19c96fd517d854497e8-564d 20220106040931417 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Engineering and Advanced Technology IJEAT 22498958 10.35940/ijeat.2249-8958 https://www.ijeat.org/ 10 30 2019 9 1 10.35940/ijeat.9.1 https://www.ijeat.org/download/volume-9-issue-1/ Assistant Professor, Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi-642001, India. R. Nandhakumar Antony Selvadoss Thanamani Associate Professor & Head, Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi-642001, India The Gene Expression data contains important information about the biological reactions that are carried out in creatures that are based on the surroundings. For understanding those processes in a better manner, the hidden expressions from the high-dimensional non-linear data are to be processed effectively. Moreover, the intricacy of biological data increases the challenges in High-dimensional non-linear gene data processing. For handling the complications, incorporation of clustering techniques is employed for identifying the patterns appropriately. Furthermore, this makes clarity in gene functions, regulations, inherent expressions, categories from noisy data input. In this paper, an Integrated Model for Optimization and Clustering (IMOC) is developed for efficient gene data processing for cancer detection application. Two efficient algorithms are integrated in this work, Ant Colony Optimization for effectively determine the features of gene data and Density based Clustering (DENCLUE) is for clustering the DNA data based on the determined features. For evaluating the proposed model, the benchmark datasets such as DNA Microarray Data of Leukemia and DNA Microarray Data of Colon Cancer are used. Further, the results show that the proposed model outperforms the existing models in accuracy and efficiency rates. 10 30 2019 603 608 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A9753.109119 https://www.ijeat.org/portfolio-item/A9753109119/ Department of Computer Technology, Madras Institute of Technology Campus, Anna University, Chennai, India - 600 044, India, S. Muthurajkumar The Cloud Storage can be depicted as a service model where raw or processed data is stored, handled, and backed-up remotely while accessible to multiple users simultaneously over a network. Few of the ideal features of cloud storage is reliability, easy deployment, disaster recovery, security for data, accessibility and on top of that lesser overall storage costs which removes the hindrance of purchasing and maintaining the technologies for cloud storage. In this modern technology world, massive amount of data are produced in day to day life. So, it has become necessary to handle those big data on demand which is a challenging task for current data storage systems. The process of eliminating redundant copies of data thereby reducing the storage overhead is termed as Data Deduplication (DD). One of the ultimate aim of this research is to achieve ideal deduplication on secured data of client side. On the other hand as the client’s data are encrypted with different keys, the cross user deduplication is merely impossible as having a single key encryption among multiple user’s leads to an in secure system resulting in fragile to client’s expectations. The proposed research adapts Message Locked Encryption (MLE) technique that looks for redundant files in cloud before uploading the client’s file which eventually reduces the storage. Since the redundant files are swept, the network bandwidth is considerably reduced with respect to the redundant contents uploaded several times. 10 30 2019 609 615 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.E7371.109119 https://www.ijeat.org/portfolio-item/e7371068519/ Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P., India Research Scholar JNTUK, Kakinada A.P, India N. SREERAM* Dr.M.H.M. Krishna Prasad Professor of CSE, Vice-Principal & Coordinator-TEQIP-III,, University College of Engineering Kakinada(A) J.N.T.U. KAKINADA Dr.kK. Satya Prasad Professor of ECE (Rtd), ,, University College of Engineering Kakinada(A) J.N.T.U. KAKINADA With the advent of IoT, number of IOT-devices are deployed in the city to acquisition data. These devices acquire enormous data and to analyze such data one need to configure novel hardware to scale up the existing servers and need to develop an application with précised framework. This work recommends an adapted scale out approach in which huge multi-dimensional datasets can be processed using existing commodity hardware. In this approach, Hadoop Distributed File System (HDFS) holds the huge multi-dimensional data to be processed and it can be processed and analyzed by using MapReduce (MR) framework. In the proposed approach, we implemented an optimized repartitioned K-Means centroid based partitioning clustering algorithm using MR framework for Smart City dataset. This dataset contains 10 million objects and each object has six attributes. The results show that the proposed approach is a scalable approach to compute intra cluster density and inter cluster density effectively. 