bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiobjective Electrical Power Dispatch of Thermal Units with Convex and Non Convex Fuel Cost Functions for 24 Hours Load Demands
Authors:   Pursuing Ph.D. in Electrical Engineering Department of the Punjab Engineering College, Chandigarh, India, Kaushal Rajanish Kumar , Thakur Tilak ,   Professor, Electrical Engineering Department of the Punjab Engineering College, Chandigarh, India
Published: March 2020

There are a host of difficult issues with scheduling, operation, and control of integrated power systems. The electricity sector is changing rapidly, and one of the most important concerns is deciding operational strategies to meet electricity demand. It is a greater challenge to satisfy customer demand for power at a minimum cost. The operating characteristics of all generators may be different. In general, operating cost is not proportionate to the performance of these generators. Therefore challenge for power utilities to balance the total load between generators. For a specific load condition on energy systems, Economic Dispatch(ED) seeks to reduce the fuel costs of power generation units. Moreover, energy utilities have also an important task to reduce gaseous emission. So the ED problem can be recognized as a complicated multi-objective optimization problem (MOOP) with two competing targets, the minimal cost of fuel and the minimum emissions effects. This paper presented an efficient method, hybrid of particle swarm optimization (PSO) and a learning-based optimization (TLBO) for combined environmental issues because of gaseous emission and economic dispatch (CEED) problems. The results were shown and verified by PSO and TLBO for standard 3 and 6-generator frameworks with combined issues of emission and economic dispatch taking into account line losses and prohibited zones (POZs) on hourly demand for 24 hours.
Predicting Student’s Academic Performance using Data Mining Techniques
Authors:   computer science, Gyan Ganga Institute of Technology and Sciences, Jabalpur, India, Agrawal Surbhi , Vishwakarma Santosh K. ,   computer science, Manipal University, Jaipur, India.
Published: March 2020

To meet the change in world in terms of digitalization and progress, the need and importance of education is known to everyone. The increasing awareness towards and digitization has given rise to increase in size of education field’s database. Such database contains information about students. The information includes students behavior, their family background, the facility they have, the society environment which surrounds them, their academic records etc. The increasing technology in data sciences can help utilize this huge education field database in a productive way by applying data mining on it. When the techniques of Data mining are applied on the database relating education records, then this process is called as education data mining. This process helps us understand the area and the students on whom the attention and the amendments are required. This increases the level of education system and also affects the success rate and understanding of the students in academics in positive direction. In this paper four different classification algorithms are used to predict grades of the students, by referring student’s previous academic records. Out of the four algorithms, the one which gave the most accurate prediction is considered as the final prediction. The performance accuracy of different algorithm is compared through accuracy performance percentage.
Optimizing Energy Efficiencies in Cloud Data Center Resources with Availability Constraints
Authors:   CCBD, CSE, PESU, Bangalore, India., Phalachandra H.L. , Sitaram Dinkar ,   CCBD, CSE, PESU, Bangalore, India.
Published: March 2020

Cloud infrastructure Resources hosted in Data Centers, support the effective execution of Cloud computing applications. Given the increased adoption of the Cloud Computing Applications and the Businesses getting to be Data-driven, there is a huge increase in the number of Data Centers and the Size and amount of resources hosted in these Data Centers. These Data Center resources consume a significant amount of energy and this continuous scaling of the resources is leading to increased power consumption and a large carbon footprint. Given our fragile eco-system, optimization of the Data Center resources for energy conservation and thus the carbon footprint is the primary area of our focus. Businesses also need to satisfy QoS guarantees on Availability to their customers. Optimization towards Energy efficiencies may compromise on the Availability and thus may warrant a trade-off, and a need for them to be considered together. Although there have been numerous studies towards Energy efficiencies, most of them have been focused on only energy. In this paper, we initially segregate Optimization activities towards the Data Center resources like Compute, Network, and Storage. We then study the different control parameters or approaches which will lead to meeting the objectives of Energy Efficiencies, Availability and Energy Efficiency constrained with Availability. Thus, this will support the selection of approaches for the optimization of energy while meeting the QoS Availability requirement.
A Longitudinal Ageing Analysis of Vocal Parameters of Singing Voice of Female Playback Singer
Authors:   Department of Electronics D. K. T. E’s Textile & Engineering Institute, Ichalkaranji, India., Loni Deepali Y , Subbaraman Shaila ,   Department of Electronics Walchand College of Engineering, Sangli, India.
Published: March 2020

