bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Seidel Energy of Certain Mesh Derived Networks
Authors:   Department of Mathematics, Mount Carmel College, Bangalore-58, India, B Sophia Shalini G. , Saleh Anwar ,   Department of Mathematics, College of Science, University of Jeddah, Saudi Arabia, V Dhananjayamurthy B. ,   Department of Mathematics, NITTE Meenakshi Institute of Technology, Yelahanka, Bangalore-64, India
Published: January 2020

The energy of graph G is defined as the sum of the absolute values of eigenvalues of the adjacency matrix A(G). The manual calculation of energy of graphs consumes several man hours. In this paper, we use MATLAB to generate the Seidel matrix and hence calculate the Seidel energy of some mesh derived networks.
Cross Coupled Differential High Speed Comparator
Authors:   Associate Profssor, ECE, Koneru Lakshmaiah Educational Foundation, Guntur, India., Rooban S. , Sri S.Jaya Sai ,   ECE, Koneru Lakshmaiah Educational Foundation, Guntur, India., Jayaram T. ,   ECE, Koneru Lakshmaiah Educational Foundation, Guntur, India., Krishna D.Praveen ,   ECE, Koneru Lakshmaiah Educational Foundation, Guntur, India.
Published: January 2020

Power efficiency and high speed comparator is presented. ,n-MOS transistors are used to design preamplifier stage and the latch stage. Both stages are controlled by a special clock circuit. By using clock circuit we can achieve enough preamplification gain. At the evaluation phase, the latch is activated with a delay to obtain sufficient pre-amplification gain and avoid extra power consumption. At this phase transistors are cross coupled to increase the preamplifier gain and to lower the input voltage common mode of the latch is used to strongly activate the n-MOS transistors (on the latch input) and reduce the delay. This circuit is designed with n-MOS transistors due to its inherent superiority over the p-MOS transistor. The proposed cross coupled comparator reduces the power and delay compared to conventional CMOS comparators.
Artificial Intelligence Based Vector Controller for Switched Reluctance Motor SRM
Authors:   Deparment of EEE, Sathyabama Institute of Science& Technology, Chennai,India., Ranadheer Patti , Prabakaran N. ,   Department of ECE, KLEF (Deemed to be University), Guntur, India.
Published: January 2020

The prevalence of the Switched Reluctance Motors (SRMs) increments step by step because of its points of interest, for example, Simple structure, low cost, less weight, high effectiveness and high beginning torque when contrasted with regular motors. SRM is an electric motor which has invaluable highlights that qualifies it to be utilized in electric vehicle, aviation and industrial applications. In this paper, the switched reluctance motor is controlled using vector control by AI controller (fuzzy) so as to limit the torque ripples by directing torque inside indicated hysteresis band. AI Control of SRM encouraged through an irregular converter. The proposed AI controllers are executed in MATLAB/SIMULINK for specified SRM parameters. As indicated by the attained outcomes the SRM behavior is better when impelled by AI controller in contrast with usual controllers.
Effect of Different Operating Conditions on Performance of Commercial Low-Temperature Thermoelectric Modules
Authors:   Mechanical Department, G. H. Raisoni College of Engineering, Nagpur, India., Patil Dipak S. , Arakerimath R. R. ,   Mechanical Department, G. H. Raisoni College of Engineering, Pune, India., Walke P. V. ,   Mechanical Department, G. H. Raisoni College of Engineering, Nagpur, India, Shelke R. S. ,   Mechanical Department, G. H. Raisoni College of Engineering, Nagpur, India.
Published: January 2020

In the field of waste heat recovery, thermoelectric generators (TEG) are used to convert waste heat to electric power. This system attracts the attention of researchers to make it more and more efficient. The performance of thermoelectric module (TEM) plays a crucial role for thermoelectric system. Appropriate selection of thermoelectric module is one of the important criteria for enhancing the power output and conversion efficiency of thermoelectric generator. In this work, the effect of various operating conditions on performance of thermoelectric modules was experimentally investigated. Three commercial bismuth telluride (Bi2Te3 ) thermoelectric modules (TEM1, TEM2, and TEM3) were experimentally tested to find the best performance module for low-temperature waste heat. The open-circuit voltage, power output, and conversion efficiency were measured at various operating conditions. Different operating parameters such as water mass flow rate, heater voltage, hot and cold side temperature of thermoelectric module, and external load resistance were considered for this work. An electric heater was used as a heat source and water used as a cooling fluid at heat sink side. It was observed that the TEM1 shows maximum power output of 0.31, 0.71 and 1.25W, for temperature ranges of 80-100, 100-150, and 150-200 oC respectively. TEM3 achieved maximum power output 0.81W for temperature range of 100-150 oC. TEM1, TEM2 and TEM3 have the maximum conversion efficiency of 1.37, 0.60, and 1.64 % respectively. The TEM2 having less power output and conversion efficiency for temperature range of 80-200 oC compare to TEM1 and TEM3. However, the TEM1 is more appropriate for temperature range of 80-200 oC and the TEM3 is also suitable for the temperature range of 80-150 oC.
Classification of Spinal Muscle Atrophy Disease using SVM in Machine Learning
Authors:   Department Of CSE, BVC Engineering College, Odalarevu, JNTUK Kakinada, AP, India, Bhavani B. Ganga , Kumar G. L. N. V. S. ,   Department of MCA, BVCITS, Amalapuram, JNTUK Kakinada, AP, India., Rekha M. L. ,   Department of MCA, BVCITS, Amalapuram, JNTUK Kakinada, AP, India., Kumar B. P. N. Madhu ,   Department Of CSE,BVC Engineering College, Odalarevu, JNTUK Kakinada, AP, India., V. Raja Rao P. B. ,   Department Of CSE, BVC Engineering College, Odalarevu, JNTUK Kakinada, AP, India.
Published: January 2020