10 30 2019 616 620 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8069.109119 https://www.ijeat.org/portfolio-item/f8069088619/ Department of CSE, Kongu Engineering College, Perundurai, India. K.S. Kalaivani Prof.S. Kuppuswami Principal, Kongu Engineering College, Perundurai, India. Sentiment analysis is the technique of automatic detection of the belief or the mood of an author towards a certain subject in textual form. To extract the opinion present in text, the machine needs expertise in the area of natural language processing. In this paper, machine learning based document-level sentiment classification is performed on Amazon product reviews to classify them as positive and negative. Two NLP based feature extraction techniques (Word Relation and POS based) are used in this study to determine the features that are sentiment bearing. The features are extracted as basic features (unigrams, bigrams and trigrams) and their combinations (unigrams+bigrams, unigrams+trigrams, unigrams+bigrams+trigrams). In order to identify the features that are most informative and to bring down the computational time of the classification algorithms, feature selection techniques are used. Performance of independent and combined feature sets is assessed using accuracy, precision, recall and F-measure. From the experiments conducted, it is observed that combined features outperformed independent features using Boolean Multinomial Naive Bayes (BMNB) classifier. 10 30 2019 621 626 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8290.109119 https://www.ijeat.org/portfolio-item/f8290088619/ Lecturer Singaperbangsa University Karawang Indonesia. Tubagus Ahmad Darojat Abdul Rahmat Lecturer Gorontalo State University, Indonesia Lucyane Djaafar Lecturer Gorontalo State University, Indonesia This research is to find out, explain and analyze the influence as well as the partial and simultaneous influence of work discipline, work motivation and leadership on employee performance at PT. Devrindo Widya Karawang - Indonesia. There were 82 employees of which 68 were used as the sample group. The research method used is the descriptive and verification method. The following conclusions result from the analysis of research data: 1) work discipline is good, 2) work motivation is good, 3) leadership is good, and 4) employee performance is good. There are influences both partially and simultaneously of work discipline, work motivation and leadership on employee performance at PT. Devrindo Widya Karawang - Indonesia. 10 30 2019 627 630 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8374.109119 https://www.ijeat.org/portfolio-item/F8374088619/ PhD Scholar, Department of mechanical Engineering NIT Agartala, Tripura. Kiran Kumar Billa G.R.K. Sastry Professor, Department of mechanical Engineering NIT A.P, A.P. Madhujit Deb Assistant Professor, Department of mechanical Engineering NIT Agartala, Tripura The present investigation delivers a comprehensive viewpoint on the current artificial intelligence (AI) meta-modelling in diesel engine system, particularly in the domains of multi-objective optimization. The relevance to the benefits of AI built modelling stratagems, and the probable Response Surface Methodology has been efficient with the consecutive growth in the current domains of the compression ignition technology. The study establishes the fundamental significance of inspecting certain multi-objective optimization stratagems matching with the accumulating need to deal with emission-performance trade-off trials of the compression ignition technology. To achieve the reliability and versatility of such model centered multi-objective optimization strategies, the current study delivers a unique case-study presenting the creditably accurate model-based standardization in an existing diesel engine. Therefore, n-Octanol produced in renewable ways, methyl esters of fish oil (MEFO) blended with diesel is used as fuel and the experiments were designed by Design of Experiments (DoE) based on response surface methodology (RSM) architecture. The results depicted that the tailor-made fuels proved their ability in terms of both performance and emissions when compared to mineral diesel. The model is further tested on a statistical platform with some special error matrices like Mean Squared Relative Error, MSRE, and Nash–Sutcliffe Coefficient of Efficiency, NCE along with conventional model testing metrics like MSE, RMSE and R which proved that the proposed model is robust and efficient in predicting the input-output paradigm. The ranges of correlation coefficients R, R2 and NCE are 0.99786 - 0.999992, 0.99786-0.999992 and 0.9957 – 0.999984 respectively. And the ranges of the error metrics Theil U2 and MSRE are 0.004048 0.065246 and 6.07E-07 to 0.000158 respectively. Optimization of input parameters was performed using the desirability approach of the response surface methodology for better performance and lower NOx and CO emission at a desirability index of 0.986. Experimental validation suggested a blend of 20% MEFO and 10% n-Octanol with petrodiesel at full loads were found to be optimal values for the test engine. 10 30 2019 631 645 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8746.109119 https://www.ijeat.org/portfolio-item/f8746088619/ Associate Professor at Mahendra Engineering College, Namakkal A.Neela Madheswari S. Ambareesh Ph.D as a part-time scholar in faculty of Information and Communication Engineering from Anna University The growth of technologies lead to a lot of improvements in almost all the fields. A huge man power is used in all the fields especially in manufacturing sectors. We can reduce man power mainly for the work which can be done by machines in an efficient manner. Industry 4.0 is focusing mainly for this purpose. Cyber physical systems are used to build a system with better communication and data collection in a shared and collaborative manner from all components of that system in safe and reliable manner. As though CPS is starting its implementation in all the fields this work deals mainly with role of cyber physical systems for smart learning environments. This work forms a basic study of those systems. 