bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of bio-Oil produced by Microwave Pyrolysis of Karanja Seed.
Authors:   Department of Mechanical Engineering, Pondicherry Engineering College, Pondicherry, India., Mathiarasu A. , Pugazhvadivu Dr. M. ,   Department of Mechanical Engineering, Pondicherry Engineering College, Pondicherry, India.
Published: January 2020

Pyrolysis is one technique that produces three products in a short span of time in which both conventional and non-conventional method of heating (microwave irradiation) can be done. Karanja seed powder is taken as the feedstock in this microwave pyrolysis experiment. Proximate and Elemental analysis of karanja seed powder resulting volatile content of about 84.89% and moisture content of 10.11% whereas the Carbon of 52.08%, Hydrogen of 8.26%, Sulphur of 0.21%, Nitrogen of 4.02% and oxygen of 35.04%. Microwave pyrolysis for karanja seed was conducted for two power inputs of 700W and 800W in which bio-oil yield is high of 47% at 700W and non-condensable gases of 39% at 800W. The FT-IR results resembles the presence of aliphatic compounds. The TGA analysis was also taken for the produced bio-oil. The rheological study was made to determine the dynamic viscosity of the produced bio-oil at 50 rpm in room temperature which is averaged to 52 cP. The flash point of 90°C and fire point of 94°C was also determined for the produced bio-oil.
Research of the Ore Dressability of the Khandiza Polymetallic Ore Deposit
Authors:   Senior Teacher, Department of Mining engineering, Tashkent State Technical University, Tashkent, Uzbekistan., Islamovna Aminjanova Sevara , Karimovna Umarova Inoyat ,   Candidate of Technical Sciences, Docent, Department of Mining engineering, Tashkent State Technical University, Tashkent, Uzbekistan., Qahorovna Salijanova Gulnora ,   Docent. Department of Mining engineering, Tashkent State Technical University, Tashkent, Uzbekistan., Suyarovich Qalandarov Qobil ,   Candidate of Technical Sciences, Docent, Department of Mining engineering, Tashkent State Technical University, Tashkent, Uzbekistan., Bahtiyorovich Mahmarejabov Dilmurod ,   Teacher. Department of Mining engineering, Tashkent State Technical University, Tashkent, Uzbekistan.
Published: January 2020

The article discusses the results of technological studies on the concentration of polymetallic ore of the Chinarsay deposit. The results of studies of the material composition and flotation concentration options for technological samples of ore from the Chinarsay deposit are presented. The results of studying the material composition of ore based on spectral, chemical and rational analysis are presented. It has been established that industrially valuable ore components are lead, zinc and copper, the contents of which are given. It was shown that ore minerals are in close intergrowth with non-metallic ones - quartz, sericite, chlorite, carbonate, etc. It is noted that the studies were carried out in two directions: collective flotation of all ore minerals with further selection of the collective concentrate into lead, zinc, copper and pyrite concentrates and direct collective selective flotation to produce sequentially lead-copper, zinc and pyrite concentrates. As a result of enrichment, lead, zinc and copper concentrates are selected that meet the production requirements.
Clustering of Municipal Self-Government Bodies on the Basis of Statistical Indicators
Authors:   Senior Lecturer, Department of Information Technology, Urgench Branch of Tashkent University of Information Technologies, Uzbekistan., Jumanazarovich Rakhimboev Khikmat , Agzamovich Ismailov Mirkhalil ,   Chief Researcher, Research and Innovation Center information and communication technologies, Tashkent University of information technologies, Uzbekistan., Khudayberganovich Khusinov Khamid ,   Lecturer, Urgench branch of Tashkent University of Information Technologyies, Uzbekistan.
Published: January 2020

The application of cluster analysis by the method of k – means local self-government bodies of the Republic of Uzbekistan is examined from the standpoint of the state of self-government bodies, as well as the level and quality of life of the population. Based on statistical information, the paper presents the results of the division of regions according to key indicators of self-government bodies. In the course of the study, five clusters were identified: with a low, below average, average, above average, and a high state of development of self-government. To characterize the self-governing bodies of the Khorezm region, statistics were used on self-governing bodies (population) and some system of socio-economic indicators of the level and quality of life (average per capita total income of the population, average per capita real income of the population, number of crimes and unemployment, facilities and municipal facilities , living area per inhabitant, etc.).
Application of Foam Stopping for Mitigation of Spontaneous Heating In Underground Coal Mines
Authors:   Pursuing Ph.D. Mining Engineering in N.I.T, Rourkela., Mahananda Mr. Alok Ranjan , Pal Dr. B. K. ,   Senior Professor in Mining Engineering at NIT, Rourkela
Published: January 2020

