bluuebunny/crossref_metadata_2025 huggingface dataset:
Nova Genesis - An Advanced Architecture for Internet of Things
Authors:   Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India, P A Ajumol , Isaac Elizabeth ,   Assistant Professor, Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India
Published: June 2020

The Internet has become the most important medium for information exchange and the core communication environment for business relations as well as for social inter- actions. The current internet architecture itself might become the limiting factor of Internet growth and deployment of new applications including 5G and future internet. Architectural limitations of internet include weak security, lack of efficient storage and caching, data distribution and traceability issues, lack of interoperability and so on. The proposed system overcomes these limitations by an alternate architecture for internet called NovaGenesis. This architecture integrates the concepts of Infor- mation Centric Networking (ICN), Service Oriented Architecture (SOA), network caching and name based routing. ICN evolve internet from a host-centric model to a content-centric model through efficient data exchange, storage and processing. SOA enables software-control/management of network devices based on service requirements. Network caching improves performance in terms of throughput, network traffic and retrieval delay. Name based routing is for discovering and delivering of data. The framework proposed increases the scalability and reliability of the delivery of IoT data for services.
Assessing the Market Potential of Home-Made Masala and Spice Powder
Authors:   Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India., L.* Harishma Vijay , M Dr Dhanya ,   Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India., Sudarsan Anupama ,   Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
Published: June 2020

This paper aims at assessing the consumer choice for masala (Homemade/ Ready-made powder) for home cooking in Trivandrum City in the state of Kerala, India. Kerala is popularly known as the "King of Spices," the leading producer of black pepper, enjoying a pride of place among all the spice producers. From the analysis made by us it is clear that people choose home-made forms of masala rather than ready-made ones. The reasons behind this are clearly studied in this paper. The target market is identified and segmented. Geographic segmentation is done by dividing the entire Trivandrum city into 12 major locations. Socio-demographic segmentation was also done on the basis of age, gender and income. Descriptive research design is being employed for the study. The data is collected using survey method by self-administering questionnaire or survey instrument. This paper is mainly divided into two main parts. The first part talks about the relationship between certain demographic factors like age, income and gender with the choice of masalas. The sample size is 300 and a Chi-square test of independence is done using SPSS tool. The second part talks about the reasons why people prefer home-made forms compared to ready-made forms of spice and masala powders. For this the sample size was 121 respondents. The analysis is done using Voyant tool. Text mining approach has been adopted. From the results it is clear that there is no significant correlation between the demographic factors considered and the choice made. Most of the respondents prefer to use home-made spices and masala powders as they consider it to be not adulterated. The two major factors driving the growth of the global organic food & beverage market are the number of health-conscious customers and growing awareness of the health benefits associated with organic spice consumption. Health is an important aspect considered in the case of spice powders and masala. People do not tolerate adulteration and hence they tend to choose the traditional methods of making masala powders over the ready-made forms available in the market today. This study would help the marketers to know the market potential and also to understand the consumer needs in case of spices and masala powders.
Smart Vehicle Registry using IOT and Image Processing
Authors:   Assistant Professor, Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India., Gayathri* D. , Gourav G. ,   UG Student, Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India., Sudharshan M. ,   UG Student, Department of Information Technology, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India
Published: June 2020

In the current technological era, everything is getting automated through various technologies. There always remains a need for a Smart Vehicle Registry with optimized performance and zero human interference. This paper deals with such a system by incorporating RFID (Radio Frequency Identification) technology and Image Processing into a single automated system that registers every vehicle and the person driving the vehicle entering into a specific zone. This paper outlines a survey on various works that had been done on the field of RFID and Image processing. The proposed system deals with an RFID system that can be used to scan the person driving the vehicle and an Image processing system which consists of a camera and an open source library to scan and record the vehicle registration plate number and a front end to manage the input and output flow of the system. The system discussed in this paper is created in such a way the analysis can be easily performed on the output data. This paper also discusses the various outcomes and futuristic works that can be performed to improve the system.
A Reversible High-Capacity Data Hide System Based on Powerful MSB Prediction in Encrypted Images
Authors:   School of Computing and Information Technology, REVA University, Bengaluru, Karnataka, India., V Raghavendra , G C Satish ,   Associate Professor, School of Computing and Information Technology, REVA University, Bengaluru, Karnataka, India.
Published: June 2020

