we discuss the multiple cloud architecture and the scheduling techniques applied to evenly distribute the workload across multiple clouds. Algorithms like Cloud list Scheduling (CLS), Cloud min min scheduling (CMMS), Minimum completion cloud (MCC), Median max algorithm (MEMAX), Multi-objective scheduling (MOS) are some methods suggested in the past for finding a near to optimal solution for task allocation.
An Extended Artificial Neural Network Assisted Hybrid Harris Hawks and Whale Optimizer to Find Optimal Solution for Engineering Design Problems
Authors:   School of Electronics and Electrical Engineering, Lovely Professional University, Punjab, India, Singh* Someet , Jain Anuj ,   School of Electronics and Electrical Engineering, Lovely Professional University, Punjab, India, Mahla Sunil Kumar ,   Department of Mechanical Engineering, IKJPTU, Punjab, India
Published: May 2020

The algorithms that have been developed recently have decorous behavior to solve and find optimum solution to various optimization problems in search space. Withal such calculations stuck in issues nearby quest space for compelled engineering problems. In succession to achieve an optimal solution a hybrid algorithmic approach is proffered. Artificial Neural Network (ANN) is considered as better solution for the known outputs. A hybrid variant of applying ANN on Harris Hawks and Whale Optimization Algorithm (ANNHHOWOA) is proposed to achieve effective solution for engineering problems. The effectiveness of proposed algorithm is tested for various non-linear, non-convex and standard engineering problems and to approve consequences of proposed algorithm standard benchmarks and multidisciplinary design problems have been considered. The validation endorsed that the results shown by ANNHHOWOA showed much better results than individual ANN, HHO and WOA and its effectiveness on multidisciplinary engineering problems.
A Data Mining Technique for Tourist Destination Brand Image Building
Authors:   Assistant Professor, Department of Computer Science & Engineering, CDGI, Indore, India., Kaul* Mr. Rahul , Singh Dr.Manmohan ,   Professor, Department of Computer Science and Engineering, CDGI, Indore, India., Gupta Mrs Sweta ,   Assistant Professor, Department of School of Engineering &Technology, Jagran Lakecity University, Bhopal, India., Raghuwanshi Ms. Geetanjli khambra ,   Assistant Professor, Department of Computer Science & Engineering, JLU, Bhopal, India., Pathak Mr. Prashant ,   Assistant Professor, Department of Computer Science, Jagran Lakecity University, Bhopal, India.
Published: May 2020

The destination image branding is the domain of tourism industry where the facts and information is collected and evaluated for finding the credibility of a target tourist destination. Manual collection and processing of collected information accurately is a complicated and time consuming task therefore a data mining model is suggested ,in this presented work that collect and evaluate the destination image accurately and based on evaluation can make the recommendations about visits of tourist. In order to perform this task data mining techniques are applied on text data source. In first the data is extracted from the Google search engine and it is preprocessed for make it impure. In further the data is labeled based on the positive and negative words available in the collected facts. Finally the clustering and classification of text is performed. For clustering of data FCM (fuzzy c means) clustering algorithm and for classification the Bayesian classifier is used. Based on final classification of text data the decision is made for the destination visits.
A Neural Network for Pattern Classification using Fuzzy Set Theory
Authors:   Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., D* Ms. Saranya , Akriti  ,   Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Sivakumar Oviya ,   Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India., Krishnan S.S. Sanjay ,   Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
Published: May 2020