The problem of spontaneous heating is a major threat to safety and productivity in mines all over the world. In India, more than 80% of fires are caused due to Spontaneous Combustion. The applicability of inert gases is expensive, time-consuming and is a very tedious process. Hence the application of advanced technologies becomes essential to be introduced in mines. In this context, Central Mine Planning and Design Institute (CMPDI), Ranchi, India carried out an R&D project entitled “Construction of quick setting stopping in case of fire in an underground mine using expansion foam agent” under the funding from the Ministry of Coal, Government of India. Under this project, two Indian mines were selected in consultation with MCL for carrying out the proposed work in Orient Mine No.3 and Bundia Mine of MCL (Ib Valley AREA). Coals from both the mines have been collected and analysed in the laboratory. The proximate analysis and CPT/IPT results show that both the coals are moderately prone to spontaneous heating. Considering both intrinsic and extrinsic properties, two stoppings were constructed in the Hirakhand Bundia mines and four in orient mines. Periodic supervision along with the altering ingress of air from intake was been checked. After careful supervision of nearly 4 years, the stoppings proved to be strong enough to be leakage proof. This paper describes the application of foam technology as stopping to avoid air entry, thus preventing the occurrences of spontaneous heating/fire in a panel of Indian coal mines.
Development of Learning Tools Based on Problem Based Learning for Electrical Motorcycle Maintenance Course: Cognitive Ability
Authors:   Universitas Negeri Padang, Jln. Prof. Dr. Hamka Air Tawar, Padang, 25131, Indonesia., Sukardi  , Andeka  ,   Universitas Negeri Padang, Jln. Prof. Dr. Hamka Air Tawar, Padang, 25131, Indonesia., Wulansari Rizky Ema ,   Universitas Negeri Padang, Jln. Prof. Dr. Hamka Air Tawar, Padang, 25131, Indonesia., TzeKiong Tee ,   Universiti Tun Hussein Onn Malaysia, BatuPahat, Johor., Irfan Dedy ,   Universitas Negeri Padang, Jln. Prof. Dr. Hamka Air Tawar, Padang, 25131 Inonesia.
Published: January 2020

This study was designed to evaluate the effectiveness of learning tools based on Problem-Based Learning for the ElectricalMotorcycle Maintenance course in SMKs. This research applieda quantitative research approach and a quasi-experimental research design. The method consists of four stages namely: define, development, design and disseminate. The results of this research wereas follow: (1) An Instructional Design had been developed for motorcycle electrical System at Vocational High School. (2) The effectiveness was 86.26%. Based on the finding, it can be concluded that the tested program is effective to be used. On the other hand, results obtained from this research also proved that PBL-based Learning Devices is giving positive effectson improving student learning outcomes.
Current Apprises of Opinion Mining Methods
Authors:   Department of Computer Science, Kakatiya University, Warangal, Telangana, India., Manjula B. , Aqlan Ameen Abdullah ,   Department of Computer Science, Kakatiya University, Warangal, Telangana, India., Naik R. Lakshman ,   Dept. of IT, KU College of Engineering & Technology, Kakatiya University, Warangal, Telangana, India.
Published: January 2020

increasingly, the data is increasing day by day and storage capacity is expanding more and more, this allowing the field of SA to growing and developing faster in research and prospecting for different opinions and emotions to be combed and technically treated to be more accurate. In our present, data can be a wealth where major global companies and development, research and crime detection centers benefit from it. In this paper we focused on the current apprises of research in this field which contributed to various improvements in the field of sentiment analysis. We have tackles comprehensive overviews for different fields which related to the Sentiment Analysis (Transfer Learning (TL), Building Resource (BR), Emotion Detection (ED)) which have the popularity of researchers has gained in recent times and attracted them. We have the aim of this survey which is to give a clear and accurate picture about the techniques of analyzing emotions and related fields.
Utilization of Storm Water Management Model for Urban Flood Scenario
Authors:   B.Tech, Department of Civil Engineering Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India, Gisrish D. , Agarwal Sunny ,   Assistant Professor, Department of Civil Engineering Department, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India
Published: January 2020

Majors cities in India have witnessed huge floods from past few decades. Due to rapid population growth and improper urban planning the chances of creek, localised or flash urban floods have drastically increased. Climatic changes are also a key reason for heavy rainfall that increases the flood volume and depth in a catchment. Modelling of Storm water plays a key role in estimating flood runoff quantity and quality. To check these issues SWMM is used to simulate floods scenario in Urban areas. This hydrological study is carried out to simulate and understand the rainfall runoff characteristics of the study area by using SWMM. It is an effective tool used for simulating flash floods and runoff in urban areas. In this study catchments have been subdivided into 14 parts and modelled for year 2017 rainfall events of 1-hr interval. The present study area is evaluated by importing AutoCAD map of the area in SWMM. Further Rainfall Data is imported as time series in the model. The results depict that the Runoff for the Sub catchments of S1, S2, S3, S9, S13 blocks are maximum. The study states that no nodes are flooded and also no overflow sections. Thus, the selected study area storm network system has been well planned and has enough carrying capacity to carry the simulated rainfall for a prolonged duration.
Digital Forensics Tools
Authors:   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India., Kapoor Vedanta , Taneja Sanya ,   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India., Kumar Kakelli Anil ,   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
Published: January 2020