Age-related changes to the vocal structure affect the singing ability of the singer. We present a longitudinal study of vocal ageing of a female professional playback singer having more than six decades of singing span (covering singer age from 19 to 80 years). The ageing analysis is performed on six vocal parameters like – fundamental frequency (F0), vibrato, formants and spectral features like spectral roll-off and centroid. Statistical variations in these vocal parameters over the entire singing span of the singer are discussed in the paper. Significant effects noted with the ageing voice were - decrease in F0, decreased vocal range, reduction in vibrato rate, increase in vibrato extent, decrease in F2 & F4 formants and rapid change in the spectral features. This investigation also studied the effect of ageing on singing voice quality through the measurement of singing power ratio (SPR). Increase in SPR measures was observed with ageing voice. The study of impact of vocal ageing with longitudinal data on singer identification (SID) is scare. The SID experimentation performed with 350 cappella songs covering entire singing span of the singer, showed a clear impact that change in acoustical parameters with ageing affected the performance of singer identification systems.
Regulation Models of Crossroad Based on Wireless Sensor Networks and Notions of the Fluid Mechanics
Authors:   Laboratory of Engineering Sciences and Energy. Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir Morocco, Mustapha Kabrane , Karimi Khaoula ,   Laboratory of Engineering Sciences and Energy. Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir Morocco, Krit Salah dine ,   Laboratory of Engineering Sciences and Energy. Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir Morocco, Lahoucine El maimouni ,   Laboratory of Engineering Sciences and Energy. Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Agadir Morocco
Published: March 2020

The permanent growth of the population in smart cities has increased the number of vehicles. Consequently the problem of traffic congestion has become one of the main problems to be solved by today's traffic control systems, especially at traffic intersections. In fact, the traditional method which avoids the congestion in a crossroads is the classic command (Timing) by means of traffic lights. However, the traffic light management modes are sometimes based on classic models which make them unsuitable for the treatment of different experienced situations in traffic (either dense or fluid traffic). Fortunately, thanks to the significant progress made, especially the use of New Information Technologies and Communications for example Wireless Sensor Network, for the regulation of traffic, are solutions become central in the field of urban traffic management. They have made it possible to propose more effective control mechanisms to reduce the effects of traffic congestion. In this article, we will present the continuation of our work [1], the objective is to offer to the users of the road a crossing time as long as possible, while preventing the car cap to propagate over a distance that is set between two wireless sensors, to do this, we can act on the setting of the traffic light to regulate traffic in intersections.
Multi Relational and Social Influence Model for Predicting Student Performance in Intelligent Tutoring Systems ITS
Authors:   Laboratoire de Recherche, Informatique Télécommunication (LARIT), Institut National Polytechnique Felix Houphouet Boigny (INP-HB), Yamoussoukro, Côte d'Ivoire., Assielou Kouamé Abel , Haba Cissé Théodore ,   Department of Training and Research of Electrical & Electronics Engineering, Institut National Polytechnique Felix Houphouet Boigny (INP-HB), Yamoussoukro, Côte d'Ivoire., Kadjo Tanon Lambert ,   Laboratoire De Recherche en Informatique Et Télécommunication (LARIT), Institut National Polytechnique Felix Houphouet Boigny (INP-HB), Yamoussoukro, Côte d'Ivoire., Yao Kouakou Daniel ,   Laboratory of studies and prevention in Psychoeducation (LEPPE-ENS), University Jean Lorougnon Guédé, Daloa, Côte d'Ivoire, Goore Bi Tra ,   Laboratoire de Recherche en Informatique et Télécommunication (LARIT), Institut National Polytechnique Felix Houphouet Boigny (INP-HB), Yamoussoukro, Côte d'Ivoire.
Published: March 2020

Recent studies have shown that Matrix Factorization (MF) method, deriving from recommendation systems, can predict student performance as part of Intelligent Tutoring Systems (ITS). In order to improve the accuracy of this method, we hypothesize that taking into account the mutual influence effect in the relations of student groups would be a major asset. This criterion, coupled with those of the different relationships between the students, the tasks and the skills, would thus be essential elements for a better performance prediction in order to make personalized recommendations in the ITS. This paper proposes an approach for Predicting Student Performance (PSP) that integrates not only friendship relationships such as workgroup relationships, but also mutual influence values into the Weighted Multi-Relational Matrix Factorization method. By applying the Root Mean Squared Error (RMSE) metric to our model, experimental results from KDD Challenge 2010 database show that this approach allows to refine student performance prediction accuracy.
Identification of Best Fit Learning Models Based on Calibration for Better Classification of Autism
Authors:   Department of ECE, DBIT, Bengaluru, India., S. Roopa B. , Prasad R. Manjunatha ,   Department of ECE, DSATM, Bengaluru, India.
Published: March 2020