The conventional algorithms related to the Artificial Neural Networks (ANN) have some innate shortcomings, similar to the probability of categorizing in native maximum outcome, which possess reduced speed in the learning procedure, thereby contributing to the failure in seeing a productive cell arrangement. To overcome this lacking factor, this given paper proposes a Neural Network Classifier (NNC) built combining the features of the Beetle Antennae Search (BAS) formula, termed BASNNC and Fuzzy Set Theory, which is a research and analysis proposal that can deal with problems relating to inconclusive, subjective and vague judgments. To enhance the weights of the NNC, the BAS formula is used. BASNNC consists of a three-layer structure- an input layer, a hidden layer and an output layer. The aim is to develop novel neural network that combines the significant features of Neural Network and the Fuzzy Set Theory into a common network. This process aims to get the efficient result while eliminating the errors. The objective will be to develop the system that achieves high accuracy results with the computational complexity, using the pattern classification. A pattern can be viewed physically or mathematically by the application of algorithms. To find results for a given set of observations, pattern classification is used. Quite differing from the normal technique employing the concept of gradient descent, the differences between the hidden and the output layers area are enhanced by the BAS formula, that successfully improves the process and gets the desired results. The domain used in the procedure is Artificial Intelligence (AI).
Fundamental Concepts of Driver Drowsiness Detection
Authors:   Assistant Professor, Department of Computer Science, University College of Science, Tumkur University, Tumakuru, India., B.M* Dr. Kusuma Kumari , P Dr. Ramakanth Kumar ,   Professor, Department of Computer Science and Enginerring, R.V. College of Engineering, Bengaluru, India.
Published: May 2020

Drowsiness appears in situations when one feels stressed and fatigue. It is unexpected and unfortunate, that the drowsiness may be due to insufficient sleep over night, some types of medicines used, and even, boring for drive, for example, driving continuously over a period of time. Feeling sleepy while driving may decrease the level of alertness / focus resulting in possibility of road crash or accidents. In this paper we will discussed about characteristics of driver, causes and symptoms of driver drowsiness and effects of fatigue driver.
Key Account Management: Decisions Sciences in Practice
Authors:   Management Department, Symbiosis Institute of Business Management, Bengaluru, Symbiosis International (Deemed University), Bengaluru, India., Fernandes* Semila , A Vidyasagar ,   Management Department, Symbiosis Institute of Business Management, Bengaluru, Symbiosis International (Deemed University), Bengaluru, India.
Published: May 2020

Key Account Management (KAM) has been vastly misunderstood, in not just in Indian companies but in many western companies too. India has a slew of multinationals, but they have also fallen into the trap of classifying key accounts by just sorting their accounts in a descending order and drawing a line based just on the contribution of the account to the top line. This paper will examine an alternate method of identifying and categorizing accounts and not just in the form of labels like A, B, C or platinum, gold, silver etc. Procedure: It will be our effort to examine various factors that, in addition to the value contribution to the supplier, that can be consolidated under two main criteria viz: 1) Attractiveness of the account to the supplier and 2) how attractive is the supplier to the buyer(account) under consideration. For this, we will be using a ‘modified’ GE/Shell matrix. An area, which will discuss en passant, is how do we evaluate the key accounts based on the above matrix and the way resources should be allocated for each category as a whole, and subsequently drill down to individual accounts. Implication: This paper should provide an insight to the students of management to understand an alternate way to classify their key accounts and also to the practitioners in industry to have a new look at how key accounts can be redefined.
Data Analytics Environment in Smart Industries using ML Strategies
Authors:   Assistant Professor, Dept. of CSE, Sri Venkateswara Engineering College (SVEC), Tirupati, Andhra Pradesh, India,, Sandeep* T.S. , Diwedi Himanshu Kumar ,   Assistant Professor, Dept. of CSE, Dev Bhoomi Institute of Technology, Dehradun, Uttarakhand, India, Ramana R.Venkata ,   Assistant Professor, Dept. of CSE, Sri Venkateswara College of Engineering (SVCE), Tirupati, Andhra Pradesh, India,, Prabhakar M. ,   Assistant Professor, Dept. of CSE, Sri Venkateswara College of Engineering (SVCE), Tirupati, Andhra Pradesh, India,, Rafi S.Mohammad ,   Assistant Professor, Dept. of CSE, Sri Venkateswara College of Engineering (SVCE), Tirupati, Andhra Pradesh, India,
Published: May 2020

