bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influencing Factors of Organizational Excellence on Corporate Foresight: Artificial Intelligence as Moderator
Authors:   Hasan is doing his Ph.D. in Business Management at UniversitiSains Malaysia., AlMujainiis Hasan , Abudaqais Anas ,   Anas is doing his Ph.D. in Business Management at UniversitiSains Malaysia., Hilmiis Dr. Mohd ,   professor in technology and innovation management at UniversitiSains Malaysia
Published: August 2019

Malaysian oil and gas industry still have underperformed with high potential and industry had laid emphasis on efforts of organizational excellence with context of improving the corporate foresight. It has presence of moderating role of artificial intelligence in Malaysian oil and gas industry. Moreover, study was motivated through different findings inconsistent stated in literature on basis of relationship with organizational excellence with corporate foresight. These types of inconsistency have led for the emergence of innovative stream of research which had recommended the systematic investigation of different moderate variables that contributed to the relations among variable. Simultaneously with context to this study, various theories were employed as this comprises resource based view and social exchange theory to give insight within variables relationships in proposed conceptual framework. Apart from this, it has presence of survey questionnaire with random distributed to gas and oil quality’s 932 managers through Malaysia’s big five companies. In this aspect, total numbers of different regained questionnaires were 238 in which only 204 could be implied for purpose of analysis. Further, there is presence of employed correlation along with hierarchical regression analysis with purpose of analyzing the study variables with actual relationships. The outcome reflects positive relationship among principals of organizational excellence and the corporate foresight. While, artificial intelligence moderates the relationship between organizational excellence and corporate foresight. Lastly, this study has been summarized through offering managerial policy along with different theoretical and practical implications and even recommendations of basis of future studies
Quality Improvement of Capacitors through Fishbone and Pareto Techniques
Authors:   Mechanical Engineering Department, ABES Engineering College, Ghaziabad.(Research Scholar Visvesvaraya Technological University,Belgaum, Raman Mr. Ravi Shankar , Basavaraj Prof (Dr.) Yadavalli ,   Mechanical Engineering Department, Ballari Institute of Technology & Management, Ballari,India.,
Published: August 2019

In the present scenario there are various methods are available to improve and control the product quality of any organization but it is necessary to continue monitoring and measuring the process so that product quality can be maintain. Through this paper try to examined the various defects during capacitor manufacturing process by using fishbone and Pareto analysis. To analyze the various defects, three months data has been collected from October 2018 to December 2018 and analyze all the defects through fishbone and Pareto chart. The outcomes of the research show that the maximum problem was arises from the capacitor’s winding and welding process and have to mainly focus on those area so that defects can be controlled up to maximum extend. To minimize all the defects, prepare fishbone diagram which shows all the root causes of defects and afterward analyze through pareto chart. Now follow some suggestive action to reduces the defects and improve the overall quality of the capacitors.
Holistic Model That Affect the Success or Failure of the Implementation of Big Data
Authors:   Assistant Professor, Department of CS, S R Engineering College, India, Byri Divya , Kafila  ,   Assistant Professor, Department of Business Management, S R Engineering College, India, Aluvala Srinivas ,   Assistant Professor, Department of CSE, S R Engineering College, India.
Published: August 2019

Big data defines the substantial volume of data that could be refined as well as examined utilizing modern technology to obtain service market values that will certainly aid institutions to obtain one-upmanships. The present paper targets to build an all natural model that features the elements that would certainly have an effect on the effectiveness or even failing of the application of big data in companies. Additionally, this analysis checks out the chances that companies would certainly achieve coming from applying big data, along with the difficulties that might impair this execution. The model is actually established based upon 3 sizes including carrying out data technique (institution), joint understanding laborer (folks) as well as carrying out data analytics (innovation).
The Effect of Integrated Warehouse Operation Efficiency on Organizations Performance
Authors:   Research Scholar, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India., Buba Mr. Mengistu Guliti , Das Dr. Debi Prasad ,   Assistant Professor, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India., Ghadai Mr. Sanjaya Kumar ,   Research Scholar, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India., Bajpai Dr. Anil ,   Director, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India.
Published: August 2019

Worldwide several firms have suffered a lot of problems in inventory management which concerns their operational achievement. Good inventory management is a means to improve customer service and reduce stock. The objective of inventory management is to handle it in a most reasonable cost and remove the constant accumulations for continuous developments. This paper brings out how to assess the effect of integrated inventory management practices on organizations representation of some selected universities in Amhara region, Ethiopia. To remain competitive, inventory accounts needs a huge capital of an organization and must have a good management in the overall flow of resource from the initial purchase to final usage. Generally, the goal of every business is to hold little inventory and keep their business running. So, those universities in this region have hold a little inventory and make their organizations run well, even determine how much they do have in their store and determine for how long it will serve them.
Design of 3-Bit Digital RF Phase Shifter for Wireless Communication
Authors:   Associate Professor,Department of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore., Nataraj B. , Prabha K.R. ,   Assistant Professor, Department of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore
Published: August 2019

