bluuebunny/crossref_metadata_2025 huggingface dataset:
Medical Text Entity Recognition Based on Deep Learning
Authors: Zhang Linjun , Wu Hao
Published: February 2021

Named entity recognition is a very important basic task in natural language processing, and a basic technology for many high-level applications of natural language processing. Traditional methods to solve named entity recognition are mainly based on rules and statistics. The rule-based method requires strong linguistic knowledge and is poor in generality. Based on the above background, the purpose of this paper is to recognize medical text entities based on deep learning. This paper proposes a new LSTM framework that integrates dual-channel and sentence-level reading control gates. In the input part, double channels are added to obtain two kinds of semantic information from static word vectors and fine-tuned word vectors. Then, the read-in control gate is integrated inside the neural network to determine the propagation of the sentence representation vector. Finally, the CRF model is used to fully consider the dependency relationship between the types of context words when outputting tags. The F1 value of 89.49% was achieved on the BioCreative II GM corpus. In summary, this article applies two deep learning methods to improve the performance of biomedical named entity recognition tasks. Finally, without adding any artificial features and post-processing operations, this article has achieved 89.94% F1 value on the BioCreative II GM corpus, and it is 0.89% higher than the F1 value of the current best system.
Optimization of E-Commerce Logistics Distribution Path Algorithm under the Background of Big Data
Authors: Yu Feng , Zhou Yingjie
Published: February 2021

In recent years, online shopping has become a major development trend of shopping. The traditional e-commerce logistics distribution mode has played e-commerce by taking advantage of the advantages of the distribution path algorithm. However, with the increase of the order quantity, the previous path optimization algorithm is no longer efficient. This paper makes an in-depth investigation on the main problems existing in China’s e-commerce logistics. Through the analysis of the survey results, we can see that there are mainly problems such as low degree of data application and imperfect function of logistics information platform. Aiming at these problems, this paper optimizes the logistics distribution routing algorithm according to the actual demand. Through the establishment of three-dimensional constraint model, the problem of low efficiency in the traditional model is effectively improved. In contrast with the genetic algorithm, the distribution mileage of the optimization algorithm is reduced by more than 25% compared with the genetic algorithm, which improves the comprehensive performance of the model. Constraint model established in this paper makes up for the shortcomings of the current e-commerce logistics distribution path algorithm to a certain extent, and makes a contribution to the development of China’s e-commerce logistics distribution field.
Research on the Application of College Basketball Course Based on the Concept of Network Experiential Teaching
Authors: Wei Wenting , Wei Jinrui , Fang Wenxuan
Published: February 2021

With the strategy of invigorating the country through science and education and strengthening the country, the relevant education departments in various parts of our country gradually put emphasis on talent education. Basketball is one of the physical education courses in Colleges and universities. At present, the teaching methods and skills of basketball in Colleges and universities are relatively simple. Experiential teaching is a new modern teaching mode. Based on this, this paper puts forward to apply the network experience teaching concept to the efficient basketball course, improve the teaching quality of college basketball teaching with the help of network-based experiential teaching, and cultivate high-quality talents. In this paper, we set up the experimental class and the control class. The experimental class uses the network experience teaching to carry on the university basketball curriculum, while the control class uses the current physical education teaching for college basketball curriculum. At the end of the semester, through comparative analysis, it shows that the college basketball course designed in this paper has played the subjectivity of students. In the final examination, more than half of the students have achieved good results. Experiential learning enhances students’ interest in learning and improves their comprehensive quality in an all-round way.
An Improved Iris Recognition Method Based on Wavelet Packet Transform
Authors: Wang Yonghui , Zheng Haoran
Published: February 2021

Wavelet packet decomposition transformation is an extension of wavelet transformation, which can achieve more refined decomposition and get more wavelet packet subgraphs. In order to improve the recognition accuracy of iris, an improved iris recognition algorithm based on wavelet packet transform is proposed. First locate and normalize the inner and outer edges of the iris, then obtain the wavelet packet subgraphs through wavelet packet decomposition, calculate the coefficients of each subgraphs to obtain the iris feature vectors, and then calculate the Hamming distances of the corresponding feature vectors of the two iris images, according to different subgraphs. The calculated coefficients are identified by the weighted Hamming distance classifier.
An effort to train the biological computation skill and teach animal phenetic taxonomy to pre-service biology teacher
Authors: Rahayu D A , Ambarwati R , Faizah U
Published: February 2021