This paper is intended to exhibit the novel approach to improve the efficiency of the supervised learning models towards the accuracy of the predictions made to classify the autism from that of the normal subject. The state of the art is about 60-75% of Autism classification accuracy. The early prediction of autism plays a vital role as the rise of autism is alarming. The invasive way to analyze the problem at the earliest would render much support to the Autism Spectrum Disorder (ASD) community. In this work, various supervised learning models are first tested on 1101 subjects with 530 ASD subjects and 571 Normal subjects. The Datasets worked are collected from Autism Brain Imaging Data Exchange (ABIDE) repository. The performance measure is calibrated in terms of Brier score which is an accuracy measure of the predictions in probabilistic way. After assessing in probabilistic way, the statistically emphasized models are then evaluated for the same set of data to validate the prediction model efficiency with their statistical measures made and hence developing the confidence of the model selection for better classification based on probability calibration (CAL). The performance evaluation of the model is tested with probability calibrated assessment and found that for given dataset the SVM and Logistic Regression provided better accuracy measure compared to other considered learning models. It is necessary to frame a hypothesis measure on the dataset before any model is deployed. This approach helps to identify the desired and validated supervised model for the given data samples.
Tensile Behaviour of Aluminium Oxide and Zirconium Dibromide Reinforced Aluminum Alloy 6063 Surface Composites
Authors:   Assistant Professor, Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore, TamilNadu, India., Raja R. , Jannet Sabitha ,   Assistant Professor, Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore, TamilNadu, India., Varughese Allen ,   Assistant Professor, Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore, TamilNadu, India, George Lijin ,   Assistant Professor, Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore, TamilNadu, India., Ratna Sumanth ,   Assistant Professor, Department of Mechanical, Karunya Institute of Technology and Sciences, Coimbatore, TamilNadu, India.
Published: March 2020

The present study aims to investigate the Aluminium oxide and Zirconium diboride particles reinforced aluminum surface composites fabricated using Friction Stir Processing (FSP). Al-6063 was used as base-metal and Aluminium oxide and Zirconium diboride were used as reinforcement media. Al 6063 is used for architectural fabrication; window and door frames, pipe and tubing, and aluminium furniture Tensile strength specimens were prepared as per ASTM –E8 Standard. Tensile strength were found using UTM. Then it is found that that the tensile strength of the composite decreases as the volume percentage of the particles added for the reinforcement increases in the composites.
Revisiting Requirement Engineering Techniques: Managerial Perspective
Authors:   Research Scholar, Jagannath University, Jaipur, Sharma Shreta , Pandey Santosh K. ,   Scientist 'D', Government of India, Ministry of Electronics & Information Technology New Delhi
Published: March 2020

In Requirement Engineering, Requirements Management (RM) is one of the significant phases that can control the success of a software project. It manages deal between dependencies and requirements, modifications to the approved requirements and connection between other documents as well as the requirements document formed during the process of requirement engineering. In the world of software development, it is estimated that changes to requirements and poor requirement management are one of the major causes for project overrun and quality issues in software development. The practice of requirements management methodologies, with the support of traceability and quantification, is renowned as a substantial ability in the software maintenance and development process, and as an essential aspect for the quality of the final software product. The present study is accompanied by an acute assessment of the current methods for managing and resolving software requirements. It also highlights the management concerns that arise in the said process . Result analysis rveal that there are still numerous issues, which require immediate attention of research community in order to develop a quality software.
Assessing Car Damage using Mask R CNN
Authors:   Student, Dept of CSE, Rajalakshmi Engineering College, Chennai, TN, India., P Sarath , M Soorya ,   Student, Dept of CSE, Rajalakshmi Engineering College, Chennai, TN, India, A Shaik Abdul Rahman ,   Student, Dept of CSE, Rajalakshmi Engineering College, Chennai, TN, India., Kumar S Suresh ,   Associate Professor, Dept of CSE, Rajalakshmi Engineering College, Chennai, TN, India., Devaki K ,   Professor in the Department of Computer Science and Engineering, Rajalakshmi Engineering College , Thandalam, Chennai, India.
Published: March 2020

Picture based vehicle protection handling is a significant region with enormous degree for mechanization. In this paper we consider the issue of vehicle harm characterization, where a portion of the classifications can be fine-granular. We investigate profound learning based procedures for this reason. At first, we attempt legitimately preparing a CNN. In any case, because of little arrangement of marked information, it doesn't function admirably. At that point, we investigate the impact of space explicit pre-preparing followed by tweaking. At last, we explore different avenues regarding move learning and outfit learning. Trial results show that move learning works superior to space explicit tweaking. We accomplish precision of 89.5% with blend of move and gathering learning.
Solar Drying System Integrated with Phase Change Material PCM
Authors:   Research Scholar, D Y Patil Institute of Technology and Associate Professor, Mechanical Engineering Department, Pimpri Chinchwad Education Trust’s Pimpri Chinchwad College of Engineering, Pune, India,, Salve S. P. , Fulambarkar A. M. ,   Principal, Pimpri Chinchwad Education Trust’s Pimpri Chinchwad College of Engineering, Pune, India,, Khune P. D. ,   PG Scholar, ME Heat Power, Mechanical Engineering Department, Pimpri Chinchwad Education Trust’s Pimpri Chinchwad College of Engineering, Pune, India,
Published: March 2020

