bluuebunny/crossref_metadata_2025 huggingface dataset:
The Mental Toughness of State and University Football Players in Malaysia
Authors:   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Karim* Zulakbal Abd , Mazlan Anis Nabila ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Zakaria Jaffry ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Yasim Mazuki Mohd ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Hassan Sadzali ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Suwankhong Dusanee ,   Faculty of Health and Sports Science, Thaksin University, Thailand.
Published: October 2019

This study aimed to identify and compare the level of mental toughness that consisted of five subfactors namely the reversal of mistakes, pressure control, focus, self-confidence, and motivation among football players of a state and university football team. The questionnaire used in this study was Sport Mental Toughness Questionnaire (SMTQ) that measure the level of mental toughness among the players. The findings showed that the state players scored greater mistake reversibility, pressure control, focus concentration, and self-confidence compared to university players. No significant differences of motivation between those two clubs. The findings of this study can provide guidance to coaches especially to identify the level of mental strength among their players and provide appropriate mental training.
Role of Heuristic Algorithms in Minimizing the Makespan of Fuzzy Flow shop Scheduling Problem
Authors:   Department of Humanities & Basic Sciences,Aditya Engineering College,Surampalem,AP,India, Selvamalar* N. , Vinoba V. ,   Department Of Mathematics ,KN Govt.Arts College, Thanjavur,Tamilnadu,India
Published: October 2019

In this paper, the three fuzzy heuristics namely fuzzy Campbell-Dudek-Smith algorithm(FCDS), fuzzy Nawaz-Enscore-Ham(FNEH) algorithm and fuzzy Rapid Access(FRA) algorithm has been subjected to a comparative study to evaluate and assess the efficiency of the fuzzy models in various problems of random size.A sample data is chosen and 14 problems are generated with different job and machine size.The makespan is evaluated,compared and depicted using ORIGIN software.The worst case solution of every problem is compared with the heuristic schedule obtained in order to show the improvement in the solution when the above heuristics are applied.It is noticed that the FNEH algorithm stand tall above the remaining procedures adopted in this work except a few instances where the FRA procedure excels.
Intelligent Driver Warning System using Deep Learning-based Facial Expression Recognition
Authors:   Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India., Suchitra* S. , Priya S.Sathya ,   Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India., Poovaraghan R.J. ,   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, India., Pavithra B. ,   Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India., Faustina J.Mercy ,   Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India.
Published: October 2019

Driver’s inattention is one of the major factors and reasons in occurrence of many road accidents and unforeseen crashes. Hence it is crucial to develop an automatic driver warning system that can send timely warning signals to the drivers. This issue involves determining the driver’s mental state that is ultimately based on the driver’s facial expressions. Automated facial emotion recognition is a recent development in the image processing domain and is the need of the hour in applications like driver warning systems. The existing methods are capable of recognizing facial emotions even when provided with a noisy signal or imperfect data, but ultimately it lacks accuracy. It is also ineffective in dealing with spontaneous emotions, and recognition. The proposed approach develops a driver warning system that extracts the facial expressions based on a novel efficient Local Octal Pattern (LOP) and effectively recognizes the facial expressions based on Deep Neural Networks, Convolutional Neural Networks (CNN). The LOP feature map serves as an input to CNN and guides in the selection of CNN learning data thereby improving and further enhancing the understanding and learning of CNN. It also has an ability to recognize both natural and spontaneous emotions, as well as image and video can be considered as an input.The experimental results consideringYawDD dataset indicates that the proposed system has been efficiently evaluated by considering the with metrics such as Precision, Recall and F-Score and thereby it is observed and inferred that the proposed system obtained a high recall rate of 96.09% in comparison with the other state-of-the-art methods.
Design and Performance analysis of IoT based Smart Street Light & Collision Detection System
Authors:   GLA University,17 Km Stone, NH-2, Mathura-Delhi Road, Mathura - 281 406 (U.P.) India, Kumari* Mona , Kumar Ajitesh ,   GLA University,17 Km Stone, NH-2, Mathura-Delhi Road, Mathura - 281 406 (U.P.) India, Lavania Vishal ,   GLA University,17 Km Stone, NH-2, Mathura-Delhi Road, Mathura - 281 406 (U.P.) India
Published: October 2019