For encrypted images (RDHEI) reversible data shielding is an important technique for embedding data into the encrypted domain. A hidden key encrypts an original picture, and additional information may be inserted into the encrypted image during or after transmission without knowing the crypting key or the original contents of the picture. The hidden message can be retrieved during the decoding process and the original image can be restored. RDHEI has begun to generate academic attention over the past couple of years. Data privacy has become a real issue with the growth of cloud computing. None of the current methods, however, will allow us to hide a great deal of information reversibly. In this document we propose a new reversible approach with a very high capacity based on MSB (most important bit) forecasting. We present two approaches: a reversible high-capacity data hiding approach with a prediction-correction error (CPEHCRDH) and an integrated-prediction error (EPE-HCRDH) reversible data hiding approach. With this approach, our findings are better than those achieved with the existing state-of-the-art approaches, both in terms of image quality recovered and embedding efficiency.
Exploring the methods on early detection of Alzheimer's disease
Authors:   Electronics and Communication Department, Sri Jayachamarajendra College of Engineering, JSS Science and Technology University, Mysuru , Karnataka, India., Kumari B A Sujatha , Shetty M Charitha ,   Electronics and Communication Department, Sri Jayachamarajendra College of Engineering, JSS Science and Technology University,Mysuru, Karnataka, India, H M Lakshitha ,   Electronics and Communication Department, Sri Jayachamarajendra College of Engineering, JSS Science and Technology University, Mysuru , Karnataka, India., Jain Mehulkumar P ,   Electronics and Communication Department, Sri Jayachamarajendra College of Engineering, JSS Science and Technology University, Mysuru , Karnataka, India., S Suma ,   Electronics and Communication Department, Sri Jayachamarajendra College of Engineering, JSS Science and Technology University, Mysuru , Karnataka, India.
Published: June 2020

Alzheimer’s disease (AD) is a disorder which is said to be irreversible and affects the behavior and cognitive processes which will eventually affect the memory. This disease beget difficulty in performing the daily task of a patient. It is one of the most common form of dementia affecting people above the age 65 and the risk increases with age. The treatments currently available can only mitigate AD progression but there is no treatment to stop this progression. To bring down the progression of AD early detection becomes necessary. Researchers have found that many machine learning (ML) methods have been useful in detection of AD. Machine learning is a part of artificial intelligence involving probabilistic and optimization techniques such as neural networks that prepares pc's to gain a model from complex datasets. This paper Scrutinizes the developments taken in the field of ML for the possibly early diagnosis of AD. It discusses about various approaches used in recent times for the detection of AD at an early stage. Through this research we found several classification methods such as Recurrent neural networks(RNN), Convolution neural networks(CNN), many more binary and multiclass classifiers along with various methods of preprocessing steps involved in the detection of AD. This paper also throws light on the datasets being used and how these preprocessing steps and different classifiers attribute to increase of accuracy in prediction of AD. Finally, coming to the objective of this paper is to analyze and evaluate these different techniques of ML contributing for the detection AD as early as possible and also to help the researchers to get maximum information and comparison of techniques in one go.
Detecting Malicious Apps in Android Devices using SVM, Random Forest & Decision Trees
Authors:   Student, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Hyderabad, India, Sanjana E. , Sagar M. Srikanth ,   Assistant professor, Department of Computer Science And Engineering Mahatma Gandhi Institute of Technology, Hyderabad, India, Nalla Deekshitha ,   Student, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Hyderabad, India, Meghana Bonthu ,   Student, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Hyderabad, India, Katragadda Anusri ,   Student, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Hyderabad, India
Published: June 2020

In recent years, the usages of smart phones are increasing steadily and also growth of Android application users are increasing. Due to growth of Android application user, some intruder are creating malicious android application as tool to steal the sensitive data. We need an effective and efficient malicious applications detection tool to handle new complex malicious apps created by intruder or hackers. This project deals with idea of using machine learning approaches for detecting the malicious android application. First we have to gather dataset of past malicious apps as training set and with the help of Support vector machine algorithm and decision tree algorithm make up comparison with training dataset and trained dataset we can predict the malware android apps upto 93.2 % unknown / New malware mobile application. By implementing SIGPID, Significant Permission Identification (SIGPID).The goal of the sigid is to improve the apps permissions effectively and efficiently. This SIGPID system improves the accuracy and efficient detection of malware application. With the help of machine learning algorithms such as SVM, Random Forest Classifier and Decision Tree algorithms we make a comparison between training dataset and trained dataset to classify malicious application and benign app.
Overcoming of Poverty and Inequality as Condition of Steady Social Development of Regions
Authors:   Associate Professor of Management Department, Borisovna* Burenina Nataliya
Published: June 2020