Production is confronting significant difficulties to meet client prerequisites, always continually evolving. Along these lines, items must be made with productive procedures, insignificant interferences, and low asset utilizations. To accomplish this objective, immense measures of information produced by mechanical hardware should be overseen and investigated by current innovations. Since the large information period in assembling industry is still at a beginning period, there is a requirement for a reference design that joins huge information and AI advancements and lines up with the Industrie 4.0 guidelines and prerequisites. Right now, for planning an adaptable investigation stage for mechanical information are gotten from Industrie 4.0 measures and writing. In light of these prerequisites, a reference enormous information design for mechanical AI applications is projected and contrasted with linked facility. At long last, the proposed design is executed in the Lab Big Data Analytics at the Xblodes BigD and their versatility and execution has to be assessed on equal calculation of a modern PACA form. The benefits that are anticipated design is directly versatile and versatile AI use cases and will help with improving the modern computerization forms underway frameworks.
Micro-Level Determinants of Livelihood Diversification in The Rural Areas of Tinsukia District of India
Authors:   M.Phil. Research Scholar, Department of Economics, Dibrugarh University, Assam-786004, India., Neog* Parswa Jyoti , Buragohain Dr. Pranjal Protim ,   Associate Professor, Department of Economics, Dibrugarh University, Assam-786004, India.
Published: May 2020

Livelihood diversification is a strategy to avoid the risk associated with shocks and to improve livelihood security. Different socio-economic and demographic factors influence the decision of livelihood diversification of households. An attempt has been made in this paper to identify the determinants of livelihood diversification of the rural people using primary data collected from 255 households of Tinsukia, one of the remote districts of India. This study, by employing the logistic regression model reveals that, at less than 10 percent probability level among 11 variables, six variables namely Age of the household Head (AGEH), Type of the Family (FAMILYT) Size of the Family (FAMILYS), Monthly Per Capita Income (MPCI), Access to Credit (CREDIT) and remittance (REMIT) are significant determinant of livelihood diversification. This study will help to formulate proper development policies on the part of various concerned authorities for supporting diversification in the rural areas.
Lightweight Blockchain to Improve Security and Privacy in Smarthome
Authors:   Dept of Computer Science, New Prince Shri Bhavani Arts & Science College, Chennai, India., Sheeba* D.M. , Jayalakshmi S. ,   Dept of Computer Applications, VISTAS, Chennai, India.
Published: May 2020

Internet of Things (IoT) growing at a rate of exponential numbers in recent years has received extensive attention with BlockChain (BC) technology which provide trust to IoT with its immutable nature, decentralization in computing, resource constraints, security and privacy. The distributed ledger of transactions in BC is path leading technology for addressing Cyber Threats in the form of data theft; it provides secure application architecture which has proven track of record for securing data. IoT devices using BC enabled to communicate between objects, share data, decide based on business criteria and act as a medium to securely transmit information. This work provides lightweight BlockChain with two prominent consensus mechanism PoW – Proof of Work and PoS – Proof of Stake for smart IoT devices. Next, Smart Home Device (SMD) is ensures providing best-in-class Security and Privacy for smart home Appliances. Further provides future advances in the Approach.
A Compendium on Qos Matrices in Iot
Authors:   Department of Mathematics and Computing, College of Engineering and Technology, Bhubaneswar, Odisha, India., Pattnaik* Dr P. K. , Lenka Stitapragyan ,   Department of Computer Science and Application, Utkal University, Bhubaneswar, Odisha., Prdhan Dr. Sipali ,   Faculty, Department of Computer Science, RBVRR WHyderbad, India., Pradhan Dr.Sateesh ,   Department of Computer Science and Application, Utkal University, Bhubaneswar, Odisha., Mishra Dr.Sujogya ,   Department of Mathematics and Computing, College of Engineering and Technology, Bhubaneswar, Odisha, India.
Published: May 2020

The Internet of Things (IoT) has turned out as an emerging technology with an aim of simplifying and easing human life by automating most of the day to day activities with wide range of applications in different domains. QoS indicates how offered service qualities are? Computing, Communication and Things are the major components of IoT. It comprises of heterogeneous elements such as RFID, sensor, Wireless Sensor Network, mobile network, cloud services. For desirable service provisioning and popularizing IoT applications, QoS parameters for IoT are very essential. This papers aims at providing a review work done by different researchers about the QoS parameters for IoT applications, transmission network and perception.
Emotion Detection with Single Channel EEG Signal using Deep Learning Algorithm
Authors:   Research scholar, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, Maharashtra, India, Joshi* Vaishali M. , Ghongade Dr.R.B. ,   Professor, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, Maharashtra, India
Published: May 2020