10 30 2019 646 651 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8849.109119 https://www.ijeat.org/portfolio-item/f8849088619/ Electrical and Electronics department, CVR College of Engineering, Hyderabad, India. Phani kumar K.S. V* S. Venkateshwarlu Electrical and Electronics department, CVR College of Engineering, Hyderabad, India. Power quality is a growing concern with sensible and critical loads asking for stringent frequency regulations. The distributed generation sources like Solar Photovoltaic, Diesel Generator, Fuel Cells, and Battery driven Electric Vehicles (BEV) are considered as power sources in the system. For the power-sharing among these generators, a central controller with a novel simple adaptive-additive control strategy is used. Each source has a local controller to regulate the power outputs. This paper presents a Neuro-Fuzzy controller for operating Solar Photovoltaic power at a Limited Power Point while a novel Neuro-Tuned-Fuzzy Controller decides which BEVs to be connected to the microgrid by giving a priority value to each BEV. The simulation results show the coordinated operation of the central and local controllers to regulate the power outputs of the sources was effective to manage reserves and achieve frequency regulation. 10 30 2019 652 663 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8853.109119 https://www.ijeat.org/portfolio-item/f8853088619/ Department of Software Engineering,Addis Ababa Science and Technology University,Addis Ababa, Ethiopia Mesfin Fekadu Dr. Sudhir K. Department of Software Engineering,Addis Ababa Science and Technology University,Addis Ababa, Ethiopia Befekadu Belete Department of Software Engineering,Addis Ababa Science and Technology University,Addis Ababa, Ethiopia White pea bean is a very important crop where its circulation in the market has to conform to the rules of quality inspection. Currently, white pea bean sample quality inspection is performed manually by human experts through visual evaluation and the constituents classified into foreign matter, rotten and diseased, healthy, broken, discolored, shriveled and pest damaged kernels. However, visual evaluation requires significant amount of time, trained and experienced people. Besides, it is affected by bias and inconsistencies associated with human nature. Such approach will not be satisfactory for large scale inspection and grading unless fully automated. A total of 24 features (14 color, 8 shape and 2 size) have been identified to model white pea bean sample constituents. For classification of White pea bean samples, a feedforward artificial neural network classifier with backpropagation learning algorithm, 24 input and 7 output nodes, corresponding to the number of features and classes respectively has been designed. The network is trained and its performance is compared against other classifiers using empirically. For the purpose of training the classifier, a total of 602 kernels and foreign matters have been collected from Ethiopian Grain Trade Enterprise. The training data is randomly apportioned into training (70%) and testing (30%). The classifier achieved an overall classification accuracy of 96.8%. The success rates for detecting foreign, rotten and diseased, healthy, broken, discolored, shriveled and pest damaged kernels are 94.9%, 96.5%, 96.3%, 97%, 97.9%, 97%, and 97.6%, respectively. 10 30 2019 664 670 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8880.109119 https://www.ijeat.org/portfolio-item/f8880088619/ Department of ECE, CMR Institute of Technology, JNTUH, Hyderabad, T.S, India M. Venkata Ramanaiah G. Anjaneyulu Department of ECE, CMR Institute of Technology, JNTUH, Hyderabad, T.S, India. Sudhakar Alluri Department of ECE, CMR Institute of Technology, JNTUH, Hyderabad, T.S, India. In this paper one novel double counter proposed which is quick when contrasted with another normal's parallel counters. First, we are designing binary counter using solely full adders, and after with new symmetric stacking method. We are evaluating these two techniques and displaying how the symmetric stacking method is decreasing the x-or gate delays in the essential route of the binary counter. This kind of our proposed counter is very useful in the existing counter based totally Wallace tree multiplier design. With this new symmetry stacking counter we are lowering delay and increasing the performance of multipliers in VLSI circuits. We are designing and simulating our proposed quick binary counter using Xilinx ISE layout suite14.7. 10 30 2019 671 677 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8952.109119 https://www.ijeat.org/portfolio-item/f8952088619/ M.E, Power Electronics and Industrial Drives, Sathyabama University, Tamil Nadu. P. Shunmugakani D. Kirubakaran Ph.D from Anna University. Quasi ZSI are used for induction motors operating at low input voltage. This work deals with comparison of FLC & PI controlled current fed quasi ZSI fed IMdrive systems. Open loop and closed loop systems are simulated by considering step change in load. The results of open loop and closed loop systems are compared. The objective of this work is to improve the dynamic response of CFQZSI using FLC. The time responses of PI and FLC controlled closed loop systems are also compared. Fuzzy logic controlled system is proposed to improve the dynamic response of CFQZSI fed induction drive system. Design and simulation results are presented to demonstrate the new features. FLC is observed to provide better control the another controllers and it also has improved damping characteristics. 