Computational biology skills for studying phenetic taxonomy is inseparable from learning outcomes of Animal Systematics Course. Pre-service biology teachers are expected to have computational biology skills, which can support further study in bioinformatics. This study was aimed to train computational biology skills and evaluate learning outcomes of phenetic taxonomy material. Phenetic taxonomy practicum was held online and assignments were given as mini-projects. Indicators of biological computation skills were evaluated using ntsys 2.2 software and analysis of resulting dendograms based on synapomorphy, automorphy, and apomorphy. Respondents consisted of three classes contained 84 students who programmed Animal Systematics Course. Computational biology skills were quantified based on self-assessment questionnaire while learning outcomes were evaluated based on mini-project assessment. Data were analyzed using descriptive quantitative method. Results indicated that mastery of computational biology for phenetic taxonomy was very good, as supported by students’ ability to use Ntsys software of 86.04%, dendogram analysis of 83.33% or categorized as good. In addition, learning outcomes of phenetic taxonomy were classified as good with average score of 77.7 ± 4.17. Evaluation of qualitative assessment data showed that computational biology skills supports the development of higher-order thinking skills (data synthesis, analysis, and evaluation) of pre-service biology teachers.
Development of ILAU based on PBL-STEM model with formative assessment as an opportunity to improve problem solving skills in heat and temperature topics
Authors: Alfiana R , Parno  , Yogihati C I
Published: February 2021

Independent Learning Activity Unit (ILAU) is a learning media that can develop independent learning strategies. However, instructional media that are based on contextual issues, practice aspects of STEM, and use independent learning strategies have not been developed. The purpose of this study was to develop and test the feasibility of ILAU based on Problem Based Learning (PBL)-STEM with formative assessment so that it was feasible to function as an opportunity to improve problem solving skills in heat and temperature topics for XIth grade of senior high school. The research design used Borg & Gall’s research and development model which consisted of three main steps: (1) initial study, (2) product development; (3) product testing. The instruments in this study were: (1) Learning Implementation Plan validation questionnaire; (2) ILAU validation questionnaire; (3) ILAU readability test questionnaire. The results of expert and practitioner validation showed that Learning Implementation Plan developed had average feasibility percentage of 100%, and ILAU had average feasibility percentage of 99%. The results of the readability test by 33 students showed that ILAU had average readability percentage of 93%. Thus, it can be concluded that Learning Implementation Plan and ILAU developed based on the PBL-STEM model with Formative Assessment have very feasible category so they can be used to improve problem solving skills.
Effect of metacognition and self-efficacy on scientific achievement by prospective science teachers of Madura through student creativity
Authors: Yasir M , Wulandari A Y R , Wahyudi I
Published: February 2021

The low student achievement is influenced by several factors, including metacognition, self-efficacy, and creativity in learning. This study aims to determine how much effect of metacognition and self-efficacy toward scientific achievement through student creativity of prospective science teachers of Madura. The research was carried out on all student in Natural Science Education Study Program, University of Trunojoyo Madura with a total population of 390 students. This study is Ex Post Facto, data of metacognition, self-efficacy, and student creativity collected through questionnaires and scientific achievement using documentation. Data were analyzed using SEM analysis techniques. The results showed that regulation of metacognition and self-efficacy positive and significant impact on the student creativity with each estimated value γ11=0.265 and = γ12= 0.356 positively with α = 0.05, > p = 0.01, and student creativity has positive and significant effect on scientific achievement with the value B21= 3.109. Metacognition knowledge and self-efficacy does not directly influence student achievement, but through regulation of metacognition and self-efficacy through student creativity together shown to result in a significant and positive effect on scientific achievement of prospective science teachers of Madura.
The Effectiveness of reflective-inquiry learning model to improve preservice-teachers’ critical thinking ability viewed from cognitive style
Authors: Verawati N N S P , Hikmawati  , Prayogi S
Published: February 2021