Today’s young generation is tormented by anxiety and stress. A past study shows that, anxiety and stress negatively impact mental and physical health, which ultimately ends up in loss of confidence, self-esteem, and negative performance. This work set guidelines for a replacement approach in neuroscience that only single-channel EEG data has sufficient information for emotion recognition. In this paper, the performance of system is evaluated using subject independent test on the SEED benchmark database using deep learning algorithm namely a bidirectional long short term memory (BiLSTM) classifier. The performance shows that results of single-channel FP1, the combined band (theta, alpha, beta, and gamma) are similar to 62 channels the best accuracy of the beta band. Result obtained for single channel (FP1) using differential entropy (DE) for all band is 74.91% as that of the highest accuracy of the beta band for 62 channels Yang Li, W. Zheng, 2019 74.85%.
Digital Food ordering system based on Spring Framework
Authors:   Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India, Karthik* Mr.R. , Sridhar T.S. ,   Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India., Sriram R. ,   Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India.
Published: May 2020

As people nowadays engage themselves in busy schedules they skip their meals just because they have to go somewhere for food. So to avoid these, applications like Zomato, swiggy,and foodpanda need to be efficient and be able to order multiple items from multiple restaurants in a single order. Food orders from mobile devices are common nowadays, and they can help consumers order food more easily and efficiently. It can also give manufacturers and consumers full benefit. This allows the consumer to get the advantage of delivering food online. This research used a quantitative approach with 187 respondents to find out what stimulus variables important people in the online supply order.In existing systems, only order is placed in a single grocer. With this system we can place orders for multiple grocers.Apps are limited to mobile phones where this web application is accessed across various devices like mobile phones, PC , PDA ,tablets etc.
Methods to Improve the Spray Characteristics of n-Butanol by Visualization of Spray in a Port Injector
Authors:   SMEC, Vellore Institute of Technology Chennai, Chennai, India., Kumar* Praveen , Hirwani Ashish Kumar ,   SMEC, Vellore Institute of Technology Chennai, Chennai, India., Gupta Manshu ,   SMEC, Vellore Institute of Technology Chennai, Chennai, India., Kumar. R. Siva ,   SMEC, Vellore Institute of Technology Chennai, Chennai, India., Venugopal T. ,   SMEC, Vellore Institute of Technology Chennai, Chennai, India.
Published: May 2020

Generally, fossil fuels are non-renewable and depleting day by day. The usage of renewable fuels reduces global warming. Alcohols are renewable in nature and used in SI engines due to their good combustion properties like antiknock and flame velocity. Ethanol, methanol, and butanol are commonly used alcohols. Ethanol is widely used in countries, where it is abundant. Butanol is gaining more attention due to its combustion properties being similar to gasoline and its corrosion less behavior when compared to ethanol. Butanol injection in the intake port through port injectors will form a plume, which leads to high emission. The high viscosity of butanol is the reason behind such plume which is the major cause of poor vaporization, less fuel efficiency, and high hydrocarbon emissions. Methods like heating of butanol to high temperatures, increasing the injection pressure and blending of butanol with less viscous fuels like gasoline and ethanol can be accomplished to obtain a better fuel spray. This particular work reveals the visualization of the spray of butanol with different fuel temperatures, injection pressure and the blending of butanol with gasoline and ethanol. Further, it can be a knowledge base for utilizing renewable butanol effectively in automotive engines for achieving low emission and high fuel efficiency.
Project Ratification System using Firebase
Authors:   Student, Department of Computer Science and Engineering Mahatma Gandhi Institute of Technology, Hyderabad, India, Pulipati* Jagruthi , Gopi Arepalli ,   Assistant Professor, Department of Computer Science and Engineering Mahatma Gandhi Institute of Technology, Hyderabad, India, Krishna R. Mohan ,   Assistant Professor, Department of Computer Science and Engineering Mahatma Gandhi Institute of Technology, Hyderabad, India
Published: May 2020