The post-harvest losses for agricultural products are around 30%-40% [1]. Drying is a one of the necessary processes for the preservation of agricultural products. Agricultural products require hot air of temperature above 40 ºC for drying. Open sun drying takes more time for drying of products due to slower drying rates. Also, various factors hamper the quality of the dried product. Due to the moisture content in the products bacterial attack is possible. India being the tropical region has good solar radiation. It is advisable to use the solar dryer to avoid spoilage of quality of products [2]. In this work, the compact and portable forced convection solar dryer designed and developed for drying chilies with thermal energy storage. Solar dryer is having capacity of 15 kg and it consists of the flat plate collector based air heating system with thermal energy storage. Paraffin wax used as phase change material (PCM). The CFD simulations carried out for the solar dryer to study the temperature distribution over the surfaces of the flat plate collector and inside the drying chamber, velocity of air and phase change behavior of paraffin wax inside the trays. The energy stored in the paraffin wax and time required for charging and discharging of paraffin wax is found out. The time for which temperature in the drying chamber is maintained above 40 oC is also found out. Results of CFD simulations validated with the experimental results.
Social Network Analysis of Terrorist Networks
Authors:   Information Technology, G H Raisoni College of Engineering, Nagpur, India., Nagdive Ashlesha S. , Tugnayat Rajkishor ,   Principal, Shri Shankarprasad Agnihotri College of Engineering, Wardha, India., Peshkar Atharva ,   Information Technology, G.H. Raisoni College of Engineering, Nagpur, India.
Published: March 2020

Terrorist Activities worldwide has led to the development of sophisticated methodologies for analyzing terrorist groups and networks. Ongoing and past research has found that Social Network Analysis (SNA) is most effective method for predictive counter-terrorism. Social Network Analysis (SNA) is an approach towards analyzing the terrorist networks to better understand the underlying structure of a network and to detect key players within the network and their links throughout the network. It is also need of the hour to convert available raw data into valuable information for the purpose of global security. Comparative study among SNA tools testify their applicability and usefulness for data gathered through online and offline social sources. However it is advised to incorporate temporal analysis using data mining methods, to improve the capability of SNA tools to handle dynamic social media data. This paper examine various aspects of Social Network Analysis as applied to terrorism, taking empirical data, and open source data based studies into account. This work primarily focuses on different types of decentralized terrorist networks and nodes. The nodes can be classified as organizations, places or persons. We take help of varied centrality measures to identify key players in this network.
Performance of Interline Unified Power Quality Conditioner IUPQC With PI, Fuzzy and ANFIS Controllers
Authors:   Studying IV, B.Tech, EEE, Kallam Haranadhareddy Institute of Engineering & Technology, Guntur, A.P., India, Navya A , Rao A Panduranga ,   Assistant Professor in EEE department at Kallam Haranadhareddy Institute of Engineering & Technology, Guntur, A.P., India, Rao L Shanmukha ,   Professor & HOD of EEE at Kallam Haranadhareddy Institute of Engineering & Technology, Guntur, A.P., India
Published: March 2020

Several artificial intelligent control schemes are highly used in several applications, in that ANFIS controller has been greatly recognized due to enhanced performance over the classical PI and Fuzzy controllers. At present the multi-feeder power distribution system is deteriorated with continuity of supply and poor power quality standards. In this multi-feeder distribution system, it is a regular consumer related issue which is acquired due to malfunctioning of massive non-linear loads. These loads create the voltage or current imperfections on distribution networks which disrupts the power quality of distribution system. An efficient and reliable active compensation scheme is used for attaining enhanced power quality features at PCC of multi-feeder distribution system with effective control functions. The Multi-Feeder Unified Power Quality Compensator (MF-UPQC) is optimal choice for attaining enhanced power quality features and it is a combined shunt or series compensator driven by common DC-link. This paper recommends the Adaptive Neuro-Fuzzy Intelligent Controller (ANFIS) based prediction technique for generation of optimal switching states to enhance performance of proposed MF-UPQC to compensate all voltage-current PQ imperfections. The performance of proposed MF-UPQC is verified by classical PI, Fuzzy and proposed ANFIS control functions by using MATLAB/SIMULINK tool and results are conferred with proper comparisons.
Labor Productivity Inconsistency among Project Sites
Authors:   Student, Adani Institute of Infrastructure Engineering, Ahmedabad, India., Patel Prachi , Patel V. M. ,   Professor, Adani Institute of Infrastructure Engineering, Ahmedabad, India.
Published: March 2020

As per ministry of statistics and programmeimplementation (2018-2019), construction industry is contributing 7.81 % share in GDP of India. There is an estimated need of around 75 million workers in the building, construction and real estate sector by 2022 (KPMG, 2019).The construction industry has been essential part in the developed and developing countries(Durdyev et al. 2012). The Construction industry in India is expected to grow at 5.6% during 2016-20(Invest India, 2019). Construction is a labor-intensive industry(Chalise 2015). Construction industry is totally dependent on labor and equipment, so increasing labor productivity by using scientific methods is the need of today’s highly growing world. Productivity is usually well-defined as the ratio of outputs to inputs. Laborand equipment productivity are some of the highly influencing factors that affect the physical growth of eachconstruction project.Therefore, to increase the profit margin of construction industry,labor productivity is key factor. This paper presents the bottom-up approach for study of laborproductivity.
Spam Detection in Social Media Networking Sites using Ensemble Methodology with Cross Validation
Authors:   Research Scholar, Anucet, ANU, Guntur, AP, India., Reddy K Subba , Reddy E. Srinivasa ,   Dean, Anucet, ANU, Guntur, AP, India
Published: March 2020