10 30 2019 678 683 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F8979.109119 https://www.ijeat.org/portfolio-item/f8979088619/ Electronics and Communication Engineering Bankura Unnayani Institute of Engineering West Bengal Mrinmoy Sarkar Asok Kumar Dean of Students welfareVidyasagar University Midnapur, West Bengal Prof Bansibadan Maji ProfessorECE DepartmentNIT Durgapur, West Bengal In high-speed wireless applications, because of the high-speed compatibility of the OFDM, it is a significant signal processing approach. In general, an efficient spectral multi-carrier modulation strategy is named OFDM, which gets impact via the issues of high PAPR. Because of the limited BW availability, the demand for high-speed applications is increasing. Due to the high data requirement, the various subcarriers are increased in OFDM, hence it made the difficult with PAPR (peak-to-average power ratio). To achieve better results by reducing the PAPR is the foremost problem on OFDM. In this paper, a hybrid optimized PTS is used to decrease the PAPR and the data will be encrypted by the DFT based chaotic sequences. A new Hybrid Whale Optimization and Moth Flame Optimization (HWOMFO) is introduced in this paper. It will generate a weighting factor for the PTS. PTS is the foremost strategy in OFDM for reducing the PAPR with low distortion. The minimum performance on computational complexity and PAPR achieved by this paper. The new combination of optimization approaches provides efficient best combination of phase rotational factors. The new hybrid optimization gives fast convergence quality and low complex and also this combination provides better than others. The proposed scheme is executed in MATLAB simulation and performance will be evaluated using parameters such as BER regards to SNR, complementary cumulative distribution function (CCDF) of PAPR and the outputs are associated depends on computation time. However, the experimental results show that compared with existing approaches, our proposed strategy gives better PAPR reduction with respect to SNR. 10 30 2019 684 691 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9036.109119 https://www.ijeat.org/portfolio-item/f9036088619/ Applied Mathematics, Pillai College of Engineering, Navi Mumbai, India. Kamini K. Chaudhari* Chandrshekhar S. Sutar Mathematicst, PSGVPM‟s A.S.C. College, Shahada, Maharashtra, India. In the present work, a semi-analytical solution is presented for the thermoelastic response of a finite plate of rectangular geometry considering hyperbolic heat conduction model. The solution of thermoelastic displacement, thermal stresses and temperature are obtained using differential transform method under hyperbolic, non-Fourier heat conduction theory. For special case, thermal stresses and displacement functions are determined numerically and plotted graphically to analyze the effect of the thermal relaxation time. 10 30 2019 692 699 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9047.109119 https://www.ijeat.org/portfolio-item/f9047088619/ Department of ECE, Sethu Institute of Technology, Kariapatti-630615, Virudhunagar, Tamilnadu A.Sabah Afroze M. Parisa Beham Department of ECE, Sethu Institute of Technology, Kariapatti-630615, Virudhunagar, Tamilnadu R. S.M. Seeni Mohamed Aliar Maraikkayar Tamilselvi Department of ECE, Sethu Institute of Technology, Kariapatti-630615, Virudhunagar, Tamilnadu, K. Rajakumar Department of CSE, Sethu Institute of Technology, Kariapatti-630615, Virudhunagar, Tamilnadu The detection of cotton leaf disease is a very important factor to prevent serious outbreak. Most cotton diseases are caused by fungi, bacteria, and insects. A new method is proposed for careful detection of diseases and timely handling to prevent the crops from heavy losses. A disease due to bacteria, insects and fungus occurs in the cotton leaves in the range of about 80-95%. In the proposed work, first the group of infected leaves and normal leaves are collected and the image preprocessing is done using Adaptive histogram equalization for enhancing the contrast. In feature extraction phase, texture and gradient feature are extracted using Local Binary Pattern (LBP), Histogram of Oriented Gradient (HOG) and Differential of Gaussian (DOG). K- Nearest neighbor classifier is applied to classify the leaf image as a unaffected or an affected leaf. A cotton leaf database is internally created to evaluate the efficacy of our algorithm. The validate results show that the proposed method achieved higher classification accuracy in lower computational time. 10 30 2019 700 703 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9083.109119 https://www.ijeat.org/portfolio-item/f9083088619/ Department of Mathematics, Government College for Girls Sector 14, Gurugram-122001, India. Sudesh Kumari* Renu Chugh Department of Mathematics, Maharshi Dayanand University, Rohtak-124001, India. Ashish Nandal Department of Mathematics, Pt. NRS Government College, Rohtak-124001, India. The logistic map occupies a renowned place in the dynamics of chaos theory and in diverse areas of science. Picard orbit and Superior orbit (Mann orbit) have been used to control this discrete chaotic dynamical system. In this article, we further extend the analytical study of logistic map using a four step feedback procedure (SP orbit). The dynamical properties such as fixed point, range of convergence and stability, periodicity and chaos of the logistic map have been investigated. These properties are illustrated experimentally by adopting dynamical techniques like fixed point analysis and bifurcation plot. Using this approach, one can easily control the chaotic system and make the system stable for higher values of population growth parameter r by selecting the control parameters carefully. 