The main objective and scope of this project are to overcome the practical problem of project submission and approval in educational institutions. This will cut down the physical efforts of students, staff and also the time frame period of completing this part of the project work. Students can streamline their project status every week and provide a report regarding the progress, which will be monitored by all the relevant professors. The application provides an interface to both the faculty and students to easily communicate about the project work with no difficulties. This portal integrates numerous features like student updating the progress of their project online to their guide; where the guide can verify it and can accept/reject the students' note; this response would be reflected in each student's dashboard; a guide can also post the information about his mentees weekly progress to the class in charge. This portal prominently serves as a repository of students' work as they are presenting in one place, and this reduces a lot of actual toil for both students and faculty. Thus, thereby automating the process of project management in educational institutions. This implementation can be achieved by making use of android application development tools like the Android Studio IDE, Java JDK, SDK tools and an emulator or a smartphone to test the working of this application. We make use of Google's Firebase for back-end support which allows us to build applications that need authentication, database, file storage, and server-side functionality without having to hold and handle infrastructure and software needed for server-side support.
Analysis of the Reliability of the Butter-Oil Processing Plant using CAS Mathematica and Maxima
Authors:   Research Scholar, Department of Mathematics, J. C. Bose University of Science and Technology, YMCA-121006, Faridabad (Haryana-India)., Jindal* Shalini , Garg Dr. Reena ,   Assistant Professor, Faculty of Sciences (Department of Mathematics), J. C. Bose University of Science and Technology, YMCA-121006, Faridabad (Haryana)-India., Garg Dr. Tarun Kumar ,   Associate Professor, Satyawati college, University of Delhi, Delhi-India.
Published: May 2020

The aim of the present paper is to analysis the reliability of the system by using CAS Mathematica and also, it’s comparative study with CAS Maxima. The butter oil manufacturing plant consists of seven units i.e. separator, pasteurizer, continuous butter making, melting vats, butter oil clarifier, packaging and standby state. Model is developed by using Markov birth-death process. The first order differential equations are derived by using model and then solved for comparative study of reliability to give accuracy in result. By using Mathematica, we calculate probability of each state, which is beneficial to plant owners because better accuracy in result enhance reliability of the plant Graphs are plotted and tables are developed with the help of CAS Mathematica and Maxima, graphs show the variation and tables shows the fluctuations in reliability in comparative manner.
Hazard Identification, Risk Assessment and Risk Control in Chemical Industry
Authors:   Department of Management, Faculty of Economics, Bhayangkara JakartaRaya University, Bekasi, Indonesia., Panday* Rorim , Rachmat Basuki ,   Department of Management, Faculty of Economics, STIE Perbanas Surabaya, Indonesia.
Published: May 2020

This study was aimed at identifying hazards through risk assessment and risk control by using HIRARC method in the warehouse of Company XYZ (a pharmaceutical company). Data was collected through direct observations, documentations, and interviews. The study found that Company XYZ identified 104 hazards in the year 2017, which were caused by poor working environment, worker attitudes, manual work, tools and machinery. This study revealed 57% of the total risks fall in medium category, 38% high, 5% low, and none of them are categorized under extreme risk. To control the risk, the company has been taking proactive actions through the elimination of risks, engineering, administration and Personal Protective Equipment (PPE).
Automating the CFD analysis of Reefer Truck using PyFoam
Authors:   Assistant Professor, Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University, Bangalore-560074, India., R* Thejaraju , Rego Anil Melwyn ,   Assistant Professor, Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University, Bangalore-560074, India., Joseph Sonal P ,   Research Scholar, Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University, Bangalore-560074, India., Patel Smit Vishal ,   Assistant Professor, Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University, Bangalore-560074, India., BC Tarun ,   Assistant Professor, Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University, Bangalore-560074, India.
Published: May 2020

CFD turned into an alluring and engineering practice utilized in the design and assessment procedure in automotive and food industries. Nowadays, open source solvers are great in demand as the small-scale industries doesn’t want to invest too much into it. On the CFD OpenFOAM software front it has the capacity to handle a mutli-physics problem with respect to commercial and industrial needs. OpenFoam solver is one great example which is a C++ encoded numerical tool to solve various fluid flows and heat transfer processed under lot of differential equations where the analyzer has to scratch his head to get the output. The present study involves round the designing and analyzing an OpenFoam CFD model of a Reefer truck chamber where the temperature and velocity variations were studied. The truck chamber is investigated by varying different inlet angles and changing the positions of outlet duct. And thereby automating the whole CFD process with the help of PyFoam which is an interface of Python scripting embedded with OpenFoam wherein helping the vendors or customers to directly input the coolant temperature and the inlet angle. The inlet angle at 20 degree and 45 degree was verified with the python code to conclude the CFD simulation on the reefer truck.
Energy Efficient Mobility Aware Clustering Hybrid MAC Protocol in WSN
Authors:   ECE department, Assistant Professor, JNTUHCEH, JNTUH University, Hyderabad, India., Rajesh* M. , Raju B.L. ,   ECE department, Professor and Principal, ACE Engineering College, JNTUH University, Hyderabad., Bhandari B.N. ,   ECE department, Professor, JNTUHCEH, JNTUH University, Hyderabad
Published: May 2020