SMA is a genetic neuromuscular disease. It is a rare disease. It is caused by mutations in the survival motorneuron (SMN) gene that encodes SMN Protein. Maindifficult area of SMA is muscle weakness, causing withdifficulty with moving, swallowing or breathing. Thereare four types of SMA’s. The primary objective of thispaper is to classify the SMA’s by using support vectormachine classifier. Then we can easily predict the life span of the children based on the group of SMA. This disease is classified on the basis of age of onset and clinical course.
Question to Query: Converting Human Language to DBMS Query
Authors:   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Thakkar Yashvi , Palwala Faiz ,   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Vyas Utsav ,   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Agarwal Krati ,   School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Regunathan Rajesh Kannan ,   School of Computer Science and Engineering Vellore Institute of Technology, Vellore
Published: January 2020

In this paper a method has been proposed keeping in the mind the need for systems that could generate structured queries from normal language keeping in mind that the user has no prior knowledge of database query language. A novel method which aims at aiding analyst who aren’t well versed with codes, but need quantitative outputs to analyze, predict and alert the business or market. A python model is used, which aims at converting any sentence typed in English to a query provided that such tables and database is present for query processing. Tree tagging is used here to relate words typed in to SQL query syntax. Any sentence typed in by analyst, it further annotated by parts of speech and lemmas. A list of generic words and stop words is used while parsing the input the sentence and tagging it. Query is generated by simultaneously removing the stop words, mapping the keywords with the one’s used in structured query language. The generated query comes out in form of a JSON file.
Reliability Assessment of Photoelectric Smoke Detector, Ionization Smoke Detector and a Fire Alarm Control Panel with Both Detectors AS Notification Device
Authors:   Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Sector 125, NOIDA,U.P. India, Chandra Anil , Gupta Surbhi ,   Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Sector 125, NOIDA, U.P. India, Jaggi Chandra K ,   Department of Operational Research, University of Delhi, Delhi
Published: January 2020

Notification device like smoke detectors are critical and important part of a Fire Alarm Control Panel (FACP). Popularly used smoke alarms in commercial establishments in India are photoelectric smoke alarms (PESD) and ionization smoke alarms (ISD). In this study reliability assessments of PESD with Integrated Circuit (IC) – MC145010 and ISD with IC – MC145017 have been carried out on the basis of reliabilities of their respective electronic components. The cases considered are: (I) Failure rates of all components are equal and constant over time (II) Failure rates of all components are equal and follow Weibull distribution and (III) Failure rates of all components are different. To determine failure rates of 9 volt battery of both detectors additional assumptions taken are, (a) battery life is 10 years with constant failure rate, (b) battery life follows Weibull distribution. In this paper the reliability and failure rate of two types of smoke alarms have been calculated based on failure rates of their electronic parts like resistors, capacitors, Integrated Circuits etc. These failure rates have been subsequently used for reliability assessment of a non-addressable FACP containing four PESDs and four ISDs as notification device. A comparison of failure rates was also performed on the basis of two quality factors of electronic components – military specific and lower than military specific. Mean Time To Failure (MTTF) of PESD and ISD have been calculated in all the cases. Subsequently, MTTF values obtained in case III were used to approximate failure rates for case I case II.
Electrical Loading Assessment of Commonly Used Transformers for Feeder 21 of Pampanga Distribution Utility
Authors:   Electrical Engineering Department, Don Honorio Ventura State University, Bacolor, Pampanga, Philippines., Jr Reynaldo H. Gomez , Santos Edgardo M. ,   Electrical Engineering Department, Don Honorio Ventura State University, Bacolor, Pampanga, Philippines., Tolentino Armie C. ,   Electrical Engineering Department, Don Honorio Ventura State University, Bacolor, Pampanga, Philippines., Bulanan Eldren V. ,   Human Resources and Development Department, Pampanga I Electric Cooperative, Mexico, Pampanga, Philippines., Florencondia Noel T. ,   Graduate School Department, Nueva Ecija University of Science and Technology, Cabanatuan, Nueva Ecija, Philippines.
Published: January 2020