In this paper, a 3-bit digital phase shifter based on switched transmission line technique using coplanar waveguide is proposed. The design has the resonant frequency of 10 GHz which can be used in wireless communication applictaions. Recent developments in radio frequency components development has raised as a significant way for constructing low loss phase shifters. MEMS phase shifters whose insertion loss is low and high isolation uses minimum power. This helps to bring low cost and light weighted phased array antennas. The transmission line length and wavelength decides the characteristics of phase shift. The phase shifter design consists of coplanar waveguides having center conductor width of 100μm and the gap of 14 μm on a FR-4 epoxy substrate with thickness of 1.6mm. The design is simulated using ADS to yield phase shift of 45, 90 and 180. The benefits of digital phase shifters include achieving flat phase over a wide bandwidth as well as having higher power handling and linearity with uniform performance. The phase shifters are used in different fields which includes microwave devices, feeder of radio system, phased array antenna, coherent radio system, etc.
Partially Replacement of Broken Roof Tiles As Coarse Aggregate and Bamboo as Reinforcement in RC Beam
Authors:   Asstiatnt Professor, Civil Engineering Department, Sri Venkateshwara college of Engineering, Bangalore, Karnataka, India,, S PRIYANKA , YASHASVINI D H ,   Asstiatnt Professor, Civil Engineering Department, Sri Venkateshwara college of Engineering, Bangalore, Karnataka, India,, H V SUDHAKAR ,   Asstiatnt Professor, Civil Engineering Department, Alpha college of Engineering, Bangalore, Karnataka, India,
Published: August 2019

Steel is commonly used as reinforcement, the cost of the steel is increases day by day, during the fabrication of steel emits the Co2 and it consumes high energy, for this reason bamboo is substituent material for the reinforcement. Scarcity of aggregate due banned quarries, the industries waste like broken roof tiles cause the environmental pollution, so it can be replaced as a coarse aggregate. In this paper aptness of bamboo used as reinforcement in RC beam with different percentage of roof tiles are replaced as a coarse aggregate. For the bamboo compressive strength, tensile strength and different treatment are performed. The beams are having size 2mx230mmx300mm, strength parameters are compared with conventional beams the roof tiles are replaced 0%, 20% ,40% , 60% and cost comparison are done.
A Novel Algorithm to the Design and Development of Lemon Leaf Fungal Disease Grading and Area Detection in Smartphones using Image Segmentation
Authors:   Ph.D. Research Scholar, Department of Computer Applications, Bharathiar University, Coimbatore, Tamil Nadu, India., Gnanamalar R.Hepziba , Devi Dr.Prof.T. ,   Professor and Head, Department of Computer Applications, Bharathiar University, Coimbatore, Tamil Nadu, India
Published: August 2019

Lemon productivity faces many hurdles due to leaf disease. Human inspection of the stages of lemon leaf diseases is a tedious process, which consumes more time and sometimes leads to error. Without knowing the status of the leaf disease, spraying unlimited pesticides leads to many health issues as well as reduces the harvesting of lemon, which is used for medicine purpose. In order, to overcome such issues “Lemon Leaf Disease Grading System (LLDGS)” has been developed and the paper elaborately explains LLDGS which detects lemon leaf disease and its stages in order to reduce time and errors in diagnoses. Due to the rapid development of smart phones, LLDGS is developed using image processing techniques in android platform that would exceptionally help the farmers in the modern world. The research work is done especially for fungal disease because lemon plants are mostly affected by the fungal disease. The paper describes a novel algorithm for the design and development of LLDGS using image processing techniques to grade the lemon leaf diseases through a sample of 170 fungal diseased lemon leaf images. Finally, the paper presents the result and performance evaluation of LLDGS.
Inference of ADHD using Linear Discriminant Feature Analysis of Brain Caudate Nucleus
Authors:   Associate Professor, Sri S.R.amasamy Naidu Memorial College, Sattur, Tamil Nadu, India, Krishnaveni K. , Radhamani E. ,   Research Scholar, Sri S.R.amasamy Naidu Memorial College, Sattur, Tamil Nadu, India
Published: August 2019

A methodology to inferAttention Deficit/Hyperactivity Disorder (ADHD) from the features of Caudate Nucleus using Linear Discriminant Analysis is proposed in this research work. A Brain Image Data Set containing 40, T2 axial Human ADHD Brain MR Images is created initially. The caudate Nucleus of each image is extracted with Fuzzy C-Means algorithm and stored in the Caudate Nucleus Data Set(CNDS). The texture, intensity and shape based features of CNDS is extracted, analysed and the features which are closely related to the inference of ADHD are identified. With the help of statistical measures and LDA classifier the input images are classified into ADHD and NOADHD classes and further the level of ADHD is identified as Mild, Moderate and severe ADHD images. The LDA classifier results show that out of 40CN brain tissues, 36ADHD images are found with reduced volume, contrast and intensity values compared to control group and 4 images are found with NoADHD. The performanceis evaluated by means of various classification metrics like Confusion matrix, Accuracy measures and Parallel Coordinates Plot. The LDA classifier yields90% of classification accuracy on CN dataset and reveals that the children with ADHD are found with low volume, contrast and Intensity values compared to normal group which suggests the neurologists to diagnose ADHD using Brain scan method instead of Medication or counseling.
Preprocessing and Statistical Analysis of Soil Parameters using Conventional Laboratory Techniques and Non-Imaging Spectral Techniques for Vaijapur Taluka.
Authors:   pursed Bachelor of Computer and Master of Computer Science from Dr. BAM University, Aurangabad, India., R.Bhise Miss.Pratibha , B.Kulkarni Dr.Sonali ,   Professor in Department of Computer Science and IT, Dr.BAMUniversity, Aurangabad, Borole Mr.Vipin Y. ,   Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra.
Published: August 2019