Mobility in Wireless Sensor Networks (WSN) poses many challenges to design Medium Access Control (MAC) protocol. In this paper, Energy efficient clustering Mobility Hybrid MAC (EMH-MAC) protocol is introduces to manage throughput, delay and energy consumption in WSN. EMH-MAC protocol merges the features of synchronous and asynchronous MAC protocols. EMH-MAC works in two stages: Clustering and Data transmission stage. In the clustering stage MMCDD protocol is used for election of Cluster Head (CH). Data transmission stage works in four segments: two-hop neighbor information, intra-semi synchronous, inter-synchronous communication and data transfer. EMH-MAC is evaluated using Network Simulator-3 and performance is compared with BN-MAC. Simulation results show that EMH-MAC performs well in comparison with BN-MAC in terms of throughput, delay and energy consumption by varying number of nodes and speed of nodes.
The Opportunities and Limitations of Human Computer Interaction in Virtual and Augmented Reality
Authors:   Student, Department of Computer Science, Northern Illinois University, DEKALB, USA., Musunuru* Gopi Vinyas
Published: May 2020

Virtual Reality, Augmented Reality and other such immersive environments have gained popularity with the increase in technological trends in the past decade. As they became widely used, the human computer interface design and the designing criteria emerges as a challenging task. Virtual and Augmented Reality provide a wide range of appli-cations ranging from a primitive level like improving learn-ing, education experiences to complex industrial and medical operations. Virtual reality is a viable alternative that can be focussed on, in the future interface design development be-cause it can remove existing generic and complex physical interfaces and replace them with an alternative sensory re-layed input form. It provides a natural and efficient mode of interaction, that the users can work with.Virtual and Aug-mented reality eradicates the need for development of differ-ent acceptable standards for user interfaces as it can provide a whole and generic interface to accommodate the work set-ting.In this paper, we investigated various prospects of appli-cations for user interaction in Virtual and Augemnted reali-ties and the limitations in the respective domains. The paper provides an outline on how the new era of human computer interaction leading to cognition-based communications, and how Virtual and Augmented realities can tailor the user needs and address the future demands which replaces the need for command-based interaction between the humans and com-puters.
Efficient key Management System using Channel Response in Wireless Sensor Network
Authors:   Research Scholar, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai,TamilNadu,600119,India, G* Manikandan , U Sakthi ,   Professor, Department of Computer Science and Engineering,St.Joseph’s Institute of Technology, Chennai, TamilNadu India.
Published: May 2020

There are challenges abound for key management in wireless sensor networks. The importance of key management gets highlighted when the network gets scaled up without the availability of enough resources and new kind of threats in the form of node capture emerge. The economic viability of such schemes are usually high as the increase in security is directly proportional to the computational complexity, thus attributing to the high cost. In the wireless sensor infrastructure, nodes get connected with each other in wireless medium and can enter and exit the network at their will. Such aspect of entering and exiting paves the way for malicious nodes too to enter in to the network, making the entire network vulnerable to several types of attacks. One of the prominent attack is network jamming where the transmission lines gets jammed blocking the free flow of data as well as corrupting it. Such attacks on node and data transmissions can be avoided by increasing the security afforded to the entire WSN. In this regard, a novel key generation algorithm has been proposed in this paper using channel response technique, where the data hops from one channel to another in its transit from the source node to the destination node securing it from attacks. The Leap and Stop algorithm has been applied for channel hopping thus ensuring that the data traverses only for a small duration in each channel before hopping to the other channel. The channel hopping technique minimizes the probability of attack since before an active channel could be successfully predicted by the attacker, it becomes inactive and another channel gets activated. This channel hopping process continues till data reaches the destination safely without getting corrupted. The proposed approach had been compared for its efficiency and performance with Secure Key Generation using Frequency Selective Channels (SKGFSC) protocol and the results had been shown therewith.
Comprehensive Analysis of Jet Flocculator in Square and Circular Basin
Authors:   Assistant Professor, Department of Civil Engineering, KDK College of Engg., Nagpur, India, Randive* P.S. , Singh D.P. ,   Principal, K.D.K. College of Engineering, Nagpur, India, Bhole A.G. ,   Ex-Emeritus Professor, Department of Civil Engineering, VNIT, Nagpur, India, Varghese V.P. ,   Professor, Department of Civil Engineering, KDKCE, Nagpur, India
Published: May 2020