For maintenance of economic security steady dynamic development of the system, permanent height of standard of living of population, is needed in a country, regardless of affecting her unfavorable external and internal factors. The basic problem of steady social development of regions is an unsolved to present tense problem of poverty and inequality. The aim of the real article is research of social development of Russia in a dynamics by realization of comparative analysis of quantitative indexes of level of poverty in a country and in her separate regions, level of inequality, exposure of reasons of decline of standard of living of population and development of recommendations on overcoming of poverty and inequality, height of welfare of population. The dialectical method of research of processes and phenomena, analysis of the systems and comparative, method of expert estimations, methods of groupment, tabular, abstractly-logical method, synthesis, is in-process used. As a result of undertaken a study of social development of Russia it is educed the method of expert estimations a standard of living of population is at low level and is the serious threat of economic and social security of country. 10 is educed the most poor regions of Russia, where the level of poverty makes the fourth of population of these regions practically, and in separate regions he makes a to 40% population from 30%. The problem of social inequality, that arose up after disintegration of the USSR and remains extremely actual for modern Russia, is certain major reason of falling of standard of living of population. On results an analysis drawn conclusion about the necessity of structural alteration of economy, changing of economic model of development of Russia on the whole. Recommendations worked out by an author on overcoming of inequality and poverty, driven to work, will assist perfection of socio-economic regional development of Russia, and also steady social development of regions.
Customer’s Attitude, Preference and Buying Behavior towards Organic Food using Fishbein Multi-Attribute Model
Authors:   Department of Management, Kochi, Amrita Vishwa Vidyapeetham, India., H Vijith
Published: June 2020

Organic food are often seen as nutritious, healthy and eco-friendly. With the change in lifestyle, people are more becoming more concerned towards healthy food. Due to this change, people are now turning towards organic food. The aim of this research is to understand the attitude of people towards organic food, the factors that influence people's desire for and purchasing behaviour towards organic food using Fishbein Multi-Attribute Model . With the results achieved, we can understand the preference and attitude of the customers and the factors that drive the customers in buying the organic food.
Analysis on Fake News Detection Methodologies
Authors:   Department of Computer Science and Engineering, LBS Institute of Technology for Women, Trivandrum, India., R Vaishnavi , S Anitha Kumari ,   Department of Computer Science and Engineering, LBS Institute of Technology for Women, Trivandrum, India.
Published: June 2020

Fake news is a coinage often used to refer to fabricated news that uses eye-catching headlines for increased sales rather than legitimate well-researched news, spread via online social media. Emergence of fake news has been increased with the immense use of online news media and social media. Low cost, easy access and rapid dissemination of information lead people to consume news from social media. Since the spread rate of these contents are faster it becomes difficult to identify the fake news from the accurate information. People can download articles from sites, share the content, re-share from others and by the end of the day the false information has gone far from its original site that it becomes very difficult to compare with the real news. It is a long standing problem that affects the digital social media due to its serious threats of misleading information, it creates an immense impact on the society. Hence the identification of such news are relevant and so certain measures needs to be taken in order to reduce or distinguish between the real and fake news. This paper provides a survey on recent past research papers done on this domain and provides an idea on different techniques on machine learning and deep learning that could help in the identification of fake and real news.
Effect of Variable Tube Wall Thicknesses of Al-Mg-Si Alloy Tube During Electromagnetic Compression using Four Turn Axi-Symmetric Coil
Authors:   Research Scholar, Department of Mechanical Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal-462003, India,, Shrivastava Amitabh , Telang Amit ,   Assistant Professor, Department of Mechanical Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal-462003, India, Jha A.K. ,   Chief Scientist, Advanced Materials and Processes Research Institute (AMPRI) Bhopal- 462026, India
Published: June 2020

Electromagnetic compression (EMC) is a solid state, high velocity process of deformation of materials. In this process the enhancement of the formability is achieved due to high strain rate forming. In the present study Aluminum alloy AA6061 tube has been compressed using four turn axisymmetric coil. The effect of variable tube wall thicknesses i.e. 1.0, 1.7, and 2.4 mm during the compression of the Al-Mg-Si Aluminum alloy tube electromagnetically has been studied. A constant gap between coil inner diameter (ID) and workpiece outer diameter (OD) was maintained. It has been found that the tube deformation was maximum when the wall thickness was minimum. For compression, 8 kJ energy was used with double power bank. A three dimensional (3D) model of four turn compression coil has been proposed using LS-DYNA software. Comparison between the numerical simulation and experimental results showed a close agreement between both the results. Compression using EMF process can be used in modern industries like automotive, aerospace and nuclear power plants.
Low Frequency Noise Remove from EEG Signal
Authors:   Student, B. Tech, Electronics and communication Engineering from Galgotias University, Greater Noida, Uttar Pradesh., Kumar Awnish , Tiwari Rahul ,   Student, B. Tech, Electronics and communication Engineering from Galgotias University, Greater Noida, Uttar Pradesh, Gaur Abhilash ,   Assistant Professor, Electrical, Electronics and Communication Engineering, Galgotias University, Greater Noida, India.
Published: June 2020