Agriculture is very important factor for all population in India. Indian economy and most of the peoples in India is totally depends upon agriculture and agriculture is depends upon soil quality. Soil provides various ecosystem services and also support to human health. To manage and preserve soil for future generations it is important to know more about soil. Soil quality is composed of its properties such as physical, chemical and biological and also categorized its nutrients in two sections like micronutrients and macronutrients. In soil quality soil macronutrients plays very crucial role for improvement of agriculture. To know about status of soil macronutrients various methods are needed. The main objective of this study is compare soil laboratory analysis methods and soil spectral analysis methods for quantitative estimation of soil macronutrients. With the help of these two methods we accurately predicted the soil macronutrients which helps in estimation of macronutrients and identifying the soil quality. In this study descriptive statistics is used for final estimation of soil macronutrients.We got better results using spectral analysis techniques compare to soil laboratory analysis techniques and this results gives contribution in agriculture sector and also helpful to farmers for taking decision related to crop.
Improve the Material Removal Rate of Electrochemical Grinding on Monel 400 Using RSM
Authors:   Department Of Mechanical Engineering, M.A.M College of Engineering, Trichy, Tamilnadu, India., Mohan P. , Vinothkumar G. ,   Department Of Mechanical Engineering, M.A.M College of Engineering, Trichy, Tamilnadu, India., Thirulogachandar M. ,   Department Of Mechanical Engineering, M.A.M College of Engineering, Trichy, Tamilnadu, India.
Published: August 2019

Electrochemical grinding is combination of electrochemical machining and mechanical grinding process.in this process 90%-98% percentage of material are removed by electrochemical machining, only 3%-5% of materials can only remove by mechanical grinding process. Faradays law of electrolysis (or) reverse electroplating act as a basic principle for this ECG process. This ECG has various advantages than other machining process for high strength materials .low induvial stress, large depth of cut .here Monel 400 alloy take base material ,its Ni-Cu alloy so it’s have very high level corrosion resistance, so it’s used in marine engineering ,heat exchanger. Here silicon carbide abrasive insulated brass grinding wheel used instead of copper bonded diamond wheel. Voltage, electrolyte concentration, electrolyte flowrate take are the parameters of this process. Three factors and two levels of RSM methodology takes for optimization. The Analysis of variance (ANOVA) has been delivers the variation between the parameters performed to develop mathematical model. The parameters high voltage and concentration of electrolyte to produce maximum material removal rate.
Accretion of A New Bitopology
Authors:   Department of Mathematics, Amity Institute of Applied Sciences, Noida, India., Agarwal Poonam , Goel Chandra Kant ,   Department of Mathematics, Amity Institute of Applied Sciences, Noida, India.
Published: August 2019

In this paper the authors have introduced a new function on a bitopological space which provides us with a tool to develop a new bitopology. Various characteristics of the derived bitopological spacehav been studied. two new separation axioms have also been introduced over the bitopological spaces. It is interesting to see that the derived bitopology accepts these new separation axioms in a very natural manner.
Quality Assessment of Road Shoulders using Light Weight Deflectometer and Geogauge
Authors:   Civil Engineering Department, National Institute of Technology, Patna, India,, Dwivedi Shubhm , Suman Sanjeev Kumar ,   Civil Engineering Department, National Institute of Technology, Patna, India,
Published: August 2019

Shoulders are an important element of the highways that provide space for vehicles to stop during an emergency. A well-compacted shoulder provides structural firmness to a pavement by transferring overlying traffic loads to the underlying soil stratum. They provide lateral support to the pavement. In recent years, the use of non-destructive testing devices like Geogauge and Light Weight Deflectometer (LWD) has emerged in our country. The main reason behind this is the inbuilt ability of Geogauge and LWD in the fast estimation of the elastic modulus of a shoulder on top of their ease to port, being cost-effective, the capability to give more amounts of data, etc. Thus, there is a need to assess these devices. The main objective of this paper is to develop correlations between the parameter obtained from these non-destructive devices and destructive test parameterslike dry density and CBR. The tests were conducted on thirty-two locations of road shoulders at the city of Patna, India. Geogauge, LWD and sand replacement or sand cone testing were performed at different locations and soil samples were collected for determination of CBR and water content in the laboratory. The result of regression analysis shows that a significant correlation exists between moduli obtained from the devices under investigation and standard test results i.e. dry density and CBR. These developed correlations may be used by the road engineers for assessment of the quality of the shoulders.
Symmetry Based Feature Selection with Multi layer Perceptron for the prediction of Chronic Disease
Authors:   Department of CSE, NMAM Institute of Technology, Nitte, India., Hegde Sandeepkumar , Hegde Rajalaxmi ,   Department of CSE, NMAM Institute of Technology, Nitte, India.
Published: August 2019