In this paper we will we reviewing the basic fundamentals of digital forensics and all go through the various types of forensics investigation teams available to us. We will also discuss about the different types of digital crimes that take place and the various tools present in order to counteract the crimes that are being committed. There will also be a comparative review among all the tools present based on various factors present giving the reader an abstract view about which tool to use for the best type of results.
An Exigent Device that aids to Educate the Attention Deficit Hyperactivity Disorder (ADHD) Children
Authors:   Assistant Professor, Computer Science and Engineering of Easwari Engineering College., Vasu Rathinapriya , UD Bhumikka ,   Pursuing their Bachelor of Engineering, Computer Science and Engineering, Easwari Engineering College., K Divya. ,   Pursuing, Bachelor of Engineering, Computer Science and Engineering, Easwari Engineering College.
Published: January 2020

ADHD called the Attention Deficit Hyperactivity Disorder is predominant among the children and the teens. Children having ADHD has differences in the way they persevere things and also has slight variation in their brain development that affects attention, the ability to focus and self control. Thus children with ADHD face obstacles in their path towards success than the normal student. These children get bored with the tasks and get distracted easily. Completing their routine would be a difficult task for them. They are unable to sit still in the class and they roam around. In order to overcome this difficulty in learning among ADHD children Virtual Reality can be implemented. These ADHD children could use VR glasses for simulating their vision and creating a immersive 3D environment. VR headset will put forth a screen in front of the eyes which eliminates the contact with the real world .By doing so, they can learn things without any boredom and they will have a feeling of being in motion. This helps to increase their ability to concentrate.
Automatic Boundary Delineation of Agricultural Fields in Multi temporal Satellite Imagery with Segmentation
Authors:   Associate Professor and Head, Department of Computer Science, Sree Narayana Guru College, Coimbatore, India., Priya Dr. R , Mrs. Darsana  ,   pursuing Ph.D. Computer Science Sree Narayana Guru College, Coimbatore, India.
Published: January 2020

A right difference in agricultural areas is the primary necessity for any sector-primarily based implementation together with estimating agricultural subsidies. Improved decision remote sensing image currently offer higher useful geographic records to delineate regions; however, their automatic managing is tedious. Its miles therefore critical to increase strategies that permit this activity to be completed right away. In any such process, a novel approach named improving the Enhanced Gustafson-Kessel-Like clustering (EGKL) version explores the use of a pc-mastering device to define agrarian areas. The current method seems for limits as either segment corners or linear traits are adjoining regions of small variation all the time series. Nearby everyday deviations from all images a while are coupled, ensuing in a sequence of extended directional edge filters. Even though, in order beautify the excellent of boundary delineation, this advised paintings is merged with sequential features of small variability across the time collection, which includes the standard deviation (STD), Near-Infra Red (NIR) band, or an index along with the Normalized Difference Vegetation Index (NDVI), or band ratios (particularly for hill us of a), or important component images. A photograph evaluation of the effects obtained with the aid of a methodology relevant to two fields of an excessive-resolution satellite image of the fractured agricultural landscape shows that it is helpful to apply the guide vector machines technique for such a task. Finally, the experimental results reveal that the proposed segmentation method is more efficient than the existing segmentation techniques in factors of each quantitative overall performance metrics and appropriateness for land-use classification.
Simulation of Different Light Well Typology by using Daylight Rules of Thumb under Overcast and Intermediate Skies without Sun
Authors:   Centre for Innovative Architecture and Built Environment (SErAMBI), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia., Atan Amran , Ibrahim Nik Lukman Nik ,   Centre for Innovative Architecture and Built Environment (SErAMBI), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia., Sulaiman Mohd Khairul Azhar Mat ,   Centre for Innovative Architecture and Built Environment (SErAMBI), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Published: January 2020

The daylight conditions that are fit for an interior can be easily achieved by applying the simple and comprehensive principles, the daylighting rules of thumb in the process design. In architecture, these rules can be expressed in a different kinds of modes and are divided into categories that based on the parameters which constitute them. Since daylighting is the control admission of natural light, one of the categories can be the light well topology. Thus, an opening plays an important role in influencing the effectiveness of daylight distribution in building. One of the categories is light well typology. This study was conducted using an existing sample of single side opening and two side opening light wells with the comparison of additives to light-well typology under under overcast and intermediate skies without sun also to proposes daylighting rules of thumb for light wells. There are several types of light wells simulated for daylighting performances in this study. Light well models were simulated by conducted using IES_VE application software. Regression analysis was then carried out to find correlation between the measurements obtained in the daylighting simulation and the calculations derived from an established daylighting formula. Thus, existing daylighting formula is modified to create new daylighting rules of thumb for light wells with reflectance mirror in single storey terrace houses. These simple equations can serve as rules of thumb to help architects and engineers in calculating daylight levels for different light well designs.
An Improved Model to Increase Retrieval Time and Security by Data Fragmentation and Replication Process in Cloud
Authors:   Research Scholar Department of Computer Science, Bharathiar University, Coimbatore., Jose P. Peter , Victor Dr S.P. ,   Associate Professor, Department of Computer Science, St. Xavier’s College (Autonomous), Palayamkottai.
Published: January 2020