Transformer plays a vital part in the process of utilization of electricity. In power distribution, the most widely used equipment is the distribution transformer (DT) and function to transform the primary voltage of 13200 volts to the utilization level voltage of 230 volts. In a distribution system, transformers are installed serving commercial, industrial, irrigation, street lights and residential consumers. Distribution transformers were classified as sole-used and commonly-used distribution transformers. The study focuses on assessing the commonly-used distribution transformer of Feeder 21 of Pampanga Distribution Utility. Microsoft Excel 2013 was used to evaluate the percent loading, core and copper losses of each DT’s installed in the feeder. The DTs were classified according to their percent loading: Overloaded Above 71%, Normal Loaded 40% to 70%, and Under Loaded Below 40%. From the data from 2017-2018, 104 units commonly-used DT’s were installed in the feeder. From the results obtained, 30 units were overloaded distribution transformers while 31 units were under loaded distribution transformers. Out of 104 distribution transformers 61 of which are not in the normal loading conditions. The total Core loss in MWh of the distribution transformer in under loaded and overloaded conditions were 34.37 and 38.04, while the copper loss in under loaded and overloaded conditions was 7.46 MWh and 199.76 MWh respectively. The study also shows the implication if the percent loading was maintained to 70%, 110.21MWh will be saved by the electric utility. The researchers find that there is a need in uprating or downrating of transformer and quantifying the consumer connected in each distribution transformers for proper transformer loading may be considered by the Distribution Utility.
Performance Modeling of Classification Techniques on Movie Sentiments
Authors:   M.Tech Scholar, Department of Computer Science & Engineering, Guru Jambheshwar University of Science & Technology, Hisar, India., Rani Pooja , Singh Jaswinder ,   Assistant Professor Department of Computer Science & Engineering, Guru Jambheshwar University of Science & Technology, Hisar, India.
Published: January 2020

The sentiment-based social media represents a goldmine approach for analyzing the performance of the products, hotels, movies, politics, etc. Large opinions of the people are found over movie comments that are honest, informative, and casual as compared to the formal type of data-survey modeling using magazines or reports. The work proposed is based on the rating of movies. This paper analyzes the performance of classifiers for the prediction of sentiment class i.e., positive and negative by using artificial neural network, k-nearest neighbor and hybrid approach. The success of these classification techniques depends mainly on the appropriate extraction of the set of characteristics used to detect sentiments. Hybrid of two or more classifiers is mainly used to enhance the results. In the proposed experiment Hybrid of ANN and KNN shows improvement in precision and accuracy than other classifiers.
Minimizing Noise in Sinusiodal Function Signal using Wavelet Transform
Authors:   Civil Engineering Department, Bina Nusantara University, Jakarta, Indonesia., Hidayat Irpan , Suangga Made ,   Civil Engineering Department, Bina Nusantara University, Jakarta, Indonesia., Soegiarso Roesdiman ,   Civil Engineering Department, Tarumanagara University, Jakarta, Indonesia., Arumsari Putri ,   Civil Engineering Department, Bina Nusantara University, Jakarta, Indonesia., Yuliastuti  ,   Civil Engineering Department, Bina Nusantara University, Jakarta, Indonesia.
Published: January 2020

Resistances that occur in retrieving and processing signal is caused by the interference (noise) on the data signal measurement results. The resistance will raise uncertainties in determining the value of the frequency. This is due to the signal which is mixed with the noise in the original signal. In general, the process of signal analysis uses Fast Fourier Transformation (FFT). However, by using FFT in analyzing and reconstructing there are still doubts in determining the real frequency due to the still visible noise in the signal. In this study the signal function used is a sinusiodal function, Y = 2 sinπf1 t + 2 sin πf2 t, with a given noise value of 2 DB. The specified frequency value of f1 and f2 equal to 0.25 Hz and 5 Hz, respectively. This research proposed wavelet transforms to analyze and in filtering original signal with noise. By using the transformation wavelet, signal with noise filtered with the high pass and low pass filter method and also using the Haar wavelet function in analyzing. Once the signal is decomposed using wavelet transformation, the wavelet coefficients value will be obtained. The wavelet coefficient values will then threshold within a range of 5-50%. The purposed in determining the treshold value is to reduce the signal data identified as a noise signal data. If the value of wavelet coefficient below the treshold percentage value multiplied by the maximum wavelet coefficient, it is identified as a noise signal data, and the value of coefficient wavelet will be zero. The wavelet coefficient will then be reconstructed in order to obtain the data signal with the new sinusoidal function. In determining the value of the reconstructed frequency signal, the Fast Fourier Transform (FTT) method is used. The results of the study is signals with noise can be analyzed and filtered using wavelet transforms, by changing the signal into wavelet coefficients. Furthermore, the threshold of 5% is capable in reducing of noise in signal so that the graph of frequency and amplitude showed a clearer value of frequency.
Route Deviation Algorithm with Location Ambiguity in Wireless Sensor Networks
Authors:   PhD Scholar, School of Engineering and Technology, Ansal University, New Delhi, India., Shivanka Priyanka Chugh , Rai Dinesh ,   Associate Professor and Dean, School of Engineering and Technology, Ansal University, New Delhi, India., Indu S. ,   Professor in ECE Department, Delhi Technological University, New Delhi, India.
Published: January 2020