Huge amount of Healthcare data are produced every day from the various health care sectors. The accumulated data can be effectively analyzed to identify people's risk from chronic diseases. The process of predicting the presence or absence of the disease and also to diagnosing the various disease using the historical medical data is known as Health Care Analytics. Health care analytics will improve patient care and also the harness practice of medical practitioner. The feature selection is considered as a core aspect of the machine learning which hugely contribute towards the performance of the machine learning model. In this paper symmetry based feature subset selection is proposed to select the optimal features from the Health care data which contribute towards the prediction outcome. The Multilayer perceptron algorithm(MLP) used as a classifier which will predict the outcome by using the features which are selected from the Symmetry-based feature subset selection technique. The chronic disease dataset Diabetes, Cancer, Breast Cancer, and Heart Disease data set accumulated from UCI repository is used to conduct the experiment. The experimental results demonstrate that the proposed hybrid combination of feature selection technique and the multilayer perceptron outperforms in accuracy compare to the existing approaches.
Designing Of Modeling and Applications in Typical Engineering Process
Authors:   Department of Mathematics, S R Engineering College, Warangal, Anusha G. , Rao S. Vishwa Prasad ,   Department of Mathematics, S R Engineering College, Warangal, Krishna C. Bala Rama ,   Department of Mathematics, S R Engineering College, Warangal
Published: August 2019

A lot importance is offered on using computer systems and also calculators as devices to solve mathematically designed bodily troubles. The outcome is actually a technique that combines mathematical theory into services for real-world concerns, using the best of both globes: maths and also calculations. Engineering mixes applied algebraic, scientific, and also specialized concepts, to give substantial final result which can be created, created, and designed. Design varies from scientific research in that it have to take demands into account featuring expenses, security, functionality and also constraints on information. All engineering job is actually regulated through security specifications, and also issues of licenses as well as design security may also arise.
Development of Automatic Home-Based Fish Farming using the Internet of Things
Authors:   Department of Computer Science, Suan Sunandha Rajabhat University, Bangkok, Thailand., Janpla Satien , Tachpetpaiboon Nisanart ,   Department of Computer Science, Suan Sunandha Rajabhat University, Bangkok, Thailand., Jewpanich Chaiwat ,   Department of Educational Technology and Computers, Suan Sunandha Rajabhat University, Bangkok, Thailand.
Published: August 2019

This research purposed to design an automatic home-based fish farming using the internet of things and to evaluate its efficiency. There were 3 processes in this research: 1. creating a home-based fish farming environment (fish pond) 2. designing and developing home-based fish farming by using the internet of things and 3. experimenting and implementing the system. The fish pond (90 x 180 x 50 cm) was made up of 90 blocks. It was coated with waterproofed plastic in order to contain a maximum of 80 cm x 170 cm x 40 cm. or 0.544 m3 of water. The automatic home-based fish farming system using the internet of things consisted of 6 parts in the form of 1. A NodeMCU Microcontroller 2. An automatic fish feeder 3. A relay module 4. Home Wi-Fi 5. Web Application 6. Line Notify. The NodeMCU Microcontroller was the main module use to control the automatic working of the system. The experiment resulted in a number of findings. Firstly, Fish feeder experiment, Experiment for the fish feeder to release food for 30 grams, 5 times, average time 23 seconds, error rate + 8.70%, -7.25%; Experiment for the fish feeder to release food for 45 grams, 5 times, average time 35 seconds, error rate + 10.00%, -8.57%; Experiment for the fish feeder to release food for 60 grams, 5 times, average time 48 seconds, error rate + 2.08%, -5.27%; finally, 75g fish feeder, 5 times, average time 75 seconds, error rate +8.33%, -8.02%. As a result, the dispensing variation was no more than ±10%. Secondly, the timing of this machine was divided into 4 periods: during days 1 to 30, it dispensed food 30g. During days 31 to 60, it dispensed food 45g. During days 61 to 90, it dispensed food 60g. During days 91 to 142, it dispensed food 75g. It would feed 2 times: 7 am. and 6 pm. each day. Thirdly, the test was to turn on and off the water and oxygen pumps by just clicking a button on the web application. The system was used to feed 80 3-inch long catfish over a period of 142 days. At the end of the period, 43 catfish were left with 37 having died. The survival rate was 54%. These fish weighed 5,380 grams in total and their growth varied. There were 24 small fish which weighed 120-220 gram (61%), 10 medium sized fish which weighed 230-330 (23%) and 7 large fish which weighed 340-440 (16%). As a result, this system could be used for feeding fish, but it needs some improvements such as the introduction of a waste water monitoring system and an automatic water changing system which would enhance the automatic working of the system.
Prediction of Option Price using Ensemble of Machine Learning Algorithms for Indian Stock Market
Authors:   Department of Applied Mathematics, MANIT, Bhopal, MP, India., Shrivastava Payal , Verma Chandan Kumar ,   Department of Applied Mathematics, MANIT, Bhopal, MP, India.
Published: August 2019