The electrical activity of the brain recorded by EEG which used to detect different types of diseases and disorders of the human brain. There is contained a large amount of random noise present during EEG recording, such as artifacts and baseline changes. These noises affect the low -frequency range of the EEG signal. These artifacts hiding some valuable information during analyzing of the EEG signal. In this paper we used the FIR filter for removing low -frequency noise(<1Hz) from the EEG signal. The performance is measured by calculating the SNR and the RMSE. We obtained RMSE average value from the test is 0.08 and the SNR value at frequency(<1Hz) is 0.0190.
Finger Vein Verification Techniques using Convolutional Neural Networks
Authors:   Dept. of Computer Science & Engineering, LBSITW, Poojappura, TVPM, India., J* Lekshmi. , G.S Gisha. ,   Dept. of Computer Science & Engineering, LBSITW, Poojappura, TVPM, India.
Published: June 2020

Finger vein beneath our skin is one of the unique features for identifying an individual. Because of its uniqueness and security the finger vein recognition is considered as a powerful biometric identifier for user authentication. Several techniques have been evolved for finger vein recognition from its early stage of development, but majority approaches were based on hand crafted features which had limitations on quality of the image, positioning of the finger etc. The emergence of neural networks led to the development of various Convolutional Neural Networks (CNN) based approaches for identity verification. This paper surveys various finger vein verification techniques using CNN and determines the factors that will affect the final result. Publicly available finger vein datasets as well as user designed ones, which are of different qualities, are used for the experimental analysis of these techniques. Though CNN is used in all the cases each one differs in the number of layers used, weight updating methods, results obtained etc. It is found that higher recognition accuracy and lower equal error rate (EER) makes the finger vein verification system an effective one. This field has emerged wide popularity recently and is used in different applications where security is of prime importance.
Multi-Authority Secure Database for Enabling Authorized Encrypted Search with Privacy Preserving on Healthcare Databases
Authors:   Department of Computer Engineering, Oriental University, Indore, India., Pokharkar* Satish , Rawat Dr. Manoj Kumar ,   Department of Computer Engineering, Oriental University, Indore, India.
Published: June 2020

Now a day’s in medical field number of application’s will develop for overcome the complexity of previous work. By using information technology and computer science provide various new techniques and medical equipment’s has improved digitalization in healthcare sector. In existing system much more advancement is providing to overcome the time and money of patients and perform exact treatments and store patient’s confidential records in securely but most important issues are security. To address the existing security issues to design and develop the proposed research work on security i.e. for patient’s confidential health data records in database servers. Existing work during data transmission can only protect the patient’s data records but they can’t stop the insider attacks. In proposed research work, first implement front end security with the help of keylogging technique, second to store patient’s confidential data in multiple data servers or chunks and to prevent the insider attacks and third and most important is access policy of search for encrypted data of multi-authority. The main contribution of this research work to assign patients data records in different chunks securely and applying the cryptosystems for security goals of a patient’s confidential records. Especially, proposed work advantages of SHA hashing technique to perform each and every user for access of particular data records. This research work explores secure data storage and sharing using proposed AES 128 encryption algorithm and Role Base Access Control (RBAC) for secure data access scheme for end user. This work also carried out backup server approach it works like proxy storage server for ad hoc data recovery for all distributed data servers.
Symmetrical Analysis of Low-Cost Filter Media and Their Efficiency in Treatment of Water
Authors:   Dept. of Civil Engineering SRM Institute of Science and Technology, Tamilnadu, India, Niyas S. Sheik , Dhanasekar S. ,   Dept. of Civil Engineering SRM Institute of Science and Technology, Tamilnadu, India.
Published: June 2020

Separating is a compelling procedure in expelling particles from water because utilization of sand become nowadays is very challenging in filtration process. It is a necessity to find an alternative media which must satisfy the low cost, easy availability, high durable with less zone required and discharge of water. Many ponds are contaminated mostly in high level of turbidity. In this work it is identified the various synthetic filter media taken examined for the replacement sand. The high level of turbid water may contain slit, dissolved organic compounds, and other microscopic organisms. So, in this method all contaminants are removed. The filtration procedure was created to break down and filtration of lab scale arrangement was planned. The performance as concerns lab scale reactor was optimized by using HDPE (High Density Polyethylene) granules are easily available in all polymer industries are used as a filter media. A proportional study of natural filter media sand and synthetic filter media HDPE granules was undergone for investigation. This two-filter media were selected because of its locally available and two different size of media (sand 2.5 mm, HDPE 3.5 mm) were evaluated. Bentonite (20mg/l ≈ 120 NTU). Identified two parameters were influenced the filtration recital i.e. media depth, filtration velocity. The outcomes uncovered to evacuate turbidity in best conditions where start to be low filtration rate (10.62 l/m² min), extended media midst (240mm). The removal of turbidity in sand was 70% and in plastic media was 55%. Nevertheless, headloss was achieved in higher manner comparing to plastic media. The treated water used as agriculture purpose.
Secure Auditing and De-duplicating Data in Cloud
Authors:   M. Tech PT, CSE, REVA University, Bangalore, India., C Lakshmankumar
Published: June 2020