This paper aims for providing solution to design and execute the system for saving energy of street lights and controlling the collisions occurring on roads. Currently we have a manual system where the street lights will be switched ON in the evening before the sunsets and they are switched OFF in the next day morning after there is sufficient light outside and currently there is no such system in India that helps in monitoring or detecting collisions occurred on roads. This we can implement by sensing a vehicle using an Ultrasonic sensor/IR sensor and using some heat & sound sensors for sensing the collision if it occurs. On sensing the movement of a vehicle, the sensor transmits the data to the Raspberry Pi, which will switch ON the next three consecutive street lights in order to give the driver a visible track to drive in dark. Similarly, the Light gets switched OFF according to a timer that gets triggered as soon as the vehicle or an obstacle goes away from the sensor.
Dualities between Mohand Transform and Some Useful Integral Transforms
Authors:   Assistant Professor, Department of Mathematics, National P.G. College, Barhalganj,Gorakhpur-273402,U.P.,India,, Aggarwal Sudhanshu , Gupta Anjana Rani ,   Professor, Department of Mathematics, Noida Institute of Engineering & Technology, Greater Noida-201306, U.P., India
Published: October 2019

Integral transforms have wide applications in the different areas of engineering and science to solve the problems of springs, Newton’s law of cooling, electrical networks, bending of beams, mixing problems, signal processing, carbon dating problems, Newton’s second law of motion, exponential growth and decay problems. In this paper, we will discuss the dualities of some useful integral transforms namely Laplace transform, Kamal transform, Elzaki transform, Aboodh transform, Sumudu transform, Mahgoub (Laplace- Carson) transform and Sawi transform with Mohand transform. To visualize the importance of dualities between Mohand transform and mention integral transforms, we give tabular presentation of the integral transforms (Laplace transform, Kamal transform, Elzaki transform, Aboodh transform, Sumudu transform, Mahgoub transform and Sawi transform) of mostly used basic functions by using mention dualities relations.
A Framework for Medical Data Analysis using Deep Learning Based on Conventional Neural Network (CNN) and Variable Auto-Encoder
Authors:   is a research scholar in College of Engineering & Technology at Acharya Nagarjuna University and he did M. Tech (Computer Science & Engineering) Degree from JNTU-Hyderabad., Shabbeer* F Shaik. , Reddy Dr. E. Srinivasa ,   Professor & Dean R&D in University Engineering College of Acharya Nagarjuna University. Guntur, Andhra Pradesh
Published: October 2019

Medical data classification is an important and complex task. Due to the nature of data, the data is in different forms like text, numeric, images and sometimes combination of all. The goal of this paper is to provide a high-level introduction into practical machine learning for purposes of medical data classification. In this paper we use CNN-Auto encoder to extract data from the medical repository and made the classification of heterogeneous medical data. Here Auto encoder uses to get the prime features and CNN is there to extract detailed features. Combination of these two mechanisms are more suitable for medical data classification. Hybrid AE-CNN (auto encoder based Convolutional neural network). Here the performance of proposed mechanism with respect to baseline methods will be assessed. The performance results showed that the proposed mechanism performed well.
Statistical Based Feature Selection and Ensemble Model for Network Intrusion Detection using Data Mining Technique
Authors:   Assistant Professor in the Department of Computer Science at Dharumapuram Gnanambigai Government Arts College for Women, Mayiladuthurai., Mageswary G. , Karthikeyan Dr. M. ,   Assistant Professor in the Division of Computer & Information Science, Faculty of Science, Annamalai University.
Published: October 2019

In today’s world, Information society, computer networks and their interconnected applications are the emerging technologies. Intrusion Detection System (IDS) is used to distinguish the attitude of the network. Now a days, due to frequent and heavy attacks an Network devices, the Intrusion Detection System has become growing and censorious component to secure Network devices. A huge amount of data is needed to build the perfect Intrusion Detection System. This proposed system focuses on feature selection and ensemble of tree based classification methods to build Intrusion Detection System. The implementation of feature selection is fulfilled by using the NSL-KDD dataset. Statistical based feature selection methods such as Pearson's Correlation, Chi-square, Gain ratio and Symmetrical uncertainty are used to generate four modified datasets. By using that modified datasets the tree based Intrusion Detection models are built using J48, REP Tree and simple CART algorithms. To acquire better prediction of accuracy the algorithms J48, REP tree and simple CART are combined using ensemble method and built perfect tree based Intrusion Detection System.
Online Purchasing Trend in the Retail Industry in Saudi
Authors:   Doctor of Philosophy of Management (PhD) student at Limkokwing University of Technology and Creative, Malaysia., Kebah* Mohamad , Raju Dr. Valliappan ,   Senior Lecturer at the Centre of Postgraduate Studies at Limkokwing University, Malaysia., Osman Dr Zahir ,   Senior Lecturer at the Faculty of Business and Management, Open University of Malaysia (OUM).
Published: October 2019