Cloud computing provides several features to users as well as to the organizations. Even though, there are some issues faced by the user while usingthe cloud. Security is a major concern that is always considered. Likewise Data replication is a significant technique to be consideredfor retrieval time. Replication helps to fetch the data from remote which is a high-time consuming process.To overcome the security issue along with data replication a novel approach is proposed in this paper.Dynamic fragmentation is utilized for the division of a file into fragments. Each cloud nodes has a different fragment to enhance the data security of the system. Blowfish technique is used for encrypt the files before storing in cloudthatdivides messages into 64 bits blocks then encrypts them separately. The result of experimental evaluation shows that this schemes increase the overall performance.
Gradual Weight Updating for Sentiment Mining
Authors:   Department of Computer Science and Engineering, Dr. B. A. M. University, Aurangabad (MS), India., Nandedkar Sugandha , Patil Prof. Dr. Jayantrao ,   Department of Computer Science and Engineering, R. C. Patel Institute of Technology, Shirpur (MS), India., Kawale Prof. Dr. Sunil ,   Post Graduate Department of Statistics, Dr. B. A. M. University, Aurangabad (MS), India.
Published: January 2020

Nowadays, many people prefer the use of social media for communicating and exchanging opinions with each other over face to face communication. This has lead to a generation of a tremendous amount of textual opinioned data. Understanding this opinioned data is useful from all perspectives. But the major challenge exists here is how to extract the exact sentiment hidden behind this huge data. To solve this problem, keyword spotting or dictionary-based approaches are followed. In this paper, we present a Gradual Weight Updating for sentiment mining. It not only considers the polarity of each word similar to the unigram methodology but, it also focuses on the entire cluster of words that contains the unigram. The different steps it follows for sentiment extraction of the word are polarity fetching, cluster marking, weight tagging, valence shifter, adversative conjunction handling, and final score generation. The paper contributions in the area of domain independent opinioned word extraction and accurate polarity mining with the help of context marking approach. We used the various opinionated datasets to compare and illustrate the performance of our proposed system.
Effect of Drilling Process Parameters on Surface Roughness of LM6/B4C Composites
Authors:   Department of Physics, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India,, Rubi C.Sarala , Prakash Dr.J.Udaya ,   Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India,
Published: January 2020

Metal matrix composites are a new course of materials with superior properties to those of the components. Such materials ' machining is distinct from that of traditional materials. So the optimization of machining process parameters becomes inevitable. By applying Taguchi's Signal-to-Noise ratio method, this paper examines the effects of drilling process parameter such as feed, spindle speed, drill material and percentage reinforcement on the drilled hole’s surface roughness. Variance analysis was used to evaluate each system parameter's contribution to surface roughness. The composites were manufactured by stir casting technique using aluminium alloy (LM6) as matrix material and boron carbide particulates at 3%, 6% and 9% by weight as material for the reinforcement. There are four factors investigated each at three levels, so 34 which implies 81 experiments has to be conducted, but by using Design of Experiments approach 27 experiments were conducted using L27 orthogonal array The minimum surface roughness measured for the hole was 1.08 μm at combination of 3000 rpm spindle speed, 50 mm/min feed rate, 3% reinforcement and Carbide drill.
Hybridization of Artificial Bee Colony Algorithm and its variants with Hyperbolic Spiral based Local Search
Authors:   Department of Computer Science and Engineering, Career Point University, Kota, Rajasthan, India., Agarwal Shiv Kumar , Yadav Surendra ,   Department of Computer Science and Engineering, Career Point University, Kota, Rajasthan, India.
Published: January 2020

Artificial bee colony (ABC) algorithm is grounded on intelligent swarming behavior of honey bees. It is one of the efficient algorithm for optimization. The ABC algorithm is good in exploration and sometimes fails to exploit properly. Local search strategies in addition to existing steps play important role to improve exploitation. In order to improve exploitation here a local search inspired by the nature of hyperbolic spiral introduced in ABC. The purposed variant used with ABC, Best-so-far ABC and Gbest ABC. Outcomes proved that hybrid of these algorithms with hyperbolic search gives good results with higher accuracy and reliability.
Existence of Nano Level Force in Protein Plays Applications of Maximum Untold Understanding of Life Form
Authors:   V.S.B. Engineering College, Karur-639111, Tamilnadu, India., Ekambaram Rajasekaran , Meenal R. ,   Prawin Angel Michael, Karunya Institute of Technology and Sciences, Coimbatore – 641114, Tamilnadu, India., Indupriya R. ,   Kazan Federal University, Kazan-420012, Tatarstan, Russia.
Published: January 2020