Social media networking sites are more popular over Internet. The Internet users spend more amount of time on social media sites like Twitter, Facebook, Instagram and LinkedIn etc. The social media networking users share their ideas, opinions, information and make new friends. Social networking sites provide large amount of valuable information to the users. This large amount of information in social media attracts spammers to misuse information. These spammers create fake accounts and spread irrelevant information to the genuine users. The spam message information may be advertisements, malicious links to disturb the natural users. This spam data in social media is a very serious problem. Spam detection in social media networking sites is critical process. To extract spam messages in social media various spam detection methodologies are developed by researchers. In this paper we proposed an ensemble methodology for identification spam on Twitter social media network. In this methodology we used Decision tree induction algorithm, Naïve bayes algorithm and KNN algorithm to construct a model. As part of this approach, we compare the classification results of any two classification algorithms, if both classifiers predict the same result, then we finalize the class of tweet under investigation. If the predicted classes of both classification algorithms differ, then we use the prediction of third algorithm as the final class label of tweet. To measure the performance of our model we used precision, recall and F measure.
Effect of Pure and Binary Fluids on Thermal Performance of Closed Loop Pulsating Heat Pipe
Authors:   Asst. Prof. & Research Scholar, JNTUCEH, Department of Mechanical Engineering, GRIET, Hyderabad, Telangana, India., Suresh J. Venkata , Bhramara P. ,   Professor, Department of Mechanical Engineering, JNTU College of Engineering, Hyderabad, Telangana, India., Nagasri K. ,   M.Tech (Thermal Engineering) Student, Department of Mechanical Engineering, GRIET, Hyderabad, Telangana, India.
Published: March 2020

Pulsating heat pipe is the raising methodology of cooling systems in many areas. CLPHP is a passive mode of phase change heat transfer device having potential to transfer heat from source to sink in less span. Heat transfer performance of this method is improving day by day as giving less thermal resistance. Number of experimentations are conducting to increase the efficiency of pulsating heat pipes in many aspects i.e. varying lengths, working fluids, number of turns, different fill ratios, heat inputs and orientation. As taking part of these research a five turn closed loop pulsating heat pipe (of tube inner diameter 2mm, outer diameter 3mm; adiabatic section length 170mm, condensation section length is50mm, evaporation section length is 42mm) working with pure and binary fluids (water-acetone, water-ethanol) compared with water, Acetone, Ethanol with heat inputs 20w, 40w, 60w, 80w, and fill ratio 50%, also the orientations are horizontal and vertical. The analysis from the results obtained was the thermal resistance of all working fluids is drastically diminishing from 20w to 40w heat input and slowly from 40w to 80w.
An Efficient Scheme for Vein Detection using Accuvein Apparatus Based on Near Infrared with Broadcom Chip
Authors:   Department of CSE, GITAM School of Technology,Bengalure, India., S Sahana D , N Dayanand Lal. ,   Department of CSE, GITAM School of Technology,Bengalure, India.., J Vidya ,   Department of CSE, GITAM School of Technology, Bengalure, India., C Bhanujyothi H ,   Department of CSE, GITAM School of Technology, Bengalure, India.
Published: March 2020

Venipuncture has been considered as one of the main fitness analysis strategies. Even although venipuncture has been taken into consideration as one of the highest prioritized and commonly accompanied practised in hospitals is to carry out obtain the veinsfor small kids, elderly peoples , fat , anaemic, or darkish skin colored patients has been a difficult procedure for medical practitioners. To get the solution for this problem, many devices using infrared light have became today's trend. But those devices share a commonplace drawback, for visualizing deep veins or veins of a thicker part of subject like limb. This paper clarifies a vein-picturing device , Accuvein which uses Near infrared (NIR) light. The light inventory quickly extends straightforwardly to the chose selected part of the skin. The camera sensor has been used to come across infrared radiation to take the vein photos. With the addition of an image processing process, the first-class of vein shape obtained is more desirable showing it extra as it should be. The implemented device has met the requirements of a desired output image when limb areas kept under Accuvein device obtaining the efficient images. The visibility of veins for the purpose of Cannulation increased by using Accuvein device.
Real time Fully Automated Internal Layer Segmentation of Human Retina in Optical Coherence Tomography Images
Authors:   Department of Nuclear Energy Convergence, Kyungil University, Gyeongsan-si, Gyeongbuk, Republic of Korea., Han Youngmin , Ravichandran Naresh Kumar ,   School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 80 Daehak-ro, Bukgu, Daegu 41566, Republic of Korea., Kim Pilun ,   Institute of Biomedical Engineering Research, Kyungpook National University, 680, Gukchaebosang-ro, Jung-gu, Daegu 41944, Republic of Korea., Jeon Mansik ,   School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 80 Daehak-ro, Bukgu, Daegu 41566, Republic of Korea, Kim Jeehyun ,   School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 80 Daehak-ro, Bukgu, Daegu 41566, Republic of Korea.
Published: March 2020