Nowadays, the primary concern of geographic routing protocol lies in the fact of minimisation of energy dissipation during the transfer of each packet in a network. This paper proposes an energy-efficient real-time algorithm in sensor networks, i.e., Route deviation Algorithm. Route deviation algorithm combines the characteristics of both distance-based criteria and direction or angle based criteria. In this paper, we have shown a comparison amongst COMPASS algorithm, NFP, MER and Route deviation algorithm. The simulation model includes numerous parameters, namely, threshold energy, number of sensors, spread of the map, position of sensors and transmission time. The results obtained through the simulation model supports the fact that the Route deviation algorithm accomplishes the task of saving energy and adds to the life of the networks.
Durability Properties on Marine Algae Concrete
Authors:   Department of Civil Engineering, Faculty of Engineering and Technology SRM Institute of Science and Technology, Kattankulathur-603 203, Tamil Nadu, India., Ramasubramani R. , G Pennarasi. ,   Department of Civil Engineering, Faculty of Engineering and Technology SRM Institute of Science and Technology, Kattankulathur-603 203, Tamil Nadu, India, Sridhar M. B. ,   Department of Civil Engineering, Faculty of Engineering and Technology SRM Institute of Science and Technology, Kattankulathur-603 203, Tamil Nadu, India, Prakashchandar S. ,   Department of Civil Engineering, Faculty of Engineering and Technology SRM Institute of Science and Technology, Kattankulathur-603 203, Tamil Nadu, India.
Published: January 2020

Investigation of marine algae had its progress, due to chemical reaction with cement as a result nature gets affected by contamination and thus the inclusion of algae in the concrete found to control the destructive reactions. Algae are natural congenial which adds to the monetary of the concrete and, in the meantime, there is a decline of the wastes. Durability of concrete assumes an essential job in concrete structures. Durability of concrete might be characterized as the capacity of cement to withstand weathering activity and acid attack by retaining its ideal building properties. There are different materials utilized in the concrete to increase durability property. In this investigation, marine brown algae was utilized as added substance with concrete. A fixed water to cement ratio (W/C = 0.5) for M25 grade concrete was adopted with different marine brown algae percentages at 2%, 5% and 8%. The outcome demonstrates that 8% marine algae concrete performed well when contrast with traditional concrete. Deflection behaviour test established that thecrucial load limit of ideal mix concrete slab was found to be higher than the customary conventional concrete slab.
Real-Time Mosquito Species Identification using Deep Learning Techniques
Authors:   Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, India., Mulchandani Pratik , Siddiqui Muhammad Umair ,   Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, India, Kanani Pratik ,   Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, India.
Published: January 2020

According to the World Health Organization, diseases such as malaria and dengue account for almost one million deaths every year. Carrier mosquitoes for a particular disease remain exclusive to it. A majority of carrier mosquitoes spread the disease throughout a region by reproducing in it. With advancements in Machine Learning and Computer Vision technologies, the species of mosquitoes in a particular region can be easily and swiftly detected using recordings of their wing movements. The wingbeats of a particular mosquito species are unique, making this a reliable method to identify them. Once these solutions are deployed on mosquito traps, a particular region can be alerted if, for example, an Aedes Aegypti mosquito is found. This mosquito species is widely known to carry the Zika virus. The identification of such carrier species can also help in detecting the spread of mosquito-borne diseases in the surveyed region. In this paper, we go through various techniques that show promising results in the identification of mosquito species. The trained models can be deployed on constrained devices to make a cost-effective and efficient mosquito species identification system.
TSD CPI Traffic Sign Detection Technique Based on Centroid Position Identification in Text Mining
Authors:   Research Scholar, Department of Computer Science, Memorial College (Autonomous), Puthanampatti-621007 (Tamil Nadu) India., Karthika R. , Murugan S. ,   Associate Professor, Department of Computer Science, Memorial College (Autonomous), Puthanampatti-621007 (Tamil Nadu) India.
Published: January 2020

Detecting and Identifying traffic sign is a complicated issue due to the changing variability in cloud conditions. Hence, it is necessary to identify and detect of traffic signs during journey. The traffic text sign identification fails due to noise, blur, distortion and occlusion. In order to identify the text, a technique should be adapted that recognizes the text with improved accuracy. In existing algorithms such as Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) were not detecting the Centroid position. In this paper, the text Centroid of position sign is detected using text color, font and size. During journey, if the text is blurred, this Traffic Sign Detection Technique based on Centroid Position Identification (TSD-CPI) K-means algorithm for clustering is possible to use. As a result, it detects the text that with improved accuracy. Ultimately, it reduces the processing time. The experimental result reveals that using WEKA-3.8 with the proposed technique shows improvement over the existing algorithms in terms of precision and Recall which enhance the accuracy in text mining.
Expression Invariant Features for Face Recognition
Authors:   Associate Professor, Department of Computer Science and Engineering, KL University, Andhra Pradesh, India, Mohit Menta , Harichandana Neralla ,   Student Department of Computer Science and Engineering, (CSE) Koneru Lakshmaiah Education Foundation Vaddeswaram, Guntur District, Andhra Pradesh, India., Bhagyasri Pendem ,   Department of Computer science and Engineering Koneru Lakshmaiah Education Foundation ,Vaddeswaram, Guntur District. Andhra Pradesh, India., Kumar P. M. Ashok ,   Department of Computer Science and Engineering, Koneru Lakshmaiah Educational Foundation, Vaddeswaram, Guntur District, Andhra Pradesh, India.
Published: January 2020