10 30 2019 704 707 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9166.109119 https://www.ijeat.org/portfolio-item/f9166088619/ Research scholar, Manipal University, Jaipur, Rajasthan Priyanka Dahiya Devesh Kumar Srivastva Professor with the department of School of Computing & Information Technology,Manipal University Jaipur, Rajasthan, India. Nowadays, the internet and network service user’s counts are increasing and the data generation speed also very high. Then again, we see greater security dangers on the internet, enterprise network, websites and the network. Anomaly has been known as one of the effective cyber threats over the internet which increasing exponentially and thus overcomes the commonly used approaches for anomaly detection and classification. Anomaly detection is used in big data analytics to recognize the unexpected behaviour. The most commonly used characteristics in network environment are size and dimensionality, which are big datasets and also impose problems in recognizing useful patterns, For example, to identify the network traffic anomalies from the large datasets. Due to the enormous increase of computer network based facilities it is a challenge to perform fast and efficient anomaly detection. The anomaly recognition in big data sets is more useful to discover fraud and abnormal action. Here, we mainly focus on the problems regarding anomaly detection, so we introduce a novel machine learning based anomaly detection technique. Machine learning approach is used to enhance the anomaly detection speed which is very much useful to detect the anomaly from the large datasets. We evaluate the proposed framework by performing experiments with larger data sets and compare to several existing techniques such as fuzzy, SVM (Support Vector Machine) and PSO (Particle swarm optimization). It has shown 98% percentage of accuracy and the false rate of 0.002 % on proposed classifier. The experimental results illuminate that better performance than existing anomaly detection techniques in big data environment. 10 30 2019 708 716 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9178.109119 https://www.ijeat.org/portfolio-item/f9178088619/ Ogarev Mordovia State University, Saransk, The Republic of Mordovia. A. P. Velmatov* O. V. Kostin Ogarev Mordovia State University, Saransk, The Republic of Mordovia, Russia T. N. Tishkina Ogarev Mordovia State University, Saransk, The Republic of Mordoviaю N. N. Neyaskin Ogarev Mordovia State University, Saransk, The Republic of Mordovia, Russia V. I. Erofeev Mordovia Institute retraining agribusiness, 33, Pionerskaya St., Yalga r.p., Saransk, The Republic of Mordovia, 430904, Russia N. V. Dugushkin JSC Mordoviyagosplem, The Republic of Mordovia, Russia In crossbred cows, three exterior and body composition types are distinguished: dense shallow, dense medium, and dense broad. Cows of broad type were superior to their peers of shallow type in height at the withers by 3.98 cm, by chest depth by 3.33 cm, by chest width by 8.25 cm, by chest girth by 5.5 cm, and by the slope body length by 5.37 cm. Cows of the medium type take an intermediate position. The share of the cows of the broad type is 67.5 %, they have a broader body, have an advantage in the indices of the breast width (5.5 – 9.2 %, P ≤ 0.001), and pelvic-thoracic width (7.2 – 13.1 %, P ≤ 0.001), but are inferior in the index of leg length (0.6 – 0.9 %). During the first lactation, heifers of shallow type gave 5,353 kg of milk, which was more by 500 – 539 kg than from heifers of the medium and broad types (P ≥ 0.99). In terms of the live weight, the calves obtained from the mothers of the broad type are superior to their peers at birth by 1.6 – 2.5 kg; at the age of three months, the difference between the groups of animals reached 8.0 – 13.0 kg (P ≤ 0.01, P ≤ 0.001); at the age of six months —15.0 – 25.0 kg (P ≤ 0.001); at the age of nine-months — 17.0 – 28.0 kg (P ≤ 0.001); at the age of twelve months — 25.0 – 44.0 kg (P ≤ 0.001); at the age of fifteen months — 25.0 – 46.0 kg (P ≤ 0.001); and at the age of eighteen months — 30.0 – 52.0 kg (P ≤ 0.001). By the weight of hot carcass, calves of the broad type were superior to their peers of the shallow type by 38.9 kg (P ≤ 0.01), and to those of the medium type — by 23 kg (P ≤ 0.05). The yield of boneless meat per 1 kg of bones in the calves of the shallow type was 3.87 kg, of the medium type — 4.10 kg, and of the broad type — 4.22 kg (P ≤ 0.05). The coefficient of feed protein and energy conversion to the dietary protein in the edible part of the carcass was higher in the calves of the broad type, which was due to the more intensive accumulation of muscle and adipose tissues in their organisms. 