The concept of online shopping is very popular in the present market scenario. The current trend is indicating the fact that people prefer to shop online because it is easier ad convenient for them. Organizations can easily understand the buying behaviour of the customers by considering different theoretical approaches. The study has indicated that in Saudi Arabia the current trend of online purchasing is at the higher level. People frequently shop online and it is expected that the rate of online shopping in the retail industry in Saudi Arabia will growth further. This study was carried on by using the primary data, which was collected through survey. Survey was conducted with 100 customers in the retail industry in Malaysia. The study used the positivism philosophy for the investigation. The findings in this study are highly important for understanding the latest scenario in the retail industry in Saudi Arabia. The study showed the fact that the people in Saudi Arabia are fond of online shopping. The people are highly motivated for online shopping because of several reasons or benefits that they can enjoy. The findings will be used in the future researches for understanding how the online retail market in Saudi has been developed. This will help to understand the reasons for which the people in this country prefer to shop online. This will also indicate the growth opportunity in the online retailing in Saudi Arabia. The overall findings in this study are highly useful for getting a clear knowledge about the online retailing in Saudi Arabia.
Information Behavior Culture of the RuNet Audience
Authors:   Kazan State Institute of culture, Kazan, Russian Federation., Gilmanova* Aigul Nurgayanovna , Gafiullina Liliya Faritovna ,   Kazan State Institute of culture, Kazan, Russian Federation., Kazakov Anton Fedorovich ,   Kazan State Institute of culture, Kazan, Russian Federation., Malakhov Victor Petrovich ,   Kazan State Institute of culture, Kazan, Russian Federation., Minnekametova Ilkhamiya Mansurovna ,   Kazan State Institute of culture, Kazan, Russian Federation.
Published: October 2019

The purpose of this study is to analyze the formation of a media consumption culture in the information-rich multiconfessional and bilingual region of the Russian Federation – the Republic of Tatarstan. The authors of this article conducted a survey of 200 respondents aged 19-55 who are active users of the RuNet. The survey was carried out among students of the Kazan State Institute of Culture and Kazan Federal University, as well as media professionals from the Republic of Tatarstan. The anonymous survey was conducted in January-March 2019. Of all the respondents participated in this survey, 56% were aged 19-20. Eighty-three percent of the respondents were female – students, teachers and media workers of the Republic of Tatarstan. Sixty-five percent of them combined their education with work. Ninety-eight percent of the respondents received information from the Internet, 76% watched information programs on television, 27% listened to the radio and only 7.5% of the respondents still read newspapers. Sixty-eight percent of the surveyed trusted messages received from news agencies, while 78% trusted news messages received from news aggregators. Ninety percent of the respondents trusted information received from online media; 11% trusted the information received from social networks and only 4.5% of the respondents trusted the information discussed in blogs. The high percentage of trust to information obtained from the media and the low percentage of trust to information obtained from blogs indicates the current culture of media use and media literacy of the population in the situation with fake news. Of all the respondents answering the question "Do you refer to the source of information you use on the Internet?", 91.5% answered positively. Disturbingly, 92.5% of the surveyed believe that they do not have to pay for the information received from online media. The authors explain the refusal to pay for content with a small amount of exclusive and analytical materials in the information field of the Republic of Tatarstan.
Wheat Yield Prediction using Data Mining
Authors:   Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India., Kawatra* Manan , Singh Prof. Jagdeep ,   Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India., Bagga Prof. Sachin ,   Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India.
Published: October 2019

These days peasants are facing problems in producing the yield of any crop due climatic changes which are unpredictable. Therefore, to provide improvement in agriculture a well organized and approach is needed to predict the yielding of crop on the basis of which planning can be done. The prediction must be good enough to support the peasants to take appropriate actions to get the apt amount of the crop by selling it. This work aims to provide prediction with high accuracy and less RMSE. It deals with the prediction of the wheat crop yielding using data mining techniques. It helps in predicting crop yield using previous data with the help of parameters like Rainfall and Temperature. It consists of clustering which has been done with the help of k-means, extracting features with independent component analysis, instance selection using moth flame optimization and the prediction and classification has been performed with Linear Discriminant Analysis. The technique is applied MATLAB. The performance is evaluated using mean square error rate and prediction of yielding of wheat is also calculated. The error must be less to get more accuracy for the predicting rate.
An Extended Shackel’s Acceptability Paradigm: a Balance of Security & Speed
Authors:   Department of Computer Science, Himachal Pradesh University, Shimla, H.P., India, Kumar* Naveen , Kalia Arvind ,   Professor, Department of Computer Science, Himachal Pradesh University, Shimla, H.P., India, Ku mar Rakesh ,   Professor, Department of Computer Science & Applications, Kurukshetra University, Kurukshetra, Haryana, India
Published: October 2019