Personal Computer sourced Face Recognition has been a sophisticated and well-found technique which is being rationally utilized for most of the authenticated cases. In reality, there is a number of situations where the expressions of the face will be different. We are here able to instinctively detect the five universal expressions: smile, sadness, anger, surprise, neutral by studying face geometry by determining which type of facial expression has been carried out. Using some facial data with variant expressions. We hereby made some experimentations to calculate the accuracies of some machine learning methods by making some changes in the face images such as a change in expressions, which at last needed for training and recognition identifiers. Our objective is to take the features of neutral facial expressions and add them with the other expressive face images like smiling, angry, sadness to improve the accuracy.
Erythrocyte Classification using Multi Layer Perceptron, Naïve Bayes Classifier, RBF Network and SVM
Authors:   Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia., Tyas Dyah Aruming , Hartati Sri ,   DepartmenttofCComputerrScienceeanddElectronics, Facultyyof Mathematicssand NaturalSSciences, UniversitassGadjahhMada, Yogyakarta, Indonesia, Harjoko Agus ,   Departmentt ofCComputer Scienceeand Electronics, FacultyyoffMathematicssanddNatural Sciences, Universitas Gadjah Mada, Yogyakarta,,Indonesia., Ratnaningsih Tri ,   Department of Clinical Pathology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Published: January 2020

Several diseases can be diagnosed based on the appearance of abnormal erythrocytes, among others anaemia and thalassemia. Process of examination peripheral blood smear manually is time-consuming and subjective. Currently, the process of examination peripheral blood smear by laboratory assistants can be assisted with digital image processing technology so that it can speed up the examination time and avoid subjectivity. This research begins with the process of microscopic image acquisition, then preprocessing, segmentation, feature extraction and classification. The microscopic image acquisition is carried out using an additional special camera on a microscope. In this study, we used peripheral blood smear of thalassemia patients and healthy individuals. We convert the RGB image to grayscale image and perform the median filtering in the preprocessing stage. In the segmentation stage, we used the watershed distance transform method. As a segmentation result, we got 7108 erythrocyte images consisting of nine types of erythrocytes. In feature extraction, we used shape, color and texture characteristics to represent erythrocytes. The combination of these three features is used as classifier’s input. One crucial stage in digital image processing technology is object classification. In this study, erythrocyte classification is done by comparing four types of the classifier to determine the best classifier performance in this case. Multi-Layer Perceptron (MLP), Naïve Bayes classifier, RBF Network, and SVM used as classifiers in this study. Experimental results showed that MLP got the highest performance with 89.6% accuracy, 89.3% precision and 89.6% recall. Furthermore SVM came in second place, followed by RBF Network and Naïve Bayes classifier.
Supervised Word Sense Disambiguation with Recurrent Neural Network Model
Authors:   Reseach Scholar, Department of Computer Engineering, Smt. Kashibai Navale College of Engineering, Pune (India)., Kokane Chandrakant D. , Babar Sachin D. ,   PhD Department of Computer Engineering, Sinhgad Institute of Technology, Lonavala, Pune (India).
Published: January 2020

Disambiguating words is a branch of artificial intelligence that deals with natural language processing. The dissatisfaction of the motive of the word deals with the polysemy of the ambiguous word, processing a single word in natural language, having two or more meanings where the corresponding context discriminates the meaning. Humans are intelligent enough to derive the meaning of the word because they are a biological neural network. Computers can be trained in such a way that they should function similarly to biological neural networks. There are four different suggested approaches to clutter as the knowledge-dependent approach and the machine learning based models which are further classified as supervised, semi-supervised and unpublished learning models. The purpose of this research is to improve better communication between computers and humans. The discussed model used a supervised learning approach with recurrent neural networks.
Detection of Diabetic Patterns using Supervised Learning
Authors:   Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India, Guleria Kalpna , Prasad Devendra ,   Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India, Kadyan Virender ,   Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Published: January 2020

World Health Organization’s (WHO) report 2018, on diabetes has reported that the number of diabetic cases has increased from one hundred eight million to four hundred twenty-two million from the year 1980. The fact sheet shows that there is a major increase in diabetic cases from 4.7% to 8.5% among adults (18 years of age). Major health hazards caused due to diabetes include kidney function failure, heart disease, blindness, stroke, and lower limb dismembering. This article applies supervised machine learning algorithms on the Pima Indian Diabetic dataset to explore various patterns of risks involved using predictive models. Predictive model construction is based upon supervised machine learning algorithms: Naïve Bayes, Decision Tree, Random Forest, Gradient Boosted Tree, and Tree Ensemble. Further, the analytical patterns about these predictive models have been presented based on various performance parameters which include accuracy, precision, recall, and F-measure.
Particle Optimization of Ceo2/Water Nanofluids in Flat Plate Solar Collector
Authors:   Department of Mechanical Engineering, Amity University Uttar Pradesh, Noida, India., Sharma Shubham , Tiwari Arun Kumar ,   Department of Mechanical Engineering, IET Lucknow India., Tiwari Sandeep ,   , Director KEC, Ghaziabad, India., Prakash Ravi ,   , Dean Faculty of Engineering & Technology, Amity University Uttar Pradesh ,Noida, India.
Published: January 2020