There are many interactive forces between atoms applied to solve the problem of nature of molecules. One would go on applying this to several diseases and sufferings. On doing so, we have discovered that a new dimension of atomic arrangements playing a role in existence of force of interaction at nano level say at 1.6 nm. Arrangements are in such way that it maintains a carbon fraction of 0.3144 in the structure of biologically important molecule called protein. Arrangements are important from maintaining structure and another way of interaction due to the deficiency of this domain formation. All our analysis conclude that there is new kind of force of attraction available for advancing the science here in biology and other field as well as other elements possess this nano level forces of attraction. Our results are validated with crystal availability because of force existence. Otherwise other may have to be studied accordingly. Bond of all atoms involved in domain formation are altered from original value of bond formation but increased or decreased according to the type of bonds. Alteration can be a measure of this newly identified nano level force of interaction. Our analysis can be extended to other problems in our science of untold answer.
Methods of Forming the Control Voltage in the Current Generation Problem for Electrical Impedance Tomography
Authors:   Department of Information and Measuring Systems And Technologies, Platov South-Russian State Polytechnic University (NPI), Russian Federation., Dmitrievich Shcherbakov Ivan , A. Katsupeev A. ,   Associate Professor, Department of Information and Measuring Systems And Technologies, Platov South-Russian State Polytechnic University (NPI), Russian Federation., V. Shcherbakova M. ,   Department of Biotechnical and Medical Devices and Systems, Platov South-Russian State Polytechnic University (NPI), Russian Federation., V. Tjaglicova P. ,   Department of Information and Measuring Systems And Technologies, Platov South-Russian State Polytechnic University (NPI), Russian Federation.
Published: January 2020

The paper considers questions of control signal for injection current generation in electric impedance tomography devices. The most common injection current generation scheme is voltage controlled current sources. In these circuits, the shape, frequency and amplitude of the current are set by the control voltage. The most common control voltage generation schemes are considered; their advantages and disadvantages are indicated. A circuit using direct digital synthesis and an amplitude-tuning digital-to-analog converter was selected, its block diagram was developed, and an operation algorithm was described. The developed scheme will improve the efficiency of the research by the method of electrical impedance tomography due to the complete automation of the process of controlling its parameters.
Design of Multi-loop Current Control Strategies for LCL Filtered Grid-connected PV System
Authors:   SOEE, KIIT, Deemed to be University, BBSR, India., Sahu Pradeep Kumar , Jena Satyaranjan ,   SOEE, KIIT, Deemed to be University,BBSR, India., Dei Gitanjali ,   SOEE, KIIT, Deemed to be University,BBSR, India.
Published: January 2020

This paper presents numerous feedback current controller methods for the grid-connected PV systems incorporating with third order LCL filter. The various potential dual-loop feedback current controller schemes for a grid-tied electrical converter and a comparison among these controllers are made based on their performance. The effectiveness of these current controllers are based on various views like performance under polluted grid condition and also the dynamic performance of two control schemes under different transient conditions. A commonly used PI controller are employed in all cases of multi-loop controllers and also the electrical converter used here is operated in voltage control mode. In this work, a third-order low-pass LCL filter is employed to minimize the high order harmonics which are created due to the switching of the converter. The LCL filter is incorporated among the dc-ac converter and the utility grid. Two current regulation techniques are focused here. The design, analysis and the performance of these controllers are briefly discussed in this paper. By comparing their performance, anyone can suggest their applications in the grid-tied PV systems. All the current control schemes are incorporated with a grid-connected system of 2-KVA voltage source inverter. Simulation results are produced to validate the performances of two current control schemes. The output ohmic resistance of VSI is taken into account here for their performance analysis.
Design of Low Cost Wireless Surveillance System for Aircraft
Authors:   Department of Electrical and Electronics Engineering, Hindustan Institute of Technology and Science, Padur, Chennai (Tamil nadu) India., Nandakumar K. , Pillai Adarsh Vijayan ,   Department of Electrical and Electronics Engineering, Hindustan Institute of Technology and Science, Padur, Chennai (Tamil nadu) India., Priyadarshini S. ,   Department of Electrical and Electronics Engineering, Hindustan Institute of Technology and Science, Padur, Chennai (Tamil nadu) India, Sitharthan R. ,   School of Electrical Engineering,Vellore Institute of Technology,Vellore, Chennai (Tamil nadu) India., Devabalaji K. R. ,   Department of Electrical and Electronics Engineering, Hindustan Institute of Technology and Science, Padur, Chennai (Tamil nadu) India.
Published: January 2020

The aim of the project is to estimate the position and orientation of a moving platform in a 3D environment which is of significant importance in many areas such as robotics, sensing, surveillance and Unmanned Aero Vehicles. In order to perform this, one can employ single or multiple sensor fusions to improve the accuracy of estimation and to compensate for individual sensors deficiencies. We are using camera surveillance controller system in which we control the movement of the camera and it is live video streaming to a remote location. The camera is made to view +180 to -180° by using servomotor. The GPS and IMU sensor modules are implanted onto the model for controlling and monitoring the flight. Wireless technology allows viewing remotely and controlling the flight as required. This paper focuses on LOW-COST WIRELESS SURVEILLANCE for improved security, more flexible and efficient systems.
Meeting Scheduling Application using Availability and Priority Attendance Heuristics
Authors:   Faculty Member, Mobile Application and Technology Program, Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia., Wibisurya Aswin , Faahakhododo Ikhtiar ,   Faculty Member, Mobile Application and Technology Program, Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia.
Published: January 2020