Today’s world is full of technical equipments. Human lifestyle has been changed due to tremendous growth in Internet Users. There are different types of machines like mobile, tablet, laptop, desktop, etc. User Interface is an important concept in case of every machine. Prof. Brain Shackel proposed a paradigm for web-development in which, there is a number of parameters like Usability, Utility, Likability, and Speed. Utility, Usability, and Likability are important while designing a web portal yet without having a good speed, these factors are useless. Now, the effect of these parameters on user’s lifestyles or lives is a big question need to be considered. In this paper, research is carried out to analyze the factors of Shackel’s Acceptability paradigm. Some key factors have been identified for improving the speed of a website. In order to carry out this research a web-portal has also been analyzed using GTMetrix Tool. An Extended Paradigm has also been introduced in this direction with five parameters i.e. Usability, likability, Utility and in the core there is speed and security.
Enhancing Image Diagnosis by the Implementation of Transfer Classifiers
Authors:   Computer Engineering and Applications, GLA University, Mathura, India., Agrawal* Vinay , Shankhdhar Ashutosh ,   Computer Engineering and Applications, GLA University, Mathura, India., Mangla Arushi ,   Computer Engineering and Applications, GLA University, Mathura, India.
Published: October 2019

Images generated from a variety of sources and foundations today can pose difficulty for a user to interpret similarity in them or analyze them for further use because of their segmentation policies. This unconventionality can generate many errors, because of which the previously used traditional methodologies such as supervised learning techniques less resourceful, which requires huge quantity of labelled training data which mirrors the desired target data. This paper thus puts forward the mechanism of an alternative technique i.e. transfer learning to be used in image diagnosis so that efficiency and accuracy among images can be achieved. This type of mechanism deals with variation in the desired and actual data used for training and the outlier sensitivity, which ultimately enhances the predictions by giving better results in various areas, thus leaving the traditional methodologies behind. The following analysis further discusses about three types of transfer classifiers which can be applied using only small volume of training data sets and their contrast with the traditional method which requires huge quantities of training data having attributes with slight changes. The three different separators were compared amongst them and also together from the traditional methodology being used for a very common application used in our daily life. Also, commonly occurring problems such as the outlier sensitivity problem were taken into consideration and measures were taken to recognise and improvise them. On further research it was observed that the performance of transfer learning exceeds that of the conventional supervised learning approaches being used for small amount of characteristic training data provided reducing the stratification errors to a great extent.
Induced H-Packing k-Partition Problem in Certain Networks
Authors:   Department of Mathematics, Loyola College, University of Madras, Chennai - 034,India., Theresal* Santiagu , Xavier Antony ,   Department of Mathematics, Loyola College, University of Madras, Chennai - 034, India, Raja S. Maria Jesu ,   Department of Mathematics, Vels Institute of Science, Technology and Advanced Studies, Chennai -117, India.
Published: October 2019

A collection = {H1,H2,..., Hr } of induced sub graphs of a graph G is said to be sg-independent if (i) V(Hi) V(Hj )= , i j, 1≤ i, j≤ r and (ii) no edge of G has its one end in Hi and the other end in Hj , i j, 1≤ i, j≤ r. If Hi H, ∀ i, 1≤ i ≤r, then is referred to as a H-independent set of G. Let be a perfect or almost perfect H-packing of a graph G. Finding a partition of such that is H-independent set, ∀ i, 1 ≤ i ≤ k, with minimum k is called the induced H-packing k-partition problem of G. The induced H-packing k-partition number denoted by ipp(G,H) is defined as ipp(G,H) = min (G,H) where the minimum is taken over all H-packing of G. In this paper we obtain the induced H-packing k-partition number for Enhanced hypercube, Augmented Cubes and Crossed Cube networks where H is isomorphic to and .
Impact of Unit Testing in Web Automation Testing
Authors:   MCA Department MepcoSchlenkEngg. College (Autonomous), Sivakasi, Tamil Nadu, India, Chandrasekaran* G. , Neethidevan V. ,   MCA Department MepcoSchlenkEngg. College (Autonomous), Sivakasi, Tamil Nadu, India, Murugachandravel J. ,   MCA Department MepcoSchlenkEngg. College (Autonomous), Sivakasi, Tamil Nadu, India
Published: October 2019

The main intent of performing Software testing is to see that the software system is working as per the user’s requirements. Unit testing is done at the individual unit or at the components level. The main objective of this testing is to validate and ensure that each unit is performing its required function effectively. In case of automated testing, in recent days, many testing tools are available which help developers to perform unit testing in a simpler manner. This paper shows how automated unit testing is performed using different testing tools like JUnit, Selenium with web driver Java and Selenium with python. Regarding the experimental work, different applications were tested with the automated tools and results have been discussed with its code. To ensure reliability on web testing, the application has to be tested with the most suitable test case. With Selenium web driver concept, various User Interfaces are identified with xpath and CSS concept and test scripts ensure that various inputs are navigated between User Interface elements. The Automated software testing process reduces time and makes it more accurate.
Assessment of Peak Ground Acceleration for South Chhattisgarh (India), with Local Site Parameters: A Deterministic Method
Authors:   Department of Civil Engineering, Faculty of SoS, E&T, GGV, Central University, Bilaspur, Chhattisgarh., India, Parashar* Ashish Kumar , Atmapoojya Sohanlal ,   Department of Civil Engineering, H.O.D., K.I.T.S. Ramtek, Maharashtra, India
Published: October 2019