The present research focuses on the role of CeO2/water nanofluid for estimating the performance of flat plate solar collector in respect of energetic and exergetic performance. Based on our experimental findings on varying mass flow rate, the present analysis focuses on a wide range of concentrations to find optimum volume concentration for which thermal performance is maximum. CeO2/water nanofluid exhibits high thermal conductivity improvement (~41.7%at 1.5% volume concentration) and comparatively lower dynamic viscosity. Performance evaluation of flat plate collector is based on first law analysis and qualitative nature of energy flow based on second law analysis. Experiments indicate that for~1.0% particle volume concentration at a mass flow rate of 0.03 kg/s, maximum collector efficiency is obtained up to 57.1% instead of water as the base fluid. Exergetic efficiency observed 84.6%at optimum concentration (~1.0% particle volume) of nanofluid at0.01 kg/s flow rate.
A Performance Analysis on Swarm Drone Loco Positioning System for Time Difference of Arrival Protocol
Authors:   Department of Mechanical Engineering, De La Salle University, 2401 Taft Ave, Malate, Manila, 1004 Philippines,, Chu Timothy Scott , Chua Alvin ,   Department of Mechanical Engineering, De La Salle University, 2401 Taft Ave, Malate, Manila, 1004 Philippines,, Sybingco Edwin ,   Department of Electronics and Communications Engineering De La Salle University, 2401 Taft Ave, Manila, 1004 Philippines, Roque Ma. Antonette ,   Department of Electronics and Communications Engineering De La Salle University, 2401 Taft Ave, Manila, 1004 Philippines
Published: January 2020

There is an increasing application potential in swarm technology, accuracy in localization becomes a critical factor in the system in executing the desired task. As there are various localization techniques, this paper focuses on analyzing the performance of a particular radio localization technique called the Loco Positioning System operating on the Time Difference of Arrival protocol subjected to various setup configurations. The research starts with the design of various setup configurations are based on two independent parameters which are, number of anchors, and distance between anchors as they prominently affect the accuracy of the system. Position estimates are obtained by manually moving the Crazyflie equipped with a Tag within a grid system and the values are reflected through the PC client. The position estimates are then compared to the true values to obtain a relative error which is used to define the performance of the system. Data showed that operating on 4 anchors offers relatively low error and increasing the number of anchors to 8 significantly improves the accuracy of the system. Additionally, increasing the distance between anchors from 0.6 m to 2 m also improves the accuracy in the system. The obtained data offers a clear relationship between accuracy and the mentioned parameters, and a good combination of both parameters also affects the accuracy of the system. This paper offers both recommended applications and data which will aid users of the loco positioning system in determining the optimal setup based on their set of constraints.
Four Most Famous Cyber Attacks for Financial Gains
Authors:   College of Computers and Information Technology, Taif University, Saudi Arabia, Altwairqi Asalah F , AlZain Mohammed A. ,   College of Computers and Information Technology, Taif University, Saudi Arabia, Soh Ben ,   La Trobe University, Bundoora 3086, Australia, Masud Mehedi ,   College of Computers and Information Technology, Taif University, Saudi Arabia, Al-Amri Jehad ,   College of Computers and Information Technology, Taif University, Saudi Arabia
Published: January 2020

Cyber attacks are on the rise every day and pose a major threat to the Internet users. Cyber attackers are constantly capable of gaining hidden exposure at the moment and keeping a low profile. There is a need to carry out analyses on cyber attacks for educational purposes. In this paper we analyze four types of most famous cyber-attacks for financial gains: phishing attack, salami slice attack, ransomware attack, and cryptojacking attack. General Terms: Cyber attacks
Implementation of Stepped Frequency Modulation Pulse Compression on NI Suite
Authors:   Associate Professor, Department of ECE, MVJ college of Engineering, Bengaluru, India., Tamilarasi D. , Pavithra P. ,   Assistant Professor, Department of ECE,MVJ college of Engineering, Bengaluru, India., Ramesh P. ,   Associate Professor, Department of EEE ,CMR Institute of Technology, Bengaluru, India.
Published: January 2020