The non-deterministic behavior of stock market creates ambiguities for buyers. The situation of ambiguities always finds the loss of user financial assets. The variations of price make a very difficult task to predict the option price. For the prediction of option used various non-parametric models such as artificial neural network, machine learning, and deep neural network. The accuracy of prediction is always a challenging task of for individual model and hybrid model. The variation gap of hypothesis value and predicted value reflects the nature of stock market. In this paper use the bagging method of machine learning for the prediction of option price. The bagging process merge different machine learning algorithm and reduce the variation gap of stock price.
Speed Characteristics of Two-Fold Sliding Mode Control of BLDC Motor
Authors:   Department of Electrical and Electronics Engineering, ANITS (A), Visakhapatnam, India., Murali S. Bala , Rao Dr. P. Mallikarjuna ,   Department of Electrical Engineering, A. U. College of Engineering (A), Visakhapatnam, India.
Published: August 2019

BLDC motors are generally implemented in copious industrial processes because of its high proficiency, large torque and minimum volume. The variation in load torque, causes the variation of speed in BLDC motor, which leads the complete system in unstable condition. In this paper a robust first-order SM controller scheme depends on twofold controlling algorithm for angular velocity and also current control in Brushless DC motor to attenuate the chattering problems. Two cascaded sliding mode controllers of first-order are used and first sliding mode controller generates stator currents based on speed error then the second SM controller generates voltage based on current-error in stator which runs the universal bridge by this controlled voltage source. In addition to the method suggested by Slotine, two feed forward loops are added to both speed and current errors to improve the response. The existing sliding-mode control is unresponsive to uncertainties and will cause undesirable chattering problems. To overcome this snag, a manual control law in conjunction with Sliding mode control is utilized that provides smooth and chattering free actual control signal. The overall system stability performance is implemented in MATLAB/SIMULINK and simulation results shows that proposed scheme is robust with respect to uncertainty in the system.
VM Selection and Allocation Policy to Optimize VM Migration in Cloud Environment
Authors:   Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, India., Garg Neha , Singh Damanpreet ,   Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, India., Goraya Major Singh ,   Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, India.
Published: August 2019

Cloud computing, a metered based technology provides the services using virtualized technology over the internet. In the cloud environment, to improve the performance (such as utilization of the resources, energy minimization) extreme number of virtual machines (VMs) can be installed on the servers as per their resource capacity. In this way, servers can be overloaded. Overloaded servers consume more energythan normal status servers. VM migration (VMM) is an efficient technique to become a server in a normal state. VMM technique is used to consolidate the resources to increase resource utilization (RU) and reduceenergy usage. In the VMM technique, selection of VM such as which VM is migrated from one server to another server and allocation of VM on servers is an important aspect. Appropriate VM selection declines the numeral of VMMs and increasesenergy efficiency. Appropriate VM allocation declines the server to become overloaded. In this paper, the VM selection and allocation strategy is presented. CloudSim toolkit is used to verify the strength of proposed VM selection and allocation algorithm. Proposed VM Selection algorithm (MaMT) performs better than existing MiMT algorithm in terms of total energy consumption, number of hosts shut down, number of VMM, and average Service Level Agreement (SLA) violation rate. MaMT algorithm with resource aware provisioning (RAP) and MiMT+RAP algorithm combines both VM selection and allocation policies. RAP algorithm used both energy and RU parameters while allocating VM to the server.MaMTreduces the energy consumption up to 7.25% and reduces the SLA violation rate up-to 2.6% in comparison to MiMT algorithm. When VM selection and allocation policies combines together than more system performance is improved. MaMT+RAPreduces the energy consumption up to6.76% and reduces the SLA violation rate up-to 0.22% in comparison to MaMT algorithm.MiMT+RAPreduces the energy consumption up to15.23% and reduces the SLA violation rate up-to 0.95% in comparison to MiMT algorithm.
Defect Prediction and Dimension Reduction Methods for Achieving Better Software Quality
Authors:   Department of Computer Science and Engineering, Periyar Maniammai University, Vallam, Thanjavur., P Dhavakumar. , N. P Gopalan. ,   Department of Computer Application, National Institute of Technology, Tiruchirappalli.
Published: August 2019