Looking into the present scenario worldwide, it is obvious that there is rapid increase in construction activities hence, the vulnerability to calamities of areas leading to large loss potentials. So the researches all over the globe are basically focused over disaster management, to safeguard the life and properties. The district headquarters Dantewara, Jagdalpur and Kanker are located in the south of Chhattisgarh state (India), where high concentration of the tribal population and rapid infrastructure development is observed. In order to trim down vulnerability, precise microzonation studies are required to be a constituent of the master plan, for construction activities, of earthquake resistant structures in the south of Chhattisgarh region. In the present research, the Deterministic Seismic Hazard Analysis (DSHA) for district headquarters of south Chhattisgarh has been carried out. In order to estimate the seismic parameters, past earthquake data of district headquarters of south Chhattisgarh, with radius of 300kM around them has been analyzed. Thirteen, Twelve and Eighteen tectonic features have been identified as potential seismogenic source, from the seismotectonic atlas of India for Dantewara, Jagdalpur and Kanker respectively. The maximum magnitude has been assigned to each seismogenic source. To evaluate the hazard in the study region, Ground Motion Prediction Equation (GMPE) developed by Cornell (1976) and Raghukanth and Iyengar (2004) has been used. The Peak Ground Acceleration (PGA) values are estimated for district headquarters of Dantewara, Jagdalpur & Kanker around its adjoining areas. Maximum PGA value for return period of100 years at bed rock level is 0.05063g and 0.06378g for Dantewara region using Ground Motion Prediction Equation (GMPE) developed by Cornell (1976) and Raghukanth & Iyengar (2004). It has been reported from the study that the above values are found to be on the lower side as compared to the recommendation given by IS Code of practice (IS:1893 part I (2016).The outcome of present research can be directly implemented for design of earthquake resistant structures in south Chhattisgarh region. Thus the study accounts that south Chhattisgarh is safe from seismic risk.
An Effective Energy Management of Nodes in MANET based Swarm Intelligence with Feature Selection Methods
Authors:   Assistant Professor, Vellalar College for Women, Erode, India., Kokila* S. S. , Devi Dr. C. L. Brindha ,   Assistant Professor, Queen Mary's College, Chennai, India.
Published: October 2019

Now-a-days constraints of hardware and resource efficient routing are very important for construct at Mobile Ad-hoc Network. Previous works describe the ABC and WO based energy efficiency. The proposal paradigm intends to reach a particular quality requirement for MANET. A novel Swarm Intelligence and Feature selection methods are developed to new routing algorithm for managing high energy. The protocol grouped together based on their structure, energy, computational complexity and path establishment. To evaluated and compares MANET routing protocols for wireless sensor network. Swarm intelligent found that not only energy as well as has the performance in both routing and Quality of Packet delivering. To using Feature selection method is to find optimal route which from feasible route. This method is to improve the quality of MANET and find intrinsic properties of energy management. The new proposal Improved Swarm Intelligence Routing Algorithm (ISRA) to have standard simulation and performance metrics for comparing different protocol using NS2 based simulator and discover the efficiency.
A Swarm Intelligence Based Weighted Feature Extraction and Classification using SVM for Sentimental Exploration
Authors:   Research scholar- CSE Department, University College of Engineering & Technology, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India., Srinivas* P. V. Naga , Sekhara Rao M. V. P. Chandra ,   Professor, CSE Department, RVR & JC College of Engineering, Guntur, Andhra Pradesh, India.
Published: October 2019

The goal of Sentiment Exploration (SE) is used for mining the accurate sentiments which are very beneficial for businesses, governments, and individuals, the opinions, recommendations, ratings, and feedbacks are becoming an important aspect in present scenarios. The proposed methodology likewise attempts to introduce a swarm intelligence based sentimental supervised methodology. In order to obtain a relevant feature data set from a large number of data samples, this method used particle swarm optimization to attain the utmost optimum feature set. The evaluation of the optimum feature set is obtained by means of using Minimum Redundancy and Maximum Relevancy measure as the fitness function. The categorization of the extracted feature set is accomplished with the Support Vector Machine classification technique. The experimental outcome for the suggested method is evaluated using four performance measure like precision, recall, accuracy, and f-measure and showed that proposed swarm intelligent based classification method has better performance using IMDB, Movie Lens and Trip Advisor Data Samples.
Mechanical Characteristics of CSP Filled Glass-Epoxy Composites
Authors:   Department of Mechanical Engineering, JSS Science and Technology University, SJCE-Mysuru, India, Mallesh* Dr. G , M Paramesha ,   Department of Mechanical Engineering, Sri Krishna Institute of Technology, Bengaluru, India, Kumar V G Pradeep ,   Department of Mechanical Engineering, JSS Science and Technology University, SJCE-Mysuru, India, R Pavankumar ,   Department of Mechanical Engineering, JSS Science and Technology University, SJCE-Mysuru, India
Published: October 2019