As the dispersed registering development makes during the latest decade, re-appropriating data to cloud organization for limit transforms into an engaging example, which benefits in sparing undertakings on generous data support and the board. In any case, since the redistributed distributed storage is not completely reliable, it raises the security worries on the best way to acknowledge information de-duplication in cloud while accomplishing trustworthiness evaluating. Right now, study the issue of uprightness reviewing and make sure about de-duplication on the cloud information. In particular, targeting accomplishing the two info honesty and the de-duplication in the cloud, we propose some two secure frame works, to be specific sec-cloud and sec-cloud+. sec-cloudhelps in presents a reviewing element with most upkeep of the Map-Reduce cloud, which assists customers with producing information about labels before the transferring just as review the trustworthiness of information having been just put away in cloud. The Contrasted and past work, the calculation by the client in Sec-Cloud is extraordinarily decreased during the record transferring and reviewing stages. Sec-Cloud is planned propelled by the way that clients consistently need to scramble their information before transferring, and empowers trustworthiness inspecting and make sure about de-duplication on encoded information.
Detection of Stroke using Image Enhancement and Segmentation
Authors:   assistant Professor, Noorul Islam Center For Higher Education, Chitra Dr. R. , J Shafeena ,   Year Pg, Noorul Islam Center For Higher Education
Published: June 2020

Incorporation of previous information regarding organ form and placement is vital to enhance execution of image examination draws near. most importantly, priors is useful in cases any place images zone unit adulterated and contain curios due to constraints in picture obtaining. The incredibly constrained nature of anatomical articles is all around caught with adapting principally based methods. Notwithstanding, in most exceptional and promising procedures like CNN fundamentally based division it's not evident the best method to join such past data. dynamic techniques work as pixel-wise classifiers any place the training targets don't fuse the structure and between conditions of the yield. AN method for the detection of Brain Stroke is projected during this work. Diagnostic strategies victimization Image Segmentation and sweetening strategies area unit projected. Our method is combined with any of the progressive segmentation or super-resolution (SR) NN models and doubtless improve its prediction accuracy and strength while not introducing any memory or process complexness at reasoning time. propose a generic coaching strategy Anatomically forced Neural Networks (ACNN), through a brand new regularization model.
An Analysis of Employee Satisfaction as a Reliable Predictor of Employee Retention in MNCS Working in India.
Authors:   Associate Professor, Faculty of commerce S.S.Jain Subodh P.G.College, Jaipur, Singhal Dr. Richa
Published: June 2020

Today, the constantly changing environment, global competition, the nature of work made companies to realize the importance of employee satisfaction for the success of organization. Now-days the competitive advantage of most companies on global market lies in the ability to create a profit driven not only by cost efficiency, but by the ideas and intellectual know-how. The networked and knowledge-based environment made the intangible assets like skills, relations and reputations of highest value. Employee satisfaction is the pleasurable emotional state resulting from the appraisal of one’s jobs as achieving or facilities the achievement of one’s job values. It is a measure of workers contentedness with their job. Every industry has different business environment, different policies for employment and different compensation measures. With the objective to analyzing the influencing factors, best policies of job satisfaction and its impact on business growth, the author decided to investigate the level of employee satisfaction in six industries namely: INFOSYS, HCL, Technologies Tech Mahindra, Oracle Financial Services, Wipro and Tata Consultancy Services. The researcher prepared questionnaire for the employees and get it filled from 303 respondents from these industries. In order to find level of satisfaction among employees of different industries, it was subjected to T-test statistical tool for variance calculation. The study concluded with the statement that the HR policies are different in different industries. The way they are implemented in different organizations has a great impact on employee satisfaction and retention.
A packed bed Reactor Combined with Membrane Unit for the Elimination of Toluene Vapours using a Novel Packing Material
Authors:   Department of Chemical Engineering, Annamalai University, Annamalai Nagar, Sundar* B. , Saravanan V. ,   Department of Chemical Engineering, Annamalai University, Annamalai Nagar, Rajasimman M. ,   Department of Chemical Engineering, Annamalai University,Annamalai Nagar.
Published: June 2020