In quality of software, a fault discovery course is anticipated; intended to recover the taking up of various methods using cluster classifiers. Initially the classifiers are qualified on software record and then utilized to forecast if a forthcoming transformation originates a defect. Shortcomings of previous classifier based error prediction methods are inadequate presentation for realistic utilization and slow-moving forecast times due to a huge number of learned machine characteristics. Feature selection is a procedure in choosing a subset of pertinent characteristics so that the eminence of forecast replica can be enhanced. So that prediction recital of grouping techniques will be enhanced or sustained, whereas learning instance is considerably abridged. This effort commences by presenting a general idea of the datasets for error prediction, and then features a novel procedure for feature assortment by means of wrapper methods namely Fuzzy Neural Network (FNN) and Kernel Based Support Vector Machine (KSVM). The features chosen from FNN and KSVM are measured as significant characters. This effort examines numerous feature selection wrapper methods that are normally appropriate to grouping based error prediction. The system castoffs not as much of significant characters until optimal grouping recital are attained. The whole number of characters utilized for guidance is considerably reduced, frequently to lower than 15% of the unique. The general performance metrics is make used to estimate grouping systems such as accurateness, Recall, Precision, and F-Measure. It demonstrates that the anticipated Hybrid Hierarchical K-Centers (HHKC) grouping executes enhanced software quality compared to conventional grouping methods.
Parameter Tuning Method for Genetic Algorithm using Taguchi Orthogonal Array for Non-linear Multimodal Optimization Problem
Authors:   Assistant Professor, Amity University, Jaipur, Rajasthan, India, Naruka Bhagyashri , Yadav Ashwini Kumar ,   Amity University, Jaipur, Rajasthan, India, Sharma Shweta ,   Amity University, Jaipur, Rajasthan, India, Rathore Janesh Singh ,   Amity University, Jaipur, Rajasthan, India
Published: August 2019

Genetic algorithm (GA) is the most widely used meta-heuristic optimization algorithm that can solve complex large scale optimization problems successfully. The only problem lies with the setting of GA control parameters and their levels for the optimal performance of the algorithm. The statistical method can be used for parameter tuning that allows us to collect data properly. Also, it analyzes the collected data accurately and presents the appropriate results. For statistical analysis, Taguchi’s robust factorial design which is highly fractional in nature with a special set of L32 orthogonal array (OA) is used. Taguchi’s robust design is a proficient method to find an optimum solution with a minimal number of designs of experiment (DOE). Analysis of variance (ANOVA) is conducted to check whether GA control parameters are statistically significant or not for non-linear multimodal optimization problems. Taguchi OA design and ANOVA analysis experimental study is conducted using Stat-Ease software and for the Genetic Algorithm control parameter setting GA solver of MATLAB is used.
Camera-Based Bi-lingual Script Identification at Word Level using SFTA Features
Authors:   Professor, Department of Computer Science, Gulbarga University, Kalaburagi, India., Dhandra Dr. B. V. , Mallappa Mr.Satishkumar ,   Research Scholar, Department of Computer Science, Gulbarga University, Kalaburagi, Karnataka, India, Mukarambi Dr. Gururaj ,   Assistant Professor Department of Computer Science, Gulbarga University, Kalaburagi, India.
Published: August 2019

Most of the documents in various application areas like Government, Business and Research is available in the form of bi-lingual/multi-lingual text document. The multilingual documents are captured from video/camera for identification of script of the text document for automatic reading and editing. In this paper, an attempt is made to address the problem of script identification from camera captured document images with SFTA features. The input image is decomposed into a group of binary images by applying TTBD with fixing the number of the threshold as t n =3 empirically, on each decomposed binary image, Box Count, Mean Gray Level, and Pixel Count are extracted to form the feature vector. This feature vector is submitted to K-NN classifier to identify the scripts of the input document image. In all 10 scripts of the indian languages are considered along with common English language as bi-lingual documents. The novelty of the paper is that 7 features are selected as potential features to obtain the highest accuracy. Features like Box Count (3), Mean Gray Level (2), and Pixel Count (2) have obtained the 87.02% recognition accuracy for English and Hindi Script combinations for the dataset collected and encouraging results for other combinations. These 7 potential features were selected using the technique named as feed-forward feature selection, from the set all 18 features.
Bancassurance – A Panacea for Increased Sales: Insurance Companies Perspective
Authors:   Research Scholar (Part-Time), Yogi Vemana University, YSR Kadapa-516005, Andhra Pradesh, Assistant Professor, MarriLaxman Reddy Institute of Technology & Management, Dundigal, Hyderabad-500043, Telangana, India, Mazeed Shaik Abdul , Reddy R. Sarveswara ,   Research Scholar, Rayalaseema University, Kurnool-518004, Andhra Pradesh, Assistant Professor, Dr.K.V. Subba Reddy School of Business Management, Kurnool-518218, Andhra Pradesh, India., Lakshmi C. Sowbhagya ,   Research Scholar (Part-Time), Yogi Vemana University, YSR Kadapa-516005, Andhra Pradesh, Assistant Professor, Chaitanya Bharathi Institute of Technology, Proddutur, YSR Kadapa-516360, Andhra Pradesh, India.
Published: August 2019