Composite materials are the combination of two or more materials which are different in form and chemical compositions. These are gradually gaining more importance as structural materials in the present day engineering design and development activity; this is because they offer very attractive physico-mechanical properties. Hence composite materials can be used in automobile brake, aircraft and marine components, wind turbine blades, heat insulators, sporting equipment etc., Brake is a very important part of an automobile which causes safe emergency stop with certain predetermined distance and it was made of asbestos and continuous use of asbestos leads carcinogenic and lung disorders due to these causes use of asbestos was banned during 1990’s. Hence attempts are made to develop new eco-friendly brake friction materials for automotive applications using Glass-Epoxy FRP composites filled with Coconut Shell Powder (CSP) to estimate mechanical characteristics.
Improving Speed and Accuracy of Image Retrieval using Elastic Search and Features Nearest Neighbor Search
Authors:   Research Scholar, Department of CSE, AMC Engineering College, Bangalore, India., Sundarakumar* R , Mahadevan Dr.G. ,   Professor, Department of CSE, AMC Engineering College, Bangalore, India.
Published: October 2019

A developing interest had shown as late in structure closest neighbor search arrangements inside Elastic search–one of the most well-known full-content web indexes. In this paper, we focus explicitly around Elastic search and Features Nearest Neighbor search (ESFNNS), which accomplishes sensitive speed-ups over the current term coordinate gauge. Features Nearest Neighbor search performs the image retrieval, which integrates the features of color, shape, and texture. This will engage an Elastic search with the capacity of quick data retrieval and accuracy when compared to the FENSHSES method.
Design of Proposed Test Case Prioritization Model for Test Sequence Generation and Validating Performance against Existing Methods
Authors:   Assistant Professor, Computer Science and Application Department, MDU, Rohtak,, Dr. Priti*  , Kavita  ,   Research Scholar, Computer Science and Application Department MDU, Rohtak
Published: October 2019

Regression testing is an effective tool or technique used for minimizing the efforts and resource consumption when a new version or the modification in the software project is tested. In such project, the testing is performed only on the selected modules or testcases. The sequence of the testcase execution also matter in regression testing. Researchers used various evolutionary, swarm based and mathematical methods for testcase prioritization and optimization. Researchers also used the fault based or coverage based measures for testcase prioritization. In this paper, the functional contribution of the recent research is provided. The research method, projects and the contribution of the work is discussed in this paper. In this paper, the framework of the proposed dynamic programming based weighted method is provided. The paper defined the work stages of the proposed model. The algorithm for test sequence generation is also provided in this paper. The analysis results of the work are provided against the greedy and dynamic programming based methods. The results are derived for cost and the number of testcases processed by the method. The results show that the proposed model improved the performance effectively.
Optimizing Municipal Solid Waste Transportation Routes for Pune City using MATLAB
Authors:   Research scholar SP Pune University, Nagrale* Sanjay D. , Thakare Dr. Sunil B. ,   Principal ABCOER Pune
Published: October 2019

The environment is heading towards a potential risk due to unsustainable waste disposal. It is a sensitive issue which concerns about serious environmental problems in today’s world. The present situation of direct dumping of the waste without proper inspection and separation leaves a serious impact of environmental pollution causing a tremendous growth in health related problems. “Domestic, industrial and other wastes, whether they are of low or medium level wastes, they are causing environmental pollution and have become perennial problems for mankind. If this situation is not handled in a proper manner within time then it would lead to worse consequences on a global level. There has been development of new technologies for improving the waste management systems. In this paper we attempt to show a detailed analysis of three crucial parameters: distance, time and cost affecting the solid waste management system by a direct comparison of existing routes and through the routes obtained by application of Arc GIS. Method adopted for analysis is VAM (Vogel’s Approximation Method) a part of Transportation model, and results of the same are validated using MATLAB Software programmed exclusively for VAM.
Natural Language Processing and Machine Learning Classifier used for Detecting the Author of the Sentence
Authors:   CSE, S R Engineering College, Warangal, India., Sheshikala Dr.M. , Kothandaraman Dr.D. ,   CSE, S R Engineering College, Warangal, India, Prakash Dr.R.Vijaya ,   CSE, S R Engineering College, Warangal, India, Roopa G. ,   CSE, S R Engineering College, Warangal, India.
Published: October 2019