Meeting scheduling is a repetitive and time consuming task for many organizations. Emails and electronic calendars has been used to help a meeting host in this process. However, it does not automate the process of searching the optimal time slot. Manual scheduling may result in suboptimal schedule. Therefore, automation is needed for meeting scheduling problem. The purpose of this research is to propose an applied model consisting of both acquiring participants’ existing schedule, and searching for an optimal time slot. Previous studies groups the solution of meeting scheduling into either constraint satisfaction or heuristics approach. Heuristics is more appropriate for a dynamic environment. The heuristics-based model is designed to consider participant availability and participant prioritization. The more participants are available, the better the time is as a candidate for optimum schedule. In the proposed model, the availability of certain key person, experts, or host may carry more weight than normal participant. An Android based application is developed as a prove of concept of the proposed model. Google Calendar API is used in this model to acquire the existing schedule, then each time slot is assigned a score based on availability weighting. The time slot with the highest score is considered the optimal solution. Evaluation is done by simulating the scheduling part for various numbers of meetings and time slots. The result shows that the model is capable of searching the optimal meeting schedule in less than one second for each of the experiment.
Esa Based Upqc Controller to Improve Power Quality in Microgrid System
Authors:   Assistant professor, Department of EEE, Aditya Institute of Technology and Management, Tekkali Srikakulam, Andhrapradesh, India., Rao Dr. B. Srinivasa , Sowjanya N. ,   Assistant professor, Department Of EEE, Aditya Institute of Technology and Management, Tekkali, Srikakulam, Andhrapradesh, India., Rao M. Bhaskara ,   Assistant professor, Department of EEE, Aditya Institute of Technology and Management, Tekkali Srikakulam, Andhrapradesh, India., Raju S. Naga ,   Assistant professor, Department of EEE, Aditya Institute of Technology and Management, Tekkali Srikakulam, Andhrapradesh, India.
Published: January 2020

Generally, Power Quality is the main concern parameter in present power system scenario, the main causes for effecting the power quality is due to either harmonic distortion, voltage imbalances, reactive power variations. There are many techniques applied to maintain this power quality in literature. In Facts family, the UPQC controller plays a key role, because it uniquely controls all the transmission parameters. The UPQC controller is combination of series-shunt converters with common dc link. The signals required for these converters are generated by reference and actual signals of bus and dc link capacitor. Phase locked loop helps to provide the phase angle sequence required to improve power factor. In addition with, this paper is implemented with extended search algorithm to better control the dc link voltage for improving power quality. Mat lab/Simulink is used to test the system conditions and performance.
Enhanced Particle Swarm Optimization assisted Cooperative Spectrum Sensing in Cognitive Radio under Rayleigh Fading Scenario
Authors:   Ph.D. Department, Electronics and Communication Engineering. Annamalai university, chidambaram, Harikrishnan R. , Padmathilagam Dr. V. ,   Associate Professor, Electrical Engineering in Annamalai university, chidambaram
Published: January 2020

When performing cooperative spectrum sensing by using Soft Decision Fusion (SDF), the weighting coefficients play a major role in the detection performance. In this work, by utilizing the Enhanced Particle Swarm Optimization (EPSO) is optimization of the weighting coefficient vector is carried out. The EPSO selects the best weighting coefficients from the weighting coefficient vector. The detection accuracy of the EPSO technique is evaluated and contrasted with traditional PSO, GA (Genetic Algorithm) and also with traditional Soft-Decision Fusion (SDF) methods by using MATLAB simulations. From simulation results, it is inferred that the proposed technique outperforms all other Soft-Decision methods over Rayleigh channel. An increased detection performance is obtained as inferred from the results.
Dielectric Resonator Rectenna for RF Energy Harvesting System
Authors:   Research Scholar, Department of Electronics & Communication C U Shah College of Engineering and Technology, Wadhwan, Gujarat, India., Makwana Renuka , Dwivedi Dr. VedVyas ,   Professor, Department of EC of Technology and Engineering, C U Shah University, Wadhwan, Gujarat, India., Mehta Prarthan ,   Department of Electronics & Communication Technology and Engineering, D D University, Nadiad, Gujarat, India.
Published: January 2020