Banking industry has grown quickly all over the world, at the same time insurance industry has also grown rapidly in the same cut throat economic environment. With the entry into non core products or services like insurance and securities markets, these days banks have increased their businesses. The integration of financial markets, emergence of new technologies and expansion of non-banking activities has a great impact on baking operations. Thus it results in opening doors for the business of non core products like insurance and securities (bancassurance) by banks. The only intention behind this diversification of business by the banks is to provide ample investment alternatives to the common people who do not have access to various financial products and securities so that they can maximize the returns on their investment. The increasing popularity of bancassurance has widened the scope of research in this area. In this study an attempt is made to know the impact of bancassurance on customers while they made decisions to purchase the insurance policies.
Decision Rule Induction: Relieving Complexity in Detecting Defection
Authors:   Research scholar at Amity University Uttar Pradesh, Lucknow Campus., Ahmad Suhel , Srivastava Dr. Alpana ,   Professor at Amity University Uttar Pradesh, Lucknow Campus., Sharmais Dr. Seema ,   Faculty Department o Economics and Statistical Analysis in the Department of Management Studies at IIT Delhi.
Published: August 2019

Customer attrition has become a serious problem globally, particularly in telecom service, resulting into substantial revenue decline. Attrition may result in accumulation ofdues as a resultof payment defaults.Proactive identification of potential attrite will help in retention as well as minimizing loss of revenue.For attrition detection many robust but complex algorithms are used. Depending on the severity of error, the complexity can be lessened and thus cost. Two methods of decision rules (1R& C5.0) are used to predict the attrition and predictive accuracy is judged withconfusion matrix. Comparison between models is made by sensitivity and specificity. It was found that 1R has a sensitivity of .60 against .69 for C5.0 and hence, the performance is not significantly different. It is suggested that 1R could be used instead of more complex algorithmsand also it can be adopted for benchmarking.
Application of Fractional PID Controller to Single and Multi-Variable Non-Minimum Phase Systems
Authors:   Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India, Shah Pritesh , Sekhar Ravi ,   Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India., Agashe Sudhir ,   Department of Instrumentation and Control, College of Engineering, Pune, India.
Published: August 2019

A non-minimum phase system has the unique characteristic of undershoot or over and undershoot based on the number of zeros and the location of zeros in the systems. A fractional PID controller has the ability to capture more dynamics, as there are two more parameters to tune compared to a traditional PID controller. In this paper, a fractional PID controller is designed for single and multi-variable non-minimum phase systems. A simple optimization method for the tuning of a fractional PID controller has been applied. Six different single variable plants were simulated covering different cases of non-minimum phase systems. Simulation results showed that zero crossing is reduced to a greater extent by fractional PID controller as compared to traditional PID controller for single variable systems. This paper also provides experimental validations for design and tuning of a fractional PID controller for a multi-variable non-minimum phase quadruple-tank system. Fine tuned experimental results agree well with simulation results, thereby validating the applicability of the fractional PID controller for multi variable non-minimum phase systems.
DSWS- Distributed Sleep/Wake Scheduling Scheme for DEC Protocol in Wireless Sensor Networks
Authors:   Research Scholar, KL University, Guntur & Senior Assistant Professor, ECE Department, PVPSIT, India., Mohammad Habibulla , Sastry Dr. A S C S ,   Professor, Electronics and Communication Department, KL University, Vaddeshwaram, India
Published: August 2019

To improve the lifespan by reducing the energy utilization of battery-driven sensors in wireless network applications has grown into a challenging task in the fields of communication. Sleep/wake programming mechanism is evidenced to be an well-organized method to meet the challenges and to maintain good energy conservation in sensor networks. In this study, we take enhanced DEC (Deterministic Energy Efficient Clustering protocol) with distributed sleep/wake scheduling scheme i.e. purely deterministic model that make effective use of clustering to organize the WSN. In this proposal cluster division of sensor nodes is based on coverage sensing metrics and through dynamic selection mechanism, it allows additional node in every group to be active concurrently. The results obtained using the concept of DSWS-DEC outperform various existing in terms of coverage and energy preservation.
Mechanical And Water Absorption Properties of Madar And Bauhinia Racemosa Natural Fiber Composites
Authors:   Professor, Department of Mechanical Engineering,CMR Institute of Technology, Hyderabad., Kumar Dr.S.Sathees
Published: August 2019

This paper focus on Madar and Bauhinia Racemosa fibers has high potential as reinforcing agents in polymer composites. The composites plates were fabricated by hand layup method with varying the fiber weight percentage of 5%,10%,15% and 20% on mechanical and water absorption properties are analyzed. The mechanical properties of such as tensile, flexural and impact properties of madar and Bauhinia Racemosa fiber mat reinforced polyester composites were studied at first time in this work. The tensile, flexural and impact strength of Bauhinia Racemosa fiber mat reinforced polyester composites had proved higher strength performance than the madar fiber mat reinforced polyester composites.
A Quality of Service (QoS) Aware Scheduling Algorithm to Boost QoS of Cell-Edge Users in LTE Networks
Authors:   student of ME in Department of Electronics and Telecommunication, Shri G. S. Institute of Technology and Science, Indore India, Lodwal Himani , Yadav Dr. Anjulata ,   Associate Professor in Shri G.S. Institute Of Technology and Sc. Indore (MP), India., Panchal Manish ,   Associate Professor in the Department of Electronics and Telecommunication Engineering of the Shri G S Institute of Technology and Science (SGSITS) Indore India
Published: August 2019