Toluene is a colorless and aromatic oily liquid primarily used in the petrochemical and polymer processing industries and has been used in this study as the target compound. Continuous experiments were performed in a biofilter on a laboratory scale, followed by a membrane reactor to monitor toluene as one single contaminant. This bioreactor device included a reactor with a packed bed and a membrane array. Pearl millet stacks and berl saddles have been used as packing material for the development of the attached microorganism. Toluene was efficiently treated, with toluene effluent concentrations held at less than 0.4 g m-3 and a Total Removal Efficiency (TRE) of more than 96 % achieved when fluctuating loads were faced by the packed bed reactor. The combined packed bed reactor system had a maximum RE of 93.8 g m-3 h-1, which was higher than the one obtained with the packed bed reactor alone. In this work the influences on gas membrane separation were also explored in the combined bioreactor and membrane fouling.
Emerging Challenges and Sustainability of Industry 4.0 Era in the Malaysian Construction Industry
Authors:   Faculty of Industrial Management, Universiti Malaysia Pahang., Moshood* Taofeeq D , Adeleke A.Q. ,   Faculty of Industrial Management, Universiti Malaysia Pahang., Nawanir Gusman ,   Faculty of Industrial Management, Universiti Malaysia Pahang., Ajibike W.A ,   Faculty of Industrial Management, Universiti Malaysia Pahang., Shittu Rukayat .A. ,   Faculty of Applied Social Science Universiti Sultan Zainal Abidin, Terengganu.
Published: June 2020

Today's businesses are challenging what to call a new technological change. Technological advancements are going towards more enhanced internet-based method resolutions. This step is usually pointed to being Industry 4.0 and is supposed to hold the potential for new adaptable, independent products able to manage themselves. By modern technologies, nevertheless, there is additional demand for new skills and qualification demands on the workforce in the construction industry. Moreover, manufacturers or construction companies of today usually have obstacles with hiring newly qualified workers, particularly the younger one. Construction companies are looking to achieve Industry 4.0 would consequently have to maintain the development and education of existing workers while including attracting new workers. The paper objects are to explain what modifications that help achieve a sustainable of industry 4.0 in the construction industry, efficient and recognizing potential developments, understanding hazards connected with economics and supporting the simulation improvement.
A Novel Categorical Data Attribute Split Technique in Decision Tree Learning
Authors:   Department of Computer Science, Dravidian University, Kuppam, India., Mabuni* D.
Published: June 2020

A new technique is proposed for splitting categorical data during the process of decision tree learning. This technique is based on the class probability representations and manipulations of the class labels corresponding to the distinct values of categorical attributes. For each categorical attribute aggregate similarity in terms of class probabilities is computed and then based on the highest aggregated similarity measure the best attribute is selected and then the data in the current node of the decision tree is divided into the number of sub sets equal to the number of distinct values of the best categorical split attribute. Many experiments are conducted using this proposed method and the results have shown that the proposed technique is better than many other competitive methods in terms of efficiency, ease of use, understanding, and output results and it will be useful in many modern applications.
Automatic wireless Monitoring and Controlling of Greenhouse using multiple sensors
Authors:   ECE department, Bapatla Women’s Engineering College, Acharya Nagarjuna University, Andhra Pradesh, India., Jyothirmai T. , Sireesha P. ,   ECE department, Bapatla Women’s Engineering College, Acharya Nagarjuna University, Andhra Pradesh, India., Anusha P. ,   ECE department, Bapatla Women’s Engineering College, Acharya Nagarjuna University, Andhra Pradesh, India., Padma M.Venkata ,   ECE department, Bapatla Women’s Engineering College, Acharya Nagarjuna University, Andhra Pradesh, India., Vasavi N. ,   ECE department, Bapatla Women’s Engineering College, Acharya Nagarjuna University, Andhra Pradesh, India., Lavanya R. ,   ECE department, Asst. professor of Bapatla Women’s Engineering College, Acharya Nagarjuna University, Andhra Pradesh, India.
Published: June 2020

Many parameters like temperature, soil moisture, light intensity, Humidity, Carbon dioxide (CO2) leads to the healthy growth of plants in greenhouse environment. Observing only few of those leads to improper growth of plants and minimize the yields. Every grower cannot visit the field and observe the parameters continuously. In order to monitor the parameters and give the approximate control to the greenhouse, we proposed this system. This system continuously monitors the plants and communicate the information to the grower through wireless Sensor Network (WSN), thus reducing the risk of staying at the field. The proposed system has three stations - Transmitter Station (TS), Control Station (CS), and Communication Station (CMS). The ZigBee plays a major role by enabling communication between the three stations. This implementation supports the farmers to simplify the management and to increase the crop production. The overall system has shown the benefits in price, volume, and strength.
Machine Learning Based Framework for Vehicle Make and Model Recognition
Authors:   CSE, VR Siddhartha Engineering College, Vijayawada, India., haripriya Alapati , kumar Dr.Kollu Praveen ,   CSE, VR Siddhartha Engineering College, Vijayawada, India.
Published: June 2020