10 30 2019 717 722 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9255.109119 https://www.ijeat.org/portfolio-item/f9255088619/ Department of Computer Science and Engineering, Government College of Engineering and Leather Technology, Kolkata, India, Arnabi Mitra Saptarshi Banerjee Department of Computer Science and Engineering, Government College of Engineering and Leather Technology, Kolkata, India, Debayan Ganguly Department of Computer Science and Engineering, Government College of Engineering and Leather Technology, Kolkata, India, Ritajit Majumdar Advanced Computing & Microelectronics Unit, Indian Statistical Institute, Kolkata, India, Kingshuk Chatterjee Department of Computer Science and Engineering, Government College of Engineering andCeramic Technology, Kolkata, India Indian Premier League (IPL) is a tournament of twenty over cricket matches. Teams of this tournament are selected via an auction from a pool of players. Each team employs a think-tank to build the best possible team. Few studies have been performed to automate the process of team selection. However, those studies mostly concentrate either on the current form of the players, or their long term performance. In this paper, we have (i) selected traditional features as well as determined some derived features, which are generated from the traditional features, for batsmen and bowlers, (ii) formulated heuristics for clustering batsmen into openers, middle order batsmen and finishers, (iii) formulated heuristics for relative ranking of batsmen and bowlers considering the current performance as well as the experience of each player, and (iv) have proposed two greedy algorithms for team selection where the total credit point of the team and the number of players in each cluster is fixed. Our proposed ranking scheme and algorithm not only determines the best possible team, but can also determine the best alternate player if one of the target players is unavailable. 10 30 2019 723 728 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9290.109119 https://www.ijeat.org/portfolio-item/f9290088619/ Electrical & Electronics Engineering Department, Sharda University, Greater Noida, India. Premananda Pany* This paper presents a flexible power control strategy of a fuel cell (FC)- battery combined hybrid power source fed DC motor drive suitable to be used in electric vehicles which can be capable of working efficiently with an straightforward control method, operating the drive precisely in FC and hybrid modes during the entire drive operation. Although Fuel Cells are very widely accepted by the electric vehicle manufacturing industries, still the power control criterion can be improved to increase overall efficiency. The most appropriate Master Slave Control technique has been implemented to control the modes based on load power requirement and transient operations. The controller with the algorithm guarantees that total load is shared exactly between the two sources all through intense load and transients conditions. Such method inevitably facilitates the fuel cell to work in normal load region throughout transient and steady state by equally sharing the load current between the master and slave converters. The efficacy of the proposed scheme is verified through simulation which is carried out using MATLAB/Simulink software. Investigational tests are carried out using LabVIEW platform with PCI 6251 DAQ I/O interfacing card for viability of the system. FC can be considered as most vital electric power and component of an electric vehicle. 10 30 2019 729 736 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9291.109119 https://www.ijeat.org/portfolio-item/f9291088619/ Research Scholar, Department of Electrical and Engineering, S.V.University College Of Engineering, Tirupati, India, Tarasi Madhuranthaka* T. Gowri Manohar Professor, Department of Electrical & Electronics Engineering, S.V.Univeristy College of Engineering, Tirupati, India, This paper proposes an optimal placement and capacitance of UPFC for enhancing the dynamic stability of a power system using a new hybrid optimization technique. The hybrid optimization technique is the joined execution of both the moth flame optimization (MFO) and ant lion optimization (ALO) and hence it is named as Joined moth flame ant lion optimization (JMFALO) technique. Here, the MFO technique optimizes the maximum power loss line as the suitable location of the UPFC by considering the variation available in the bus system power flow parameters like voltage, angle, real power and reactive power. Dependent on the ALO technique the influenced location parameters and dynamic stability constraints are restored into secure limits utilizing the optimum capacity of the UPFC with least voltage deviation, loss of power, and reduced installation cost. Subsequently, to restore the dynamic stability constraints at a secure limit the optimized UPFC capacity is utilized. The dynamic stability constraint of the system is power balance constraint, active and reactive power loss, and UPFC installation cost and bus voltage constraints. The proposed technique is implemented in MATLAB/Simulink working platform. The performance of the proposed technique is assessed by utilizing the comparison analysis with the existing techniques. 10 30 2019 737 746 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9294.109119 https://www.ijeat.org/portfolio-item/f9294088619/ Research Scholar, Civil Engineering Department, College of Engineering, Pune, India. Vijay R. Wairagade* Dr. Ishwar P. Sonar Associate Professor, Civil Engineering Department, College of Engineering, Pune, India. Bamboo reinforced concrete is expected to be an alternative to steel reinforced concrete as a building material. Steel, when used for construction activities, is energy intensive and causes pollution. In this context, the use of bamboo, which is a fast growing, affordable and ecologically friendly solution; especially in a tropical country like India, is being considered as a suitable material for structural applications. It is potentially superior to steel in terms of its weight to strength ratio. However, the bond strength is a major concern for the bamboo to be a reinforcement in structural composites. The goal of this paper is to investigate the bonding properties of a newly developed bamboo-reinforcement composite in concrete, through pull-out tests. Various coatings are applied to the bamboo to determine the different bonding behaviours between the concrete and newly developed BRC. To improve the bonding at interfacial of bamboo concrete composite; easily applicable, adoptable and economical technology have been developed. The results of this study demonstrate that the bamboo-reinforcement composite develops adequate bonding with the concrete matrix with the hope that the newly developed material could contribute, on a large scale, to sustainable development. 