This study aims to explore the effectiveness of Reflective-Inquiry Learning (RIL) model to improve the critical thinking ability of preservice-teachers viewed from cognitive style. Quasi-experimental research using one sample group was conducted in this study. The research sample consisted of 24 (twenty-four) preservice-teachers consisting of 14 (fourteen) males and 10 (ten) females. They are preservice-teachers (PTs) in the physics education study program – Universitas Pendidikan Mandalika (Undikma). Measurement of cognitive style using GEFT to classify the sample group into the field dependent (FD) and field independent (FI) cognitive style. Pre-test and post-test to measure the critical thinking ability of preservice-teachers. Data were analysed descriptively and statistically, where the n-gain test, normality test, and t-test (pair-t test) were conducted. The results of the study have shown that the RIL model is effective in improving the critical thinking ability of preservice-teachers in both the field dependent (FD) and field independent (FI) cognitive style. The results of further studies are described in this article.
The impact of learning management system implementation on students’ understanding of mechanics concepts
Authors: Gunawan G , Harjono A , Suranti N M Y , Herayanti L , Imran I
Published: February 2021

The Learning management system (LMS) is an effective model of learning for solving the teaching problems. Effective learning will help students achieve better understanding of the concept. This article discusses the use of LMS in teaching mechanics and its effect on student understanding. This quasi-experiment research used one group post-test design. The sample used was 21 students from one of the higher educations in Mataram, Indonesia. The instrument used was the conceptual understanding test in multiple choices. The test consists of 30 questions which are divided into three mechanics concepts, namely Newton’s Laws of Motion, Work and Energy, and Simple Harmonic Motion. Each data was analyzed using simple statistics. The findings showed that the use of LMS had a positive impact on students’ understanding of each topic of mechanics concepts. The highest average score on the topic of Work and Energy. The lowest average score is on Newton’s Laws of Motion. LMS is an alternative platform for developing students’ understanding of concepts in each cognitive aspect.
Choosing dy or dx? Students’ Preference for constructing integral form on Area-related problem
Authors: Hidayat D , Kohar A W , Artiono R
Published: February 2021

Students are often found dilemmatic when constructing an integral form of a calculus problem. This is a descriptive-explorative study aiming at investigating college students’ preference for constructing integral form of area-related problem. Data were collected from 63 responses of college students who were taking an Integral Calculus course at a university in Surabaya on an integral problem related to area between curves containing two regions. Data were analysed by categorizing students’ responses regarding the succesfulness of responses and preference regarding symbol notations : upper and lower limit, integrand, and variable of integration (dy or dx). The results showed that for the first region, 71% of students could successful to construct integral form, while 24% of them were unsuccesful, and 5% students did not give any responses. Meanwhile, for the second region, 10% of students could successful to construct integral form, while 78% of students unsuccesful, and 13% students did not give any responses. The preference of students in choosing dy or dx as part of integral notation was explained and the students’ misconceptions that arise in constructing the integral notation were also discussed.
Understanding definite integral concepts of prospective teachers through actions and processes based on gender difference
Authors: Langi E L , Juniati  , Abadi
Published: February 2021

This research was a qualitative research which aimed at describing the understanding of the integral concept of prospective teachers through actions and processes in terms of gender difference. The research subjects were one female student and one male student of Mathematics Education study program. Data were collected through assignment sheets and followed by interviews. After data were analyzed, it was found that the action of the female subject in determining the definite integral was certainly shown by completing the integral task procedurally using the appropriate formula. At the action stage, in determining the total area female subject directly used the integral formula regardless the form and location of the region formed by a curve. The action of male subject in determining the integral was certainly similar to the female subject. It was shown by calculating the integral using the appropriate formula. For the task of determining the total area under the curve, male subject first described the form of the curve and paid attention to the position of the region with respect tox-axis. At the process stage, female subject explained the steps to complete the integral. When explaining how to calculate the total area under the curve, the female subject explained the solution steps regardless the position of the region. Meanwhile, the process stage of male subject was shown by explaining the steps and revealing the reasons for using the formula he used after identifying the form of the given integral. The male subject gave attention to the position of the region with respect tox-axis when calculating the region.
Analysis of Temperature and Relative Humidity towards the Dispersion of CoVid-19 in Indonesia
Authors: Hariyono E , Rahmadhani E A , Kusumawardhani K D
Published: February 2021

The research purpose is to analyze how the temperature and humidity affect the development of CoVid-19 in Indonesia. The data used is secondary data from BMKG and official CoVid-19 data based taken from May 2-8, 2020. The data analysis techniques use the violin plots and the jitter plots with the assistance of software R. Based on the research can conclude that the temperature has a positive correlation of 0.3 and that humidity has a positive correlation of 0.2. That means the temperature and humidity are not the main factors in the development of CoVid-19 in Indonesia. High temperatures and humidity do not cause the virus to grow slower.
The Effectiveness of Blended Learning in Chemistry Creative Media Course
Authors: Yonata B , Novita D
Published: February 2021