Nowadays, the speedy increase with in the rage of the automobiles on the main road and urban roads have created several challenges regarding the proper management and management of traffic. This is a very significant framework for intelligent traffic monitoring and management. Vehicle analysis is an important component for many smart applications, that includes automated toll collection, self-guided car driver assistance systems, smart car parking systems. In a recent years, due to increased security awareness in parking lots, restricted areas and building for access control systems, the need to identify and classify the vehicles has become important.
Localizing Text in Images and Videos based on Morphology
Authors:   Laboratory of Electronics and Information Technology (E.N.I.S.), University of Sfax, PHD student at National Engineering School of Gabes (ENIG), University of Gabes, TUNISIA., Atitallah Mohamed Amin Ben , Kachouri Rostom ,   LIGM, Univ Gustave Eiffel, CNRS, ESIEE Paris, F-77454 Marne-la-Vallée, France, Mnif Hassene ,   National school of electronics and telecommunications of Sfax, Laboratory of Electronics and Information Technology (E.N.I.S.), University of Sfax, TUNISIA.
Published: June 2020

Many multifaceted images comprise observable text. If the occurrences of this text can be identified, segmented, and recognized automatically, they will be a prized source of high-level semantics; for retrieval and indexing. In this paper, we will propose a novel method for localizing and detecting text in complex images and video frames based on morphology. A morphological Gardient is generated by computing the variance between the dilation and the erosion image. Then the candidate of regions are connected via a morphological closing operation and every text areas are determined used the occurrence of text in each candidate. The identified text regions are localized perfectly via the projection of the text pixels in the morphological Gardient map. This method is sturdy to different position, character size, color and contrast. The updating of the text region between images is also used to minimize the processing time. Tests are realized on divers images to confirm the good efficient of our method.
Object Sorting by Arduino Robot
Authors:   Pawar , Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India., P. Prof. Pruthviraj. , Ganashekaran Karthik ,   Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India., Dhanawade Prashant Popat ,   Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India., Khera Simranjit ,   Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India.
Published: June 2020

Automation of work has become an important part of industrial manufacturing process in the recent years. Tasks that usually take large amount of labor and time can now be easily completed by using robots which can be programmed to do the said task. Tasks such as assembly and object sorting which require tasks to be repeated can be carried out by robots. The system proposed here can be used for sorting objects in the industrial manufacturing process. The system focuses on sorting objects based on their size or color or both. The system is designed using IR sensors, a TCS3200 color sensor and Arduino UNO board for controlling the different parts. The proposed system gives better accuracy and performance as compared to the methods currently used.
Chaos based Encryption of Image for Secure Communication
Authors:   M.Tech student, Department of Electronics and Communication Engineering at SDM College of Engineering and Technology, Dharwad, Karnataka, India., Japate Mamatha L , Navalgund Dr.S.S. ,   Assistant Professor, Department of Electronics and Communication Engineering at SDM College of Engineering and Technology, Dharwad, Karnataka, India..
Published: June 2020

The 20th century is known as the Information age. Development of technology led to the storing and communication of information in the digital form. Digital technology provides easy access to the information through internet and other forms of technology. Transmission of information is also become easy using digital technology. The information stored or communicated may be vulnerable to attacks from the adversaries. All the organizations and individuals are facing the threat of the insecurity of the information of data over the internet. Development of communication media and insecure media emphasizes the requirement to secure the data. The method of securing the information so that it is not stolen by the hackers is known as encryption. The development of multimedia technology has increased the images as the carriers of information. The conventional encryption algorithms are not well suited for the image encryption. Image encryption has developed in the past recent years as an important field. In the image encryption, the substitution and transposition techniques are performed on the pixel values of the image based on the key. One of the mechanisms for image encryption is based on chaos theory. Chaos sequence is used as a key for encryption because of its properties. This method of encryption is more secure and robust.
Machine Learning Based Track Classification and Estimation using Kalman Filter
Authors:   School of Electronics Engineering, Vellore Institute of Technology, Vellore, India, Reddy B.Sai Tejeswar , J Valarmathi. ,   School of Electronics Engineering, Vellore Institute of Technology, Vellore, India
Published: June 2020