In the field of ophthalmology, optical coherence tomography (OCT) has proven to be a powerful imaging technique when it comes to diagnosing various eye-related diseases. This research article introduces a real-time automatic retinal layer segmentation algorithm based on intensity variation in the OCT images. The built algorithm is capable of detecting internal retinal layers like the internal limiting membrane (ILM), the retinal pigment epithelium (RPE) and the retinal nerve fiber layer (RNFL) with micrometer level precision, the algorithm uses openMP for parallelized computation for real-time visualization of the segmented retinal layers. The total execution time of the algorithm was evaluated using various image sizes and compared with the OCT frame rate to demonstrate the efficiency of real-time segmentation.
Software Quality Assesment using COCOMO II Metrics with ABC and NN
Authors:   PhD Research Scholar, Department of Computer Science & Engineering, Maharishi Markandeshwar (Deemed To Be University) Mullana, Ambala , India., Malik Naveen , Goyal Sandip Kumar ,   Professor, Department of Computer Science & Engineering, Maharishi Markandeshwar (Deemed To Be University) Mullana, Ambala, India., Malik Vinisha ,   PhD Research Scholar, Department of Computer Science & Engineering, Maharishi Markandeshwar (Deemed To Be University) Mullana, Ambala , India.
Published: March 2020

Time, cost and quality predictions are the key aspects of any software development system. Loses that result due to wrong estimations may lead to irresistible damage. It is observed that a badly estimated project always results into a bad quality output as the efforts are put in the wrong direction. In the present study, author proposed ABC-COCOMO-II as a new model and tried to enhance the extent of accuracy in effort quality assessment through effort estimation. In the proposed model author combined the strengths of COCOMO-II (Constructive Cost Model) with the Artificial Bee Colony (ABC) and Neural Network (NN). In the present work, ABC algorithm is used to select the best solution, NN is used for the classification purpose to improve the quality estimation using COCOMO-II. The results are compared and evaluated with the pre-existing effort estimation models. The simulation results had shown that the proposed combination outperformed in terms of quality estimation with small variation of 5-10% in comparison to the actual effort, which further leads to betterment of the quality. More than 90% projects results into high quality output for the proposed algorithmic architecture.
Accelerating Anisotropic Cosmological Model Filled with Two Fluid and
Authors:   Department of Applied Mathematics, SIPNA College of Engineering and Technology, Amravati, India., Borikar S. M.
Published: March 2020

In this paper we have studied Kantowski-Sachs universe filled with perfect fluid and radiation with a cosmological constant. To get determinate solution, it is assumed that the scalar of expansion is proportional to shear scalar (    ) which leads to the relation between metric potentials n R AS The cosmological parameters of models are also discussed.
Seismic and Time History Performance of RCC Framed Buildings with and without Passive Energy Dissipators
Authors:   Field of Transportation and Structures, Visakhapatnam, India., Dasari Sai Gowtham , Rao K. Srinivasa ,   Professor, Department of Civil Engineering, Andhra University, India.
Published: March 2020

Base isolation is an effective way to protect large structures from earthquake damage. It is a costly approach, as the entire structure must be supported on elastomeric or sliding bearings. Viscous dampers distributed throughout an otherwise conventional structure can achieve the same result at a significantly lower cost. Dampers are used to resist lateral forces coming on the structure. Dampers are the energy dissipating devices which also resist displacement of Reinforced Concrete (RC) buildings during an earthquake. These dampers help the structure to reduce buckling of columns thereby increasing the stiffness of the structure. During earthquakes, multi-storeyed buildings get damaged and as a result, large deformation occurs. Dampers reduce vibration and deformation of structural elements during an earthquake. Retrofitting buildings with fluid viscous dampers (FVDs) can improve Interstorey drifts and floor accelerations. In the present study, an RC framed building is modelled and analysed under Southern Sumatra and Chile earthquakes to evaluate the performance of the structure and its elements with and without energy dissipators. For the study, a model (G+19) with and without energy dissipators is modelled in ETABS. The seismic force is applied based on the time history data of the models pertaining to Southern Sumatra and Chile Earthquake. Response Spectrum analysis has been carried out to find the lateral displacements, storey shear and Base shear for the model with and without dampers. The lateral displacement, storey drift, storey shear and Base shear are found to less for the model with Linear FVDs when compared to the model with Non-Linear FVDs and without FVDs.
25GHz 40GHz Circularly Phase Array Microstrip Patch Antenna for Millimeter Wave Communication
Authors:   Department of Electronics and Communication NERIST, Nirjuli-791109, Arunachal Pradesh, India., Shah Md. Farid , Singh Aheibam Dinamani ,   Department of Electronics and Communication, NERIST, Nirjuli-791109, Arunachal Pradesh, India.
Published: March 2020