This study has purpose to figure out the effectiveness blended learning activity in creative media course through blended learning for education chemistry students year 2017. The effectiveness declared from learning outcome and students’ response. The study was held in odd semester 2019-2020 for 15 meetings. After the instrument of blended learning (Students worksheets, visual and video/audio media) showed validity then learning activity was conducted from August to December 2019. There were combination of online and offline in teaching-learning activity for 15 meetings. Discussion, Assignments and its submission activities was using vi learn for 4 meetings, and the rest of meetings were used offline. As final project, students in team presented chemistry creative media in internal exhibition. The theme of exhibition is physical chemistry creative media. The media assessed by lecturers and students (other years or other study programs) who attended the exhibition. The data of learning outcome were obtained from final project score and assignments. While the data of students’ response were gained after the exhibition was held. The result of this study showed 100% students could achieve mastery learning outcome and student responded this course in very good criteria. It can be concluded that chemistry creative media course effective to be conducted by using blended learning activity.
The Understanding and Awareness of First-Year Undergraduate Physics Students in Astronomical Phenomena: A Response of Penumbral Lunar Eclipses on June 5th, 2020
Authors: Deta U A , Fadila D , Lestari N A , Yantidewi M , Nurlailiyah A , Prahani B K
Published: February 2021

A penumbral lunar eclipse phenomenon occurs when Earth’s outer shadow falls on the Moon’s face. This astronomical phenomenon is easy to miss because sunlight still illuminates most of the Moon. In this research, we want to describe the first-year undergraduate physics students’ understanding and awareness of Penumbral Lunar Eclipses, especially on June 5th, 2020. The study using qualitative research with a questionnaire and an interview. The subject of the course is 100 participants from first-year undergraduate physics students. Physics students’ answers are categorized into four levels, namely Dissatisfaction, Intelligible, Plausibility, and Fruitfulness. From the results, it can be concluded that physics students know with the Dissatisfaction category related to the phenomenon of the penumbra lunar eclipse. Otherwise, for knowledge about the strawberry full moon eclipse, students learn the intelligible and dissatisfaction types. It recommended that physics students increase their understanding of the occurrence of a lunar eclipse by understanding scientific processing skills to reinforce their opinion.
Constructive metacognition activities through students’ communication skills in solving PISA based on personality
Authors: Santoso H A , Istiqomah N R
Published: February 2021

This study aims to describe the constructive metacognition activity through students’ communication skills in solving PISA’s problems. The subjects in this study were 4 junior high school students. Three types of metacognitive activity functions used in this study are awareness, regulation, and evaluation. Data collection instruments used were adaptations of PISA problems with space and shape content. Data were analyzed through the communication skills of students verbally and in writing, after that they got three descriptions about the constructive metacognition activity patterns of each student. It was found that the constructive metacognition activity pattern of each student was very unique based on their personality. From this study, we suggest further studies to conduct a deeper assessment of the metacognitive components that arise in the communication skills of the subject.
Ultrasound assisted interesterification for biodiesel production from palm oil and methyl acetate: Optimization using RSM
Authors: Ansori Ansori , Mahfud Mahfud
Published: February 2021

High energy demand in the industrial world and pollution problems caused by the use of fossil fuels causes the need for the latest innovations that will replace the use of non-renewable energy. One of them is the replacement of diesel fuel with biodiesel. At present biodiesel production uses a transesterification reaction which produces a side product in the form of glycerol. However, the presence of glycerol is considered waste and has no economic value so a separation process is needed. So to eliminate the by-product separation process, a new route is used. This route is called interesterification, using methyl acetate instead of methanol which later produces triacetin as a by-product. Triacetin is recognized as an additive in biodiesel which functions as an anti- knocking in diesel engines. In this research, an interesterification study was carried out by ultrasound and a potassium methoxide catalyst was used to increase the reaction rate and the yield of biodiesel. The operating parameters used include the reactant molar ratio of 1:3; 1:6 and 1:9, catalyst concentration 0.5%; 1.0%; and 1.5%, and reaction times 5, 10, and 15 minutes. The parameter optimization is carried out by the central composite design (CCD) method to reduce the number of experiments needed and also to evaluate various variables and their interactions. The optimal operating conditions are the molar ratio of methyl acetate to palm oil of 8.95, catalyst concentration of 1.44%, and interesterification time of 10.03 minutes can produce the yield of biodiesel of 99.66%.
Alleviating NB conditional independence using Multi-stage variable selection(MSVS): Banking customer dataset application
Authors: Siva Subramanian R , Prabha D , Aswini J , Maheswari B , Anita M
Published: February 2021