Recently, the various methods for RF energy harvesting and reutilizing has become the challenging matter around the world to minimize the wastage of RF energy in the form of electromagnetic waves within the atmosphere. An associate approach of collecting a particular range of frequencies & conversion into dc current- Rectenna is proposed here. Star shaped Dielectric Resonator Antenna is implemented as antenna for receiving RF energy at 2.44 GHz resonant frequency. It is observed that Star shaped DRA exhibits a radiated power of 0.8825 W with respect to 1W incident power and maximum gain of 5.9672 dBi. The RF power received by Antenna is given to a Rectifier circuit via proper impedance matching circuit. The rectified pulsating DC power is given to capacitor filter to suppress harmonics .
Prediction and Analysis of Water Resources using Machine Learning Algorithm
Authors:   Research Scholar, Rayalaseema University, Kurnool, India,, K. Sarakutty T. , K. Ravikumar ,   Research Scholar, Kalinga Institute of Industrial Management, Bhubaneshwar, India,, M. Hanumanthappa ,   Department of Computer Science and Applications, Bangalore University, Bengaluru, India,
Published: January 2020

Water demand prediction plays an important role in urban and environmental planning, ecological development, decision-making processes and optimum utilization of water resources. A precise water demand prediction has a key job in the forecasting, design, process, and organisation of water resources frameworks. The under stress natural resources and the ever increasing population size makes it dominant to accurately and efficiently forecast water demand in the urban area which is possible by applying data mining techniques on the huge volumes of available water data. This paper focuses on building precise predictive models for water demand prediction using support vector machine which takes care of the nonlinear changeability of water demand at diverse levels for optimal operations.
Artificial Music Generation using LSTM Networks
Authors:   Assistant Professor, Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad, Hyderabad, India., Eedi Hemalatha
Published: January 2020

Advancements in machine learning have minimized the gap of variation between human and algorithm composed music. This paper realizes a music generation system using evolutionary algorithms. The music generation is fully automated with no requirement of human intervention. Multiple music sample from a single dataset were used to the neural network. Software has been constructed to exhibit the results over various datasets. The proposed model is based on recurrent neural network with the input layer represents a measure at time T, and the output layer represents the measure at time T+1. The approach results in generation of new music composition by the system. Composition rules are used as constraints to evaluate the melodies generated by the novel neural network. Thus, the results are expected to evolve to satisfy the defined constraints. The proposed system of work would be capable of music generation without human intervention.
Effect of Different Propagation Models in Routing Protocols
Authors:   Department of Computer Science, Assam University, Silchar, Assam, India., Khan Munsifa Firdaus , Das Indrani ,   Department of Computer Science, Assam University, Silchar, Assam, India.
Published: January 2020

Mobile Ad hoc Networks (MANET) are wireless networks where communication of nodes takes placevia radio waves. Due to dynamic topology and mobility of nodes frequent path failure takes place which in return affects the Quality of Service (QoS) in MANET. This paper mainly focuses on the experimental analysis on different propagation models namely Two-ray ground reflection, Free Space and Shadowing models on AODV and DSDV. We have done rigorous experiments to verify the effects of various propagation models and try to find its environment suitability. The QoS parameters we have used for the observation of the performance are throughput, delay and Packet-Delivery-Ratio (PDR). Simulation is done using NS-2.Free Space model gives better performance in both the protocols in contrast to other models. This paper will be helpful for researchers, students who are newly involved in research for better understanding and utilization of propagation models in corresponding environment.
Design of Ultrasonic Conical Horn using Aluminium Alloy and Steel
Authors:   Assistant Professor, VNR VAN Jyothi Institute of Techonlogy and Science, Hyderabad, (Telangana) India., Chilukuri Mrs. Priyadarsini , Naik Mr. M. Kalyan ,   P.G. scholar, Advanced Manufacturing System, VNRVJIET, Hyderabad, (Telangana) India.
Published: January 2020

Horn plays an important role in ultrasonic machining process. The design of horn is critical to its efficiency and quality of machining process. Ultrasonic horns are tuned. Components designed to vibrate in a longitudinal mode at ultrasonic. Frequencies. Reliable performance of such horns is normally decided by the uniformity of vibration amplitude at the working surface and the stress developed during loading condition. The design parameters of horn are calculated from the theoretical derivation of horn. By these parameters, the horn is designed and analyzed using CREO PRO and ANSYS software. In this paper the main object of the project is to Improve the performance of the Horn from the analysis test results, The horn is compared with other available horn results by comparing its natural frequency, amplitude vibration and temperature of the horn.
Khasi to English Neural Machine Translation: an Implementation Perspective
Authors:   Department of Computer Science, Assam University, Silchar, India., Thabah N. Donald Jefferson , Purkayastha Bipul Syam ,   Department of Computer Science, Assam University, Silchar, India.
Published: January 2020