10 30 2019 747 752 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.F9323.109119 https://www.ijeat.org/portfolio-item/f9323088619/ Assistant Professor, Department of Production Engineering, Sri Sai Ram Engineering College, Chennai. V. Velmurugan U. Tamilarasan Professor, Department of Production Engineering, Sri Sai Ram Engineering College, Chennai. V.Linkesh kumar Student, Department of Production Engineering, Sri Sai Ram Engineering College, Chennai. Composites are being used as an effective alternate replacement of various traditional metals and alloys. They possess very high mechanical properties and high corrosion resistance. With high strength to weight ratio, the composites are widely used to withstand high stress. GFRP are the composites having Glass fibers as reinforcements and epoxy resin as matrix. With the addition of Al alloy powder to the epoxy matrix, an enhanced mechanical property is observed. The existing domestic LPG cylinders are made up of low carbon steel with suitable heat treatment. It is used to store the mixture of Butane and Propane under high pressure. However, the gross weight of the cylinder is very high which makes handling difficult. The aim of this paper is to replace the traditional LPG cylinders with GFRP- Al composite which is less dense than the traditional steel, however having significant mechanical properties that satisfy the safety standards. 10 30 2019 753 756 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A9426.109119 https://www.ijeat.org/portfolio-item/a9426109119/ Binus University, Indonesia. Nur Azmi Karim* Chyntia Ika Ratnapuri* Binus University, Indonesia Exchange rate fluctuations are caused by interactions between economic factors and non-economic factors. The purpose of this study is to see the effect of the fluctuations in the rupiah exchange rate on economic growth along with several macro variables in Indonesia. The analytical method used in this study is multiple regression methods, namely testing the hypothesis about the effect of rupiah exchange rate fluctuations (KURS), inflation (INF), Foreign Direct Investment (FDI), Indonesian bank certificate interest rate (SBI), and Money Supply (JUB ) to the Indonesian economy (GRDP). The data used in this study are secondary data taken from Bank Indonesia, the Central Bureau of Statistics, and the World Bank. The research method used is multiple linear regrelsi method using eviews application. The results of this study indicate the exchange rate, inflation and the money supply have a negative direction with economic growth while foreign investment (FDI) and interest rates on Bank Indonesia Certificates (SBI) have a positive and significant direction towards economic growth in Indonesia. 10 30 2019 757 761 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1364.109119 https://www.ijeat.org/portfolio-item/a1364109119/ Department of Mechanical Engineering, Visakha Institute of Engineering and Technology, Visakhapatnam, India. G. Siva karuna* P. Suresh Babu Department of Mechanical Engineering, Maha Veer Institute of Science and Technology, Hyderabad, India Hybrid AA2024 Metal Matrix composite find explicit application, so important factors like Hardness, lightweight is considered and hybrid composite was synthesized by stir casting route. In this investigation, the effects of age hardening on Hardness of AA2024 reinforced with industrial wastes is measured by using a Vickers hardness test and the influence of different process parameters are studied using Design Expert. A Response Surface Methodology is an effective technique used to observe the impact of age hardening parameters and their interconnection on surface hardness of the prepared hybrid AA2024 composite. A mathematical model was created to optimize the weight percentage of reinforcement and artificial ageing process parameters for maximum Hardness. Adequacy and lack of fit of the developed model were checked using the Analysis of variance Technique. Hardness is taken as the response and optimum parameters are obtained by using the quadratic model. Based on the results, it can be perceived that the weight percentage of Red mud, ageing temperature and ageing time has shown a notable effect on the response. For a specifically optimized parameter, the hardness is improved and it was observed that ageing temperature is the most influencing factor based on the RSM. The optimized parameters for the desired response are Ageing Temperature is 198.87ᵒC, Ageing time is 6.82884 hours, and Red mud wt % is 4.2865 respectively. A confirmation test is carried out with the optimized parameters experimentally and its error is less than the 5 % which shows good results with RSM. Surface morphological studies are carried for the optimized Age Hardened hybrid composite and it showed the uniform distribution of reinforcements in the matrix. Because of the increased hardness, these hybrid composite would perceive real time applications like Orthopaedic braces, aircraft structures and manufacturing crew machine products. 