Millimeter wave technology will enable to provide high data rate. It is also expected to provide continuous good quality, low latency video. For high-resolution video, wireless communication will require huge bandwidth. The present 4G spectrum will be unable to meet the demand of each mobile user. To solve bandwidth shortage millimeter wave technology is consider. In this paper present a circularly phase array designed. It is operating in the 25GHz to 40GHz. To enhance bandwidth the array used edge couple parasitic patch arrangement which provides dual resonance. The array is designed in circular phase array with the rotational feeding line. The designed used polyflon CuFlon(tm) low dielectric constant, Ɛr = 2.1 and tangential loss, δ = 0.00045 with height h = 1.6mm. The designed achieved 8.41dB gain. The array achieved good return loss, S11 bandwidth i.e. -11.83dB ≤ S11 ≤ -37.8dB (25GHz to 40GHz) and voltage standing wave ratio, VSWR ≤ 1.7 (25GHz to 40GHz).
Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy Based Image Processing Techniques
Authors:   Department of Electronics and Instrumentation, Bharathiar University, Coimbatore, India., Durai L. Jeganson , Vijayakumar J. ,   Department of Electronics and Instrumentation, Bharathiar University, Coimbatore, India.
Published: March 2020

Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.
Experimental Analysis on Performance and Emission Characteristics of C.I. Engine Fueled by Neem Oil Biodiesel with Additive
Authors:   Department of Mechanical Engineering, B V C Engineering College, Odalarevu, A.P., India., Prasad A. S. V. , Rao G. Venkateswara ,   Department of Mechanical Engineering, B V C Engineering College, Odalarevu, A.P., India., Krishna A. Rama ,   Department of Mechanical Engineering, B V C Engineering College, Odalarevu, A.P., India., Srikanth B. ,   Department of Mechanical Engineering, B V C Engineering College, Odalarevu, A.P., India.
Published: March 2020

In this present work, experiments were conducted on a VCR Diesel engine with diesel, Neem oil biodiesel and Di-ethyl ether mixed with neem oil biodiesel. The performance and emission characteristics were evaluated and compared. The study shown that the Brake thermal efficiency increased and the brake specific fuel consumption reduced with B10 blend of neem oil biodiesel compared to diesel. The emissions of CO, CO2 were reduced but HC and smoke were increased with the use of biodiesel than diesel. The addition of Diethyl Ether (DEE) further improved the performance and decreased the emissions of CO and CO2 of the engine at B20DEE20 blend compared to other blends of biodiesel and diesel.
ANN and SVM algorithm in Divorce Predictor
Authors:   Master of Computer Science - Postgraduate Programs STMIK Nusa Mandiri, Indonesia,, Hafidz Noor , Sfenrianto  ,   Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jakarta, Pribadi Yogie ,   Master of Computer Science - Postgraduate Programs STMIK Nusa Mandiri, Indonesia,, Fitri Evita ,   Master of Computer Science - Postgraduate Programs STMIK Nusa Mandiri, Indonesia,, Ratino  ,   Master of Computer Science - Postgraduate Programs STMIK Nusa Mandiri, Indonesia,
Published: March 2020

Classification is a technique used to predict group membership or label for data samples (instances). In order to predict the result, the classification algorithm processes the training set, which contains a set of attributes and corresponding results. One of these classification technique is implemented in order to predict divorce in Turkey. This research is executed by Yöntem, M. K. et al. in 2019. In this , M. K. concluded that the ANN algorithm combined with correlation-based feature selection has the best performance with an accuracy of 98.82% and Kappa value of 0.9765. Nevertheless, unlike any previous research, ANN is not considered very good in terms of the required training time. In several previous studies, it was also concluded that other classification algorithms, such as SVM, have better prediction accuracy compared to ANN. In this study, prediction accuracy and Kappa value between ANN and SVM algorithms are compared using the same dataset and feature selection as the research done by Yöntem, M. K., to ensure a fair comparison between both of the algorithms. The result obtained from comparing both algorithms is that the SVM algorithm performs better than ANN with an accuracy of 99.8235 and a Kappa value of 0.9964. The training time required by SVM is also better than the ANN training time.
Voice Based E Mail System using Artficial Intelligence
Authors:   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Khan Rijwan , Sharma Pawan Kumar ,   Department of Applied Science, Krishna Engineering College, Ghaziabad, Affiliated to AKTU Lucknow, India., Raj Sumit ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Verma Sushil Kr. ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Katiyar Sparsh ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India.
Published: March 2020