Detecting the author of the sentence in a collective document can be done by choosing a suitable set of features and implementing using Natural Language Processing in Machine Learning. Training our machine is the basic idea to identify the author name of a specific sentence. This can be done by using 8 different NLP steps like applying stemming algorithm, finding stop-list words, preprocessing the data, and then applying it to a machine learning classifier-Support vector machine (SVM) which classify the dataset into a number of classes specifying the author of the sentence and defines the name of author for each and every sentence with an accuracy of 82%.This paper helps the readers who are interested in knowing the names of the authors who have written some specific words.
Symmetric Random Biometric Key (SRBK) Based Cryptography
Authors:   Research scholar, Saveetha Institute of Medical And Technical Sciences (SIMATS), Pavithra* S. , Muthukannan Dr.P. ,   Professor, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences
Published: October 2019

In this paper, we propose a novel cryptographic algorithm namely Symmetric Random Biometric key (SRBK) algorithm. The key for this SRBK algorithm is obtained from two biometric features namely ear and lip. The key generated are flexible and can be altered based on the type of algorithm used. We also consider Advanced encryption standard (AES) algorithm for comparison with SRBK algorithm and finally it was proved that SRBK algorithm is better than AES algorithm on selected parameters.
Modeling and Simulation of the Flyback Converter using SPICE Model
Authors:   Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, India, Dhamodaran* M. , Jegadeesan S. ,   Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, India, Murugan A. ,   Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, India, Ramasubramanian B. ,   Department of Electronics and Communication Engineering, SRM TRP Engineering College, Trichy, India
Published: October 2019

This paper presents to find a sufficient model of integrated passive structures for high frequency analysis and prediction in power electronic circuits. At high frequencies there are many parasitic oscillations that begin to circulate in the power circuits. Some sources of these oscillations include inter-component connections and their environment begin having electromagnetic significance, unmodeled characteristics in the semiconductor devices, Parasitic impedance characteristics of discrete passive components, Interference from an imperfect source and a ground plane and Interference from radiation. A simulation model involving most of these factors can prove valuable in distinguishing between the causes of parasitic oscillations. A designer can modify the parameters of a particular parasitic element, and observe its effect on the oscillations, hence seeing which factors are the most significant.
Medical Image Authentication by SWT and SVD
Authors:   Department of CSE, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka ,India., B* Madhu , Holi Ganga ,   Department of Information Science & Engineering, Global Academy of Technology, Bangalore, Karnataka ,India.
Published: October 2019

The proposed paper work is implemented using Stationary Wavelet Transformation (SWT) with Singular Value Decomposition (SVD).Even though, there are many other transformations, the Stationary Wavelet Transformation method is chosen for its shift invariance property. The designed method has three steps; the first step is the decomposing of the Medical image into sub-bands using SWT to find the value of sub band and as a second step is to apply SVD, third step will combine both the images with scaling factor. The experiments were conducted over gray scale of MRI and CT Medical images. The statistics of proposed method indicates that imperceptibility of Watermarked Medical images have a Peak Signal to Noise Ratio (PSNR) value of 50 DB for medical images. The robustness is ensured by having Correlation Coefficient (CC) of 1 for the retrieved watermark images. Security for the watermark is extended by encrypting the watermark with chaotic sequence.
An Enhanced Human Activity Prediction at Rainy and Night Times
Authors:   Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India., D* Manju , V Radha ,   Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India.
Published: October 2019

Human activity prediction aims to recognize an unfinished activity with limited motion and appearance information. A generalized activity prediction framework was proposed for human activity prediction where Probabilistic Suffix Tree (PST) was introduced to model casual relationships between constituent actions. Then, each kind of activity in videos was predicted by modeling interactive object information through Spatial Pattern Mining (SPM). This framework mined the temporal sequence patterns. For efficient human activity prediction a Spatio-Temporal Frequent Object Mining (STOM) was proposed in which the spatial, size and motion correlation among objects information were collected along with the temporal information. After the collection of this information, the objects were identified by using Modified Histogram Of Gradient (MHOG) and then the objects were tracked by particle filter technique. The frequent action of detected objects were identified by using Frequent Pattern-growth (FP-growth) which predicted the infrequent action as abnormal human activity in videos. However, MHOG based Object Detection and Tracking-STOM (MHOGODT-STFOM) based human activity prediction is not more effective at night time and rainy time. So in this paper, Enhanced Object Detection and Tracking- STFOM (EODT- STFOM) and Removing Rain Streaks-EODT-STFOM (RSR-EODT-STFOM) are proposed for human activity prediction even at night time and rainy time. In EODT, a modified Contrast Model is used which combined the contrast information and local entropy information to detect object contents present in the current image frame. Then, the objects are tracked by Kalman filter. In RSR-EODT, the rain streaks in the images are removed based on the deep Convolutional Neural Network (CNN). Then the objects are detected and tracked by modified Contrast Model and Kalman filter respectively. After the object detection and object tracking by EODT and RSR-EODT, the frequent actions are obtained by applying STFOM. The frequent actions are considered as normal activities and the infrequent actions are considered as abnormal activities. Thus the proposed EODT-STFOM and RSR-EODT- STFOM methods predict the human activities even at night time and rainy time.
Modeling of Action’s Semantic Memory Incorporated with Procedural and Skill Memory to Perform Tasks
Authors:   Department of Computer Science & Engineering, National Institute of Technology, Patna, Bihar, India., Shrivastava* Rahul , Kumar Prabhat ,   Department of Computer Science & Engineering, National Institute of Technology, Patna, Bihar, India., Tripathi Sudhakar ,   Department of Computer Science & Engineering Rajkiya Engineering College Ambedkar Nagar, UP, India.
Published: October 2019