10 30 2019 762 770 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1367.109119 https://www.ijeat.org/portfolio-item/a1367109119/ computer science & engineering, Dr APJ Abdul Kalam Technical University, Lucknow, India. Arunima Mishra* Bipin Kumar Tripathi computer science & engineering, Rajkiya Engineering college , Bijnor, India. Sudhir Singh Soam computer science & engineering, Institute of Engineering and Technology, Lucknow, India. Protein Multiple sequence alignment (MSA) is a process, that helps in alignment of more than two protein sequences to establish an evolutionary relationship between the sequences. As part of Protein MSA, the biological sequences are aligned in a way to identify maximum similarities. Over time the sequencing technologies are becoming more sophisticated and hence the volume of biological data generated is increasing at an enormous rate. This increase in volume of data poses a challenge to the existing methods used to perform effective MSA as with the increase in data volume the computational complexities also increases and the speed to process decreases. The accuracy of MSA is another factor critically important as many bioinformatics inferences are dependent on the output of MSA. This paper elaborates on the existing state of the art methods of protein MSA and performs a comparison of four leading methods namely MAFFT, Clustal Omega, MUSCLE and ProbCons based on the speed and accuracy of these methods. BAliBASE version 3.0 (BAliBASE is a repository of manually refined multiple sequence alignments) has been used as a benchmark database and accuracy of alignment methods is computed through the two widely used criteria named Sum of pair score (SPscore) and total column score (TCscore). We also recorded the execution time for each method in order to compute the execution speed. 10 30 2019 771 776 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1369.109119 https://www.ijeat.org/portfolio-item/a1369109119/ Information Technology Dept., College of Computer, Qassim University, Buraidah, KSA. Dina M. Ibrahim Sadaf Ambreen Information Technology Dept., College of Computer, Qassim University, Buraidah, KSA. The basic goal of information security is, to protect the privacy, reliability, and availability of information on devices that manipulate and store the information. To protect this information, the fundamental step is user authentication. The most common method for authentication on devices is the personal identification number (PIN) method, which is vulnerable to shoulder surfing attack. Shoulder surfing attack used by attacker especially in the crowded public places. For shoulder surfing attack prevention several methods had been proposed. This paper proposed a GazeTouchCrossPIN authentication method that overcome the limitations found in the earlier work. we propose a multimodal authentication system that combines between the gaze gesture and touch PIN authentication systems. The results illustrate that the proposed GazeTouchCrossPIN method is more secure hence it decreases the shoulder surfing rate in both side attacks and iterative attacks. 10 30 2019 777 781 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1381.109119 https://www.ijeat.org/portfolio-item/a1381109119/ Electronics and Communication Department, MANIT, Bhopal, India. Abhishek Sharma Dr. Vijayshri Chaurasia Electronics and Communication Department, MANIT, Bhopal, India Medical image processing is very wide and most interesting area of research now days. It covers wide application in diagnosis of diseases and analysis of inner body structure. Medical image processing include the study of internal body structure like organs, tissues, etc., which produce better information and help to detect disease using the digitalized data of human organs. In last few decades, so many denoising techniques were proposed like DWT techniques, Maximum likelihood (ML) etc. But all these algorithms have some limitations to preserve edges and fine details. So there is need of compromise between de-noising quality and edge preservation to use images for real time application. The proposed advancement in Non-Local Means filtering with different distant function and analyze them for best results. NLM filter reduce noise without degrading important features like edges and fine details. The analysis is based on the quality and quantity base like MSE, PSNR and SSIM. 10 30 2019 782 786 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1387.109119 https://www.ijeat.org/portfolio-item/a1387109119/ Research Scholar, Department of Computer Science and Engineering, Shri Venkateshwara University, Gajraula, Amroha, Uttar Pradesh, India. V. Porkodi* Dr. S. Anbu Karuppusamy Professor, Department of Electronics and Communication Engineering, Excel Engineering College, Namakkal, Tamilnadu, India. In the field of medical diagnosis, early detection of COPD symptoms is difficult. The use of predictive tests leads to the treatment of COPD and also helps to identify signs of COPD early. Therefore, we present in this paper a feature extraction method for the structural representation of COPD images using the Gabor Filter. In addition, we train and evaluate COPD extracted function or category with SVM classification. The results show that the proposed method can be more accurate, more flexible, and more reliable. This approach is well adapted for early diagnosis of COPD. 10 30 2019 787 790 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijeat.org true 10.35940/ijeat.A1392.109119 https://www.ijeat.org/portfolio-item/a1392109119/