One of the mostly used forms of communication among the people is Email. Lot of confidential and urgent information is exchanged over emails in today’s time. There are about 253 million visually impaired people worldwide. These visually impaired people are facing a problem of communication. Since, technology is growing day by day these types to visually challenged people feel that they are more challenged. So authors proposed a Voice based Email System using AI that will make email system very easily accessible to visually challenged people and also help society. Accessibility is the most important feature that is considered while developing this system. Any system is called accessible only if both able and disable people can use it easily.
Enhancement of Power Transfer Capacity and Transmission Efficiency using SSSC
Authors:   Department of Electrical Engineering, UIE, Chandigarh University, Gharuan, Punjab, India, Bisht Kamal , Kumar Deepak ,   Department of Electrical and Electronics Engineering, UIET, Panjab University Chandigarh, Chandigarh, India., Bedi Kuldeep Singh ,   Department of Electrical and Electronics Engineering, UIET, Panjab University Chandigarh, Chandigarh, India.
Published: March 2020

The power demand is increasing globally at a higher rate than the possible increase in the generation. The increased demand requierements put additional burdon on the existing transmission lines and sometimes burdoned beyond their power carrying capacities. Increase in power demand either due modernization of power system, industrialization leads to congestion problem and abruptly affects the stable and reliable operation of power system. Redesign and reconstruction of power system according to load requirements everytime is not an economical and viable solution. Other possible solution to the problem is use of FACTS devices. The use of FACTS devices the problems like increase in load demand, high losses in transmission line and dip in receiving end voltage can be eliminated or easily tackeled. In this paper, Static Synchronous Series Compensator as one of FACTS device has been used for improvement of voltage profile of different buses and power carrying capacity of the transmission lines. The main objective of this paper is to make a comparative investigation between compensated and uncompensated power system in terms of enhancement of power carrying capacity with low losses and improvement of voltage profiles of buses in the transmission network. The performance of uncompensated power system has been compared with compensated power system with the use of MATLAB/ Simulink software.
Distribution of Data Handling in Cloud Asset
Authors:   Assistant Professor, Department of CSE, GITAM School of Technology- Bengaluru Campus, Bangalore, India, Tukkoji Chetana , Shyamala Boosi ,   Assistant Professor, Department of CSE, GITAM School of Technology- Bengaluru Campus, Bangalore, India., Nadhan Archana S. ,   Assistant Professor, Department of CSE, GITAM School of Technology- Bengaluru Campus, Bangalore, India., K. Rashmi ,   Assistant Professor, Department of CSE, GITAM School of Technology- Bengaluru Campus, Bangalore, India.
Published: March 2020

In Cloud computing, task scheduling is one of the technique of specifying and assigning job to assets that finish the job. It may be virtual computing elements like threads & processors or data flows, which is planned on hardware resources like processors. The planning operation is performed by a scheduler. Schedulers are enabled various customers to properly communicate system funds or attain excellent service quality. Scheduling is essential for computing and the notion of planning allows multitasking computers with single CPU as inner portion of a computer system's execution model. Preference will be provided based on the requirements and goals of the user. Multiple computing parts comprise of many parallel applications while duties of execution are relied on other duties. We have studied few related articles in this paper, which is presented in the following section.
Detection of Vulnerability Injection Point in Software Development Lifecycle for Effective Countermeasures
Authors:   Computer Science and Engineering, Jain University, Bengaluru, India, N. Thejasvi , R. Shubhamangala B. ,   Professor, Research Head, Bengaluru, India.
Published: March 2020

This paper takes a deeper look at data breach, its causes and the linked vulnerability aspects in the application development lifecycle. Further, the Vulnerabilities are mapped to the software development life cycle (SDLC) involving requirement elicitation, design, development, testing and deployment phases. Being aware of exact SDLC life cycle where the vulnerabilities are injected, suitable security practices (countermeasures) can be adopted in delivery methodology, which can control the eventual data breaches and safeguard the application from security perspective. Our research focuses on Evolution of Vulnerabilities through the application development life cycle, and we have leveraged “Inverted Tree Structure/Attack Tree” and “Affinity Principles” to map the vulnerabilities to right Software Development Life Cycle.
Determining the Scope of Recovery from Physically Damaged Micro SD Card
Authors:   Department of Digital and Cyber Forensic, Government Institute of Forensic Science, Aurangabad (MS). India., Landepatil Amar B. , Bawiskar Shobha K. ,   Department of Digital and Cyber Forensic, Government Institute of Forensic Science, Aurangabad (MS). India.
Published: March 2020

Today’s use of secondary devices like cloud storage, Hard Disk, Pen Drive, SD, CDs, DVDs is constantly growing. Data might be deleted , loss or device is formatted accidentally or intentionally by various means. It’s a myth that “once secondary storage devices are damaged then there is no access to data too”. This article gives the detail investigation that from damaged devices too data can be recovered.
绿色人力资源管理探析
Authors: 丁 敏
Published: March 2020

绿色人力资源管理是人力资源管理的新模式，它通过企业人力资源管理职能的绿色化来影响企业的环境绩效，促进社会绿色经济的可持续发展。