The demand for better quality drinking water gives inspiration for advancement in the functioning of water treatment processes. Jet mixing technology, widely adopted in Flocculation process is unique due to its advantages over mechanical stirrer or vanes. Jet flocculator take primacy, as it do not have any moving parts inside the reactor. The present experimental investigation focuses on the examination of jets in flocculation. Comprehensive study of various parameters such as nozzle diameter, angle of inclination, flow pattern and jet position in two geometrical shapes of flocculation chamber: Square and Circular. Effect of tank shapes on flocculation process is analysed and compared.
Smart Air Fertigation (SAF) without using Fertilizers through Air Irrigation for Sustainable Agriculture
Authors:   MCA Department, Thakur Institute of Management Studies, Career Development & Research affiliated to University of Mumbai, Mumbai, India., Gaikwad* Dr. Vinita , Mudholkar* Pankaj ,   MCA Department, Thakur Institute of Management Studies, Career Development & Research affiliated to University of Mumbai, Mumbai, India., Khake Manohar ,   Agricultural Consultant, Pune, India.
Published: May 2020

In India approximately 80% of the total water is consumed for agriculture. India does not spend any money in conserving water consumed in agriculture. In the current scenario humans are concerned about potable water, more and more insufficient in relation to the increase of the population and as effect of pollution. Crops are watered using various irrigational methods with the ground water. Water consumption in irrigation also depends upon the crop which is cultivated. Sugarcane and rice cultivation consumes nearly 60% of the irrigation water. Further to ensure a bumper produce, farmers are encouraged to use chemical fertilizers. Many of these fertilizers give a promising crop produce but the after effects of consumption of such chemically treated produce leads to harmful effect on human health. Nevertheless, quite a many farmers are now focusing on Organic method of farming wherein chemical fertilizers are totally avoided. However, the produce under this method does not give a bumper crop produce. To tackle the problem of water waste during irrigation process, techniques like drip irrigation, dry farming, irrigation scheduling, and Smart irrigation using Information Technology are applied to ensure least wastage of irrigated water at the same time providing desirable conditions for bumper crop produce. To provide an alternate solution for reducing water wastage in irrigation and providing natural fertilizers to the crops, this research paper suggests the use of Smart Air Fertigation (SAF) without using fertilizers with the aid of Air Irrigation method. Further, by using various IT tools and sensors it is possible to provide Smart Air Fertigation system which will also help reduce labor and will be less time consuming.
Iceberg Detection in Satellite Images using Deep Learning Techniques
Authors:   M.Tech, Department of Computer Science and Engineering, V R Siddhartha Engineering College, Vijayawada., Naveena* Aravapalli , Prasad J.V.D. ,   Pursuing Ph.D, Acharya Nagarjuna University
Published: May 2020

Iceberg detection is found to be more critical in the previous researchers. High quality satellite monitoring of dangerous ice formations is critical to navigation safety and economic activity in the regions. The satellite images play a crucial role in the identification of the icebergs. In this manuscript, a convolutional neural network (CNN) model is proposed for the iceberg detection from the satellite images. It is based on the satellite dataset for target classification and target identification. The iceberg detection is based on the statistical criteria for finding the satellite images. This model is used to identify automatically whether it is remote sensed target is iceberg or not. Sometimes the iceberg is wrongly classified as ship. This model is done to make accurate about the changes in the detection.
Marketing Strategy using SWOT and QSPM Methods
Authors:   Department of Chemistry, Faculty of Technique, Bhayangkara JakartaRaya University, Bekasi, Indonesia., Saing* Bungaran , Wulandari Eni ,   Department of Industry, Faculty of Technique, Bhayangkara JakartaRaya University, Bekasi, Indonesia., Panday *Rorim ,   Department of Management, Faculty of Economics, Bhayangkara JakartaRaya University, Bekasi, Indonesia.
Published: May 2020