In Radars and Sonar, the pulse compression technique is used continuously to increase the range resolution, range detection and the signal-to noise ratio (SNR). This can be achieved by modulating the transmitted pulse and then correlating it to the received pulse with the transmitted signal. This transforms short pulse into long pulse and is used to increase long pulse bandwidth by some form of modulation such as linear frequency modulation (LFM), so that Range Resolution is not compromised. The proposed Stepped Frequency Modulation (SFM) is a common Pulse Compression Method, which is useful to increase the Radar Range Resolution without losing the capability of target detection. Step Frequency Continuous Wave (SFCW) is also one of the techniques used in the Pulse Compression Technique, where the return echo step is used to determine range and is used for different purposes. This type of setup is widely used in RADAR design and testing. This Paper proposes the implementation of various Modulation techniques such as LFM, SFM and SFCW for proposed Stepped frequency Modulation using NI suite hardware PXI system which has a configurable FPGA and RF front end to generate custom waveform in wide range of frequencies with bandwidth up to 1GHz design and testing.
Improved Task Scheduling using Effective Particle Swarm Optimization in Cloud Computing Environment
Authors:   CSE, Graphic Era Deemed to be University, Dehradun, India., Tomar Ankit , Pant Bhaskar ,   CSE, Graphic Era Deemed to be University, Dehradun, India, Tripathi Vikas ,   CSE, Graphic Era Deemed to be University, Dehradun, India., Pandey Priyank ,   CSE, Graphic Era Deemed to be University, Dehradun, India, Verma Kamal Kant ,   CSE, College of Engineering Roorkee, Roorkee India.
Published: January 2020

A vibrant on demand service of today’s era is cloud computing where one can utilize computer resources without indirect active management by user where one can use computing resources to achieve coherence in economic scale. Since cloud computing feel like Everything as a service so there should be highly scalable and reliable mechanisms to distribute the load evenly across the VMs evenly. Innumerable cloudlet mapping policies are presented in various research articles to achieve the high performance, better QOS and minimized task execution time but maximum are conventional approaches. No unconventional realistic scheduling algorithms is available which can schedule the tasks in heterogeneous manner. Since cloudlet scheduling is crucial metrics of cloud computing that has to be heightened by combining the different parameters. This paper tried to provide effectiveness and improvement in task scheduling using nature inspired Particle Swarm optimization (PSO) strategy. A powerful nature inspired load balancing mechanism is proposed in this paper which optimized makespan and throughput in environment of varying cloudlets and virtual machines results as compared to other conventional approaches. Proposed (EPSO) algorithm is with four scheduling policies namely FCFS, Round Robin (RR) and Shortest Job First (SJF) and get near twice good throughput percentage and minimized makespan in two different environments. Author used Cloud sim toolkit and some Open Source cloud packages to simulate the results of various scheduling components. Experimental results of various components are tested and simulated on java based CloudSim toolkit framework.
Micro Clustering Methodology for Document Objects using Deep Learning Techniques
Authors:   Department of Computer Engineering, Rajarambapu Institute of Technology, Rajaramnar, India, Mulla Amirkhan R. , Patil Sachin S. ,   Department of Computer Engineering, Rajarambapu Institute of Technology, Rajaramnar, India
Published: January 2020

Large data clustering and classification is a very challenging task in data mining. Various machine learning and deep learning systems have been proposed by many researchers on a different dataset. Data volume, data size and structure of data may affect the time complexity of the system. This paper described a new document object classification approach using deep learning (DL) and proposed a recurrent neural network (RNN) for classification with a micro-clustering approach.TF-IDF and a density-based approach are used to store the best features. The plane work used supervised learning method and it extracts features set called as BK of the desired classes. once the training part completed then proceeds to figure out the particular test instances with the help of the planned classification algorithm. Recurrent Neural Network categorized the particular test object according to their weights. The system can able to work on heterogeneous data set and generate the micro-clusters according to classified results. The system also carried out experimental analysis with classical machine learning algorithms. The proposed algorithm shows higher accuracy than the existing density-based approach on different data sets.
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Authors:   The Society For Chinese Humanities In Korea, . .
Published: January 2020

Adversative relation is an universal semantic category in human cognitive system.This study chooses Chinese and English which belong to two topological languages to contrast their adversative discourse markers in location, semantic relations and pragmatic functions.In these aspects, Chinese-English adversative discourse markers have more similarities than differences, however, they do not have one-to-one correspondence relation. Some adversative discourse markers are influenced by the language contact.Chinese-English adversative discourse markers share lots of common ground but also have their own characteristics.
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Authors:   The Society For Chinese Humanities In Korea, . .
Published: January 2020

In this paper, I probe into the forming process of the phonetic list of the different pronunciation in the book Yü-yen Tzŭ-erh Chi written by Thomas Francis Wade, and expound its inheritance and development relationship by comparing the content differences of three phonetic lists. It exactly provides an important clue and a reliable basis for revealing the source of the foreign words in Beijing dialect in the middle of the 19th century.
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Authors:   The Society For Chinese Humanities In Korea, . .
Published: January 2020