Being able to translate and communicate consistently from one language to another would have been the ultimate goal of an intelligent system. With recent advancement of Neural Machine Translation (NMT), it has shown a promising solution to the problem of machine translation. NMT generally requires large size parallel corpora to obtained a good translation accuracy. In this paper, we would like to explore a Translation system from Khasi to English language using both supervised and unsupervised technique. Unsupervised was inspired to help attaining a better translation accuracy for low resource language. It was influenced by the recent advancement of unsupervised neural machine translation which primarily relies on monolingual corpora. In this work, Supervised NMT technique was also implemented and compared with the standard OpenNMT toolkit. Here, we also use Statistical Machine Translation (SMT) tools like Moses as a standard benchmark to compare the translation accuracy. When considering monolingual corpus, we obtain an accuracy of 0.23%. Given the small size monolingual corpus the result was lacking but showed promising rooms for improvement. We obtain much better accuracy of 35.35% and 41.87% when we use parallel corpus in supervised NMT and OpenNMT respectively. On comparison with SMT system with Blue score of 43.76%, the supervised NMT system was on par in its performance. Lastly, with improvement in corpus size and better adaptation of preprocessing steps on the source language (Khasi) the result can be tune to a better outcome.
Variable Frequency Signal Carrying Nonlinear Transmission Line - Modeling using Machine Learning
Authors:   Department of Electronics and Communication Engineering, BMS College of Engineering, Bengaluru, India., S. Nagaraj , D. Seshachalam ,   Department of Electronics and Communication Engineering, BMS College of Engineering, Bengaluru, India.
Published: January 2020

in modeling of complex systems, manual creation and maintenance of the appropriate behavior is found to be the key problem. Behavior modeling using machine learning has found successful in modeling and simulation. This paper presents artificial neural network (ANN) modeling of transmission line carrying frequency varying signal using machine learning. This work uses proper orthogonal decomposition (POD) based reduced order modeling. In this proposed work, snapshot sets of complex mathematical model of nonlinear transmission line and also linear model are obtained at different time interval. These snapshot sets are arranged in matrix form separately for nonlinear and linear models. POD method is applied on both the matrices separately. This reduces the order of the matrix which is used as input and output data set for neural network training through machine learning technique. Trained neural network model has been verified using different untrained data set. The proposed algorithm determines the dimension of the interpolation space prompting a considerable decrease in the computational expense. The proposed algorithm doesn't force any imperatives on the topology of the appropriate circuit or kind of the nonlinear segments and hence relevant to general nonlinear systems.
Feature-Based Opinion Mining and Managed Machine Learning with Sentiment Classification Models
Authors:   Department of Virtualization, University of Petroleum & Energy Studies, Dehradun (Uttarakhand) India., Patni Dr. Jagdish Chandra , Garg Shubhita ,   School of Computer Science, University of Petroleum & Energy Studies, Dehradun (Uttarakhand) India., Romika  ,   School of Computer Science, University of Petroleum & Energy Studies, Dehradun (Uttarakhand) India., Billus Shubham ,   School of Computer Science, University of Petroleum & Energy Studies, Dehradun (Uttarakhand) India., Billus Shivam ,   School of Computer Science, University of Petroleum & Energy Studies, Dehradun (Uttarakhand) India.
Published: January 2020

Sentiment Analysis is individuals' opinions and feedbacks study towards a substance, which can be items, services, movies, people or events. The opinions are mostly expressed as remarks or reviews. With the social network, gatherings and websites, these reviews rose as a significant factor for the client’s decision to buy anything or not. These days, a vast scalable computing environment provides us with very sophisticated way of carrying out various data-intensive natural language processing (NLP) and machine-learning tasks to examine these reviews. One such example is text classification, a compelling method for predicting the clients' sentiment. In this paper, we attempt to center our work of sentiment analysis on movie review database. We look at the sentiment expression to order the extremity of the movie reviews on a size of 0(highly disliked) to 4(highly preferred) and perform feature extraction and ranking and utilize these features to prepare our multilabel classifier to group the movie review into its right rating. This paper incorporates sentiment analysis utilizing feature-based opinion mining and managed machine learning. The principle center is to decide the extremity of reviews utilizing nouns, verbs, and adjectives as opinion words. In addition, a comparative study on different classification approaches has been performed to determine the most appropriate classifier to suit our concern problem space. In our study, we utilized six distinctive machine learning algorithms – Naïve Bayes, Logistic Regression, SVM (Support Vector Machine), RF (Random Forest) KNN (K nearest neighbors) and SoftMax Regression.
Development of Low-Cost Auto Robot for Plastic Floating Garbage Collection using IoT
Authors:   Assistant professor, Department of Information Technology, Suan Sunandha Rajabhat University, Thailand., Nuanmeesri Sumitra
Published: January 2020

Nowadays, there is still much plastic waste floating in the sea and rivers, causing a limited number of officials to take care of this waste is not thoroughly. In this paper propose to develop the low-cost auto robot from waste materials based on Internet of Things for grabbing and collecting the floating garbage in the closed of water pool. The sensors and motors were mixed to control the robot on water surface and collect the plastic floating waste which is detected by sensors. To classified the floating garbage, the Fast Approximation Nearest Neighbor algorithm was applied to system in the web platform. The activities for garbage collection were submitted to social media such as LINE notify application. As a result, the auto robot system has the accuracy value at 94.4% and 98.8% for stationary mode and cover mode respectively.