Classification of target from a mixture of multiple target information is quite challenging. In This paper we have used supervised Machine learning algorithm namely Linear Regression to classify the received data which is a mixture of target-return with the noise and clutter. Target state is estimated from the classified data using Kalman filter. Linear Kalman filter with constant velocity model is used in this paper. Minimum Mean Square Error (MMSE) analysis is used to measure the performance of the estimated track at various Signal to Noise Ratio (SNR) levels. The results state that the error is high for Low SNR, for High SNR the error is Low.
Big Data Model for Financial Assistance to Students- A Paradigm Shift
Authors:   Department of ECE, Desh Bhagat University Mandigobindgarh, India, Singh Harinder Pal , Singh Harpreet ,   Department of Electrical and Computer Engineering, Wayne State University Detroit, USA, Singh Jang Bahadur ,   Department of ECE Desh Bhagat University Mandi Gobind Garh, India
Published: June 2020

Big Data Technologies for managing huge amounts of student data which is rising exponentially year after year specially in the countries like India, where there is a large no of young population is a need not luxury. Many students are searching for courses of their choice and for funding their education interests they look for scholarships. There are many scholarship schemes available for students of different status in the society. Educational institutions look for solutions to handle large amount of student data ranging from enrollments, scholarships, academic content, literature search, testing, results and finally placements. Such data require a lot of integrity and scalability. Memory saving schema for hardware and software platforms for the needy Universities and Colleges along with lot of mobility for their executives to access and analyze such data remain in focus. In this paper a new data base model has been suggested using modern day Big Data technologies rather than using conventional database technologies to handle complex data generated through student activity which can be analyzed to reach decisions. New model suggested after testing real time data sets of scholarships management of technical education system. Lot of memory and cost has been saved along with achieving data integrity, security and improvement in response time.
Servitization Trend in Big Data to Personal Styling Service
Authors:   Seoul School of Integrated Science and Technologies(aSSIST), South Korea., Won Jessica , Kim* Bo-Young ,   Seoul School of Integrated Science and Technologies(aSSIST), South Korea.
Published: June 2020

Servitization is a customer service with integrated product-service offerings, called product-service systems. This study aims to analyze consumer awareness and user behavior of servitization and focus the personal styling service in fashion industry. We used the social network and text mining techniques to capture social network service communications, which is a great source of useful information close to customers. Frequency analysis, centrality analysis, clustering analysis, and network visualization were conducted to investigate consumer awareness and user behavior using big data in social media. “Shoes” and “clothes” were the most frequently apparent keywords with the notion of “servitization,” and the keywords “home” and “fashion” had the highest degree of centrality in the network. Four clusters were found on the notion of servitization: fundamentals, fashion, home, and job seeking. A significant transition toward servitization is ongoing in various industries, especially the fashion industry, according to the clustering analysis. To gain a better understanding of this transition, a commercially available personal styling service was investigated. Three major companies were selected by sales volume and reputation, and the names of these companies were used as search keywords to acquire related data on social media. The keywords “men’s fashion” and “subscription box” appeared frequently apart from common fashion-related hashtags. In betweenness centrality, “best quality” and “low price” were the most important keywords in the market. This study contributes to the investigation on the trend of servitization and provides insights to service providers on consumer awareness and user behavior toward this trend via social media.
Secure Routing Algorithm in Wireless Mesh Network
Authors:   Research Scholar, Department of Computer Science and Engineering, VelTech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology (Deemed to be University), Chennai, Tamil Nadu, India., Narwade* Mr. Rajnikant Kundlik , Balamurugan Dr. P. ,   Professor, Department of Computer Science and Engineering, VelTech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology (Deemed to be University), Chennai, Tamil Nadu, India.
Published: June 2020

In the today’s’ era of communication technology disaster management plays important role in life saving. Regardless of men made disasters or natural disasters proper communication network can be used to exchange information. In natural calamities wireless sensor mesh network proved to be as good option for communication. Low-altitude Unmanned Aerial Vehicles (UAVs) which is associated with WLAN Mesh Networks (WMNs) can be used in disaster management areas. The advantage of it is it can be installed on demand and it can use for efficient exploration of sized areas. The WMN is consisting of different components such as mesh clients, mesh routers and base station. It is more prone to have attacks of different types such as Denial of Service attack, black hole, gray hole , reply attack, Sybil attack etc. The most important attack which can damage whole working of WMN is routing attack. IEEE 802.11i is used as standard protocol for security in WLAN and IEEE 802.11s is used as secure algorithm for communication in WLAN mesh network. But both of them fail to address issue of routing problem in WLAN mesh network. The primary purpose of this paper is to outline routing algorithm and to design assured routing protocol. In this paper we have proposed improved secure Position-Aware, Secure, and Efficient mesh Routing approach (S-PASER). The proposed mechanisms have obviated more attack than regular IEEE 802.11s/i security mechanism and well known, secure routing protocol. The proposed methodology can be implemented on omnet++ simulator. The simulation results proved to be have better performance and throughput than existing algorithm.