This paper is a study on the development of Chinese language education in kindergarten through actual survey on the present situation of Chinese language education in dream fruit kindergarten. First of all, the basic situation of Chinese education in dream fruit kindergarten was introduced, and Chinese educational game was reproduced in kindergarten according to card games, performance games, song and dance games, and outdoor game types. This research process presented the meaning of Chinese educational game making in kindergarten through analysis of Chinese educational game making class in dream fruit kindergarten. Based on theoretical inquiry and field visits of Chinese education in dream fruit kindergarten, the results of the study suggested a kindergarten Chinese educational game. First, it should provide a safe physical space for the kindergarten Chinese educational game-making class. Second, the institutional environment for supporting kindergarten Chinese gamification teaching should be improved. Third, the professionalism of game education for kindergarten Chinese teachers should be improved.
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Authors:   The Society For Chinese Humanities In Korea, . .
Published: January 2020

We need three types of knowledge to support reading science fiction at least. Ontology knowledge is not only the lever to mobilize the other two kinds of knowledge to participate in reading, but also the key to avoid misreading, including stylistic knowledge such as concept, type, elements and boundary determination. In terms of type, science fiction is divided into two categories , in addition to the theory of “soft and hard”, the eight types determined from the perspective of subject matter are generally recognized by researchers. “Scientific elements”, “strange environment”, “humanistic thinking” and “logical self-consistency” are necessary elements of science fictions. Together with the literary attributes and scientific boundaries of science fictions, they define the creative territory and reading vision of this kind of novels.
Two Lane Settlement of Sharia Economic Disputes Between Religious Court and National Sharia Arbitration Agency (BASYARNAS)
Authors: Minardi Anton
Published: January 2020

The development of the sharia economy, particularly in the banking sector, both domestically and abroad, is very encouraging. Because of his young age and lack of adequate understanding of various economic practices, Sharia opens the possibility of strife. When there is a Sharia economic dispute, there are two institutions that have the authority to handle the settlement, namely the Religious Court and BASYARNAS. Both institutions, both the religious court and BASYARNAS, have advantages and disadvantages in handling Sharia economic disputes. Openness must be developed from various parties who prefer Islamic shura (consensus) in determining everything and solving problems. Through Shura disputes can be resolved satisfactorily, can still maintain the privacy of the parties, the closer the relationship between the parties, the time can be shortened, the more cost-effective, and the relationship between the parties can be improved better. If you see that the resolution of economic disputes through BASYARNAS Syariah can be submitted before resolving disputes through the Religious Courts. Considering the new Shariah economic practices, it still needs to be disseminated in addition to the implementation of sharia economics, it also requires human resources and top-class facilities, as well as a complete constitutional and operational foundation.
Residents’ Perception of Importance and Satisfaction with Infrastructure in Selected Public Housing Estates in Osun State, Nigeria
Authors: Oyedele J. B. , Oyesode M. F.
Published: January 2020

This study examined residents’ level of satisfaction with the available infrastructure in Moremi, Oroki and Akoda Estates in Osun State, with a view to enhancing provision of infrastructure. Primary data was used for the study. Questionnaire was used to elicit information from the residents of the three selected public housing estates from the three senatorial districts in Osun State, each public housing estate representing one senatorial district. These public housing estates are under the portfolio of Osun State Property Development Corporation (OSPDC), Osogbo. The public estates include, Moremi Estate in Osun east senatorial district with 416 residential buildings, Oroki Estate in Osun central senatorial district with 816 residential buildings and Akoda estate in Osun West senatorial district with 46 residential buildings. These reflect a total of 1,278 residential buildings where systematic random sampling was adopted in selecting 20% of the residential buildings in the three selected public housing estates. A total of 255 residential buildings were selected, from which a resident was selected for questionnaire administration. The data collected were analyzed using relative importance index (RII) and Residents' Satisfaction Index (RSI) analysis. The result showed that the average Residents' Satisfaction Index (RSI) for the level of satisfaction derived from the infrastructure in the study area was 2.49 which showed that the residents were not satisfied. This study concluded that the residents were not deriving adequate satisfaction from the infrastructure available in the public housing estates. The study recommends that there is need to integrate residents’ preferred infrastructure into development policies: The residents’ preferred infrastructure identified in this study should be linked and integrated into the development policy designs for the estates.
O (im)possível do educar na cibercultura: reflexões psicanalíticas sobre educação, tecnologia e os desafios da docência na contemporaneidade
Authors: Alcântara Samuel , Lima Maria Celina Peixoto
Published: January 2020

No campo da educação frequentemente nos deparamos com o mal-estar docente diante dos novos dispositivos tecnológicos que adentram as salas de aula, seja pelas mãos dos alunos, seja pela utilização de novas tecnologias aplicadas ao contexto educacional. Portanto, este estudo é uma investigação teórico-reflexiva acerca dos desafios da educação, incluindo professores e alunos, diante da cibercultura e da hiperconectividade contemporânea. Este trabalho apresenta uma discussão sobre as inovações tecnológicas vigentes na sociedade e suas vinculações com as dinâmicas e práticas pedagógicas, com base em contribuições de estudos em educação, filosofia, sociologia e psicanálise. Nesse contexto, a psicanálise, ao abrir espaço para a construção de um saber e para a produção de efeitos de significação num sujeito que, com isso, poderia transcender o lugar que lhe cabe no social e apontar na direção de seu desejo, parece oferecer algumas pistas para se pensar a relação entre a educação e as novas tecnologias.