LTE is the abbreviation of Long Term Evolution. LTE networks are developed to provide enhanced Quality of Service (QoS), as today’s cellular world and its high speed multimedia applications demand variety of QoS along with a high speed data rate. Scheduling is a key feature of any network to achieve QoS requirements. The QoS widely depends on the distance of user from the Evolved- Node-B (eNB). The user near eNB experience good QoS and the user far away from eNB experiences poor QoS. The system performance is widely affected due to this. Hence, the ultimate and supreme goal of this research work is to enhance the QoS of the cell edge user and improve network performance. Proposed scheduling algorithm i.e. Improved Extended Modified Largest Weighted Delay First (IE-MLWDF) improves the cell edge throughput along with QoS of the cell - edge users. The paper compares IE-MLWDF with its previous versions namely Modified Largest Weighted Delay First (MLWDF) and Extended - MLWDF in terms of various network parameters. This paper presents a detailed analysis of a scheduling algorithm to enhance QoS of cell edge users to provide better network goals. This algorithm can further be extended or improved to make it more effective.
Reputation and Security Based File Sharing Model using P2P Networks
Authors:   Research Scholar, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, S Vimal , Srivatsa Dr. S. K. ,   Retired Professor, MIT, Chennai, Tamilnadu
Published: August 2019

The present system fails to utilize the trust in the social network which is based on Peer to Peer (P2P) file sharing systems. To overcome this issue, a trust management system named “Social Link” is used to utilize the social network and predefined transaction links. The Social Link manages the novel weighted transactions and networks. The link is constructed using the historical file transaction. Two friends can share their files and increased trust can be guaranteed with the help of Social Link. The Networkof Weighted Transaction (NWT) can be calculating the successful transaction and it finds trust over the client on server. By this process, Social Link will reduce transaction misbehaving, avoids free riding and promotes nodes to transact data files to non friends. Whitewashing and collision can also be rectified using Social Links.
D2d Big Data Analytics for User Behavior over Cellular Networks for Improving Content Desliveries
Authors:   Research Scholar, Department of Computer Science, Bharath University, Chennai, Tamilnadu., K Baalaji. , Khanna Dr.V. ,   Dean Info, Bharath University, Chennai, Tamilnadu.
Published: August 2019

Nowadays cellular phones are profoundly increasing and present network capacity need to be increased to meet the growing demands of user equipment (UE) that has led to evolution of cellular and communication networks. Device-to-Device (D2D) communication is a usage technology that extends enormous features that can be incorporated with LTE and conssidesred as a finest technological componentespecially for the 5G network. Generally the 5G wireless networks are being introsduced to improve the present technology that meets the future demands extending efficient and reliable solutions. This Device-to-Device (D2D) communication can be established within LTE that limits to its proximity and comes with various advantages such as increase of spectral efficiency, energy efficiency, reduction of transmission delay, efficient offloaded traffic, avoiding congestion in cellular network. This paper deals D2D entities that include user behaviors, content deliveries and characteristics in big data platform that utilizes sharing large scale data accurately and effectively. Besides D2D, the proposed work builds concept of big data analytics integrated with D2D for effectively improving the content deliveries while offloading large data set.The presentwork also discussesbig data predictive analysis for the users based on D2D network services that help for further work.
Fresh and Hardened Properties of Hybrid Fibre Reinforced Self Consolidating Concrete Containing Basalt and Polypropylene Fibres
Authors:   Department of Civil Engineering, ABES Engineering College, Ghaziabad, India., Khan Uzair , Khan Rizwan A ,   Department of Civil Engineering, Z. H. College Engg. & Tech., Aligarh Muslim University, Aligarh, India., Pandey Naveen Kumar ,   Department of Civil Engineering, ABES Engineering College, Ghaziabad, India., Tyagi Ayush ,   Department of Civil Engineering, ABES Engineering College, Ghaziabad, India.
Published: August 2019

Evidences as well as outcomes proved that the progress of self-consolidating concrete is comprehensive benchmark in the construction area. Due to its highly beneficial characteristics, self-consolidating concrete is eminently preferred and widely used all around the Globe. Self-consolidating concrete is that inventive concrete which does not need any assistance of vibration by any means in order for its placement and compaction. Its ability to flow under its self-weight allows complete filling formwork. Hence, successful results to attain full compaction, even in the existence of clogged reinforcement. Intension of this research paper is to put light on the fresh properties of hybrid fibre reinforced self-consolidating concrete (HFRSCC)such as T50cm, L-box, spread flow, V-funnel and properties of hardened like compressive strength, flexural strength and ultra-sonic pulse velocity at the period of 7 and 28 days. The properties of hardened HFRSCC is greatly improved by the process of addition of fibres.