In this paper, a computational model is proposed to mimic an action’s semantic, procedural and skill learning’s by an abstract modeling of cortical columns of the Neocortex, Basal ganglia and Cerebellum brain region. In proposed work, the action semantic Learning makes a robot capable to learn an action in terms of their body parts movement sequence that allows it to recognize the learnt action by seeing as well. Whereas in procedural, it allows to learn tasks in the form of action’s hierarchy and makes it capable to capture the environmental features as a context for action’s activations. The skill memory also been added in the proposed work which allows an agent to translate the action as per the current demand of the action. Also, the model has used Vnect model of computer vision to map the human motion into sequence of 3D skeleton of human body, therefore the model can learn by seeing, like humans. In experimental work, the model is tested on vague samples of few actions, where the model is found robust in action recognition task and performed well as per the expectations.
Near Surface Characteristic: Hybrid Fiber Reinforced Concrete With Different Aspect Ratio
Authors:   pursuing Doctorate of Philosophy under Visvesvaraya Technological University, Belagavi, Karnataka., M. P* Mr. Rudraswamy , Patagundi Dr. B. R. ,   B.E. and M.Tech. Degrees from NITK, Suratkal Karnataka; PhD from Shivaji University, Kolhapur. India., Prakash Dr. K. B. ,   principal of Government engineering college Haveri.
Published: October 2019

The present work is enhancement of near surface characteristics for hybrid fiber reinforced concrete (aspect ratio 40+100). Here in this research work an attempt has made to study water absorption values for different types of fiber reinforced concrete, which are having different aspect ratios like 40, 100 and 40+100. Concrete mix along with fibers are casted and cured for 28days. Both water absorption test and sorptivity tests carried on hardened concrete. The main objective is to check variation in absorption values due to addition of different types of fibers. Here totally five different types of fibers are considered like steel fiber, Galvanized iron fibres, High density polyethylene fibres, waste plastic fiber and polypropylene fibers Experimental investigation shows that except polyprolene hybrid mix concrete other hybrid mixes has showed good results. But as compared to mono fiber reinforced concrete hybrid fiber reinforced concrete has showed better results. This research was aimed to provide benchmark for future research works on near surface characteristics of hybrid fiber reinforced concrete.
Seismic Performance of Reinforced Concrete Frame with Steel Bracing System
Authors:   Structural Engineer, Vellore Institute of Technology, Chennai, India., Khattar* Somil , Muthumani K. ,   Professor, Vellore Institute of Technology, Chennai, India.
Published: October 2019

The design of the 15 storey R.C building (seismic zone V) is made in accordance with IS 456:2000 using ETABS software. It is already reported that provision of concentric bracing throughout the building are reliable during seismic activity. Hence, this work is aimed to improve the performance of multi storey R.C. building by provision of eccentric steel bracing through analysis. Different types of bracing such as V bracing, Chevron bracing and Diagonal bracing are provided in concentric and eccentric manner. The effect of distribution of steel bracing throughout the height of the building is examined. It is found that the deflection in the building increases with increase in eccentricity. Moreover, V type bracing with 10 percentage eccentricity is found to be most reliable under seismic activity compared to other arrangements.
Novel Assessment of Innovation in Projects and Mega-Projects
Authors:   Department of Mathematics, Computer and Information Technology, Hassan II University Casablanca, Ben M'sik School of Science, TIM, BP 7955 Casablanca, Morocco, Smaiti* Marwane , Hanoune Mostafa ,   Department of Mathematics, Computer and Information Technology, Hassan II University Casablanca, Ben M'sik School of Science, TIM, BP 7955 Casablanca, Morocco
Published: October 2019

A project manager / investor / decision-maker has limited resources. To improve project management and results, innovative technology can be introduced, or available resources can be managed in an innovative way. We note this in this paper: innovative substance or innovative use. We will develop a novel, user-friendly model to guide project managers, senior management, city councils and political / economical leaders in their choices for the utilization of technology in projects and mega-projects.