Hijab Alila (HA) is one of the Muslim fashion brands in Indonesia. This brand has 52 distributors to distribute its products to all customers in Indonesia, one of which is the Karawang distributor. In carrying out its distribution in the Karawang region, this distributor had internal and external constraints. The purpose of this study is to determine the company's external and internal environmental factors and find out appropriate alternative strategies. The method used are SWOT and QSPM. The data used are secondary and primary data. Secondary data were obtained from company data, literature studies, books, internet, and journals. While the primary data obtained from the questionnaire, interviews and observation. Based on the results of data processing, it is found that the value of the internal matrix is 3.15 and the value of the external matrix is 2.71. Then for the results of the IE matrix, it is found that the Karawang distributor occupies position IV which is called the growth and develop the position. In this position, the company carries out market penetration strategies, market development, and product development. Then for the results of QSPM, the company is advised to promote the product through as many social media accounts in the most possible creative way to reach a wider and more market.
A Novel Method for Real Time Recognition of Facial Expressions using Machine Learning Techniques
Authors:   CSE, V R Siddhartha Engineering College, Vijayawada, India., Pushpa* Aakula Sharon , Rao Dr. Duvvada Rajeswara ,   CSE, V R Siddhartha Engineering College, Vijayawada, India.
Published: May 2020

In the real-life situation, facial expressions and feelings are nothing more than responses to human external and internal events. In human computer association, acknowledgment of end client's demeanors and feelings from the video gushing assumes significant job. In such frameworks it is required to follow the dynamic changes in human face developments rapidly so as to convey the necessary reaction framework. The one constant application is physical exhaustion location dependent on facial discovery and articulations, for example, driver weariness recognition so as to forestall the mishaps on street. Face appearance based physical weariness investigation or location is out of extent of this paper, however this paper uncovers concentrate on various techniques those are introduced as of late for outward appearance as well as feelings acknowledgment utilizing video. This paper introducing the procedures as far as highlight extraction and arrangement utilized in outward appearance as well as feeling acknowledgment techniques with their near investigation. The relative examination is done dependent on precision, usage apparatus, preferences and hindrances. The result of this paper is the ebb and flow explore hole and research difficulties those are as yet open to illuminate for video based facial discovery and acknowledgment frameworks. The review on ongoing strategies is properly introduced all through this paper by considering future research works.
Women Safety Prediction using Logistic Regression Model
Authors:   Student, Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P, Swaraj* V. Sushma , Bhavya L. ,   Asst. Professor (Adhoc), Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P,, Pooja G. ,   Student, Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P, Revathi R. Deva ,   Student, Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P,
Published: May 2020

Safety of Women has become a major issue in India. Especially at night women think a lot before coming out of their homes. We daily come up with news of how women are subjected to a lot of violence and harassment or get molested in public areas. This paper focuses on the issue of helping Women that they don’t ever never feel alone in the middle of any situations. The project idea is to predict whether the given place at any time is safe for a women to go or not. There are many pre-existing applications that are useful at the time of crisis situations. At some situations when a women is in trouble, she is not able to use those applications. And there are also so many rehabilation centres which are used after the situation has happened. But our proposed model will help women to take precautions so that they never ever get that situation. For this idea we used Machine Learning. Machine learning is used to train the data and make quality predictions by recognizing the patterns in data. We applied different algorithms like Naïve Bayes, K-Nearest Neighbours, Logistic Regression models. Logistic regression is the best fit among other machine learning algorithms and it is more effective than others. In this paper, we used Logistic regression algorithm of Sklearn machine learning library to classify the dataset. Information about some set of areas in Tamilnadu are collected and was used in our project. When a women alone want to go out for any personal work or any financial work without knowing any safety details about the place she wants to go our application helps more better.