Customer research is one of the important aspects of understanding customer behavior patterns with business enterprises and predicate how consumer satisfaction is achieved. Customer analysis brings out various underlying information about the customer patterns with enterprises and analysis decision helps to make better marketing strategies to improve the customer lifetime and also enhance the business profit. To perform effective customer analysis in this research Naive Bayes an ML algorithm is applied. The efficiency of NB comes from its conditional independence assumption and the violation of NB assumption results in poor prediction. But in most real-time customer datasets, the NB assumption is violated due to the presence of correlated, irrelevant, and noisy variables. To improve NB prediction with these customer customers, in this research Multi-Stage Variable Selection(MSVS) is proposed to select the relevant variables from the customer dataset which helps to predicate the customer patterns wisely. The proposed approach consists of two stages in selecting the relevant variable subset from the customer datasets. Further variable subset obtained from the proposed MSVS approach is experimented with using the NB algorithm and the results obtained are compared using the wrapper and filter approaches. From the results, it clearly shows the proposed MSVS approach performs better in selecting the variable subset and improves the NB prediction in customer analysis efficiency compare to wrapper and filter approaches. Further, the proposed approach works efficiently in time and less computational compare to wrapper and filter approaches.
Survey on Forecasting the vulnerability of Covid 19 in Tamil Nadu
Authors: Ananthi P. , Jabeen Begum S. , Latha Jothi V. , Kayalvili S. , Gokulraj S.
Published: February 2021

Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this project, linear regression (LR) a Machine Learning model is used to forecast the number of patients will get the infection in near future. By simulating SIRD model, the infection spread and recovery rate of the disease in a geographic region can be predicted. The vulnerability of the disease is checked by observing the transmission of disease over a period. In addition to this many info graphic models and graphs are created for easy understanding of data to get more insights about the disease. However, these prediction models enable us to make quick response of pandemic and to bring a conclusion to the disease. INDEX TERMS: Covid 19, data science, machine learning, prediction, analysis, pandemic, recovery and infection.
A Context-free Grammar based Association Rule Mining Technique for Network Dataset
Authors: Saranyadevi S , Murugeswari R , Bathrinath S
Published: February 2021

Among various data mining concepts like prediction, clustering, classification, association and outlier discovery, association is a useful technique to extract the interesting relations among data items effectively. Association technique is applied in a number of applications like marketing, education, chemical, bioinformatics, computational linguistics and etc. The important purpose of association is to provide useful information of buying preferences of customers in supermarket in order to increase the sales opportunity, which is called as market- basket analysis. Till now there are many algorithms were developed, but the usage of formal grammars in association rule mining (ARM) is a latest technique to mine required data by means of grammars. In this paper ARM is performed using Context –free Grammar (CFG) – (ARM – Grammar) and the experiments are conducted on MATLAB 2017 software using network dataset, KDDCUP’99. Experimental outcomes prove that the proposed ARM – Grammar is effective than the traditional ARM approach.
Analyzing ELearning platform reviews using Sentimental Evaluation with SVM Classifier
Authors: Muralidharan R , Kanagasabapathy T , Vijai Ganesh R P
Published: February 2021

In today’s scenario, the participation of eLearning courses is rapidly increasing among users, especially during post-pandemic situation. Due to a hike in the need of eLearning, there is a sharp increase in emerging of online courses. Not only the academic people (students and teachers), but others also interested in the online courses, irrespective of their ages. Since numerous eLearning platforms are mushrooming, it is mandatory to follow various standard techniques to evaluate the quality of these courses. It would be more adaptable, if the evaluation techniques are made based on the Course users feedback. These feedback of the users contain more valuable information which helps in constructive decision making. The satisfactions and criticisms of the courses are shared through opinion of the registered user. Due to enormous amount of web reviews available for a course, it is extremely time-consuming and difficult to manually analyze the review and come to a conclusive decision. Reviews contain course feature specific factual information along with the opinion statements which may be positive or negative. The text reviews obtained from most of the webpages of the online courses feedback or comments section, are found to be unstructured and inconclusive. Analyzing and extracting the actual opinion throughout the reviews manually is very difficult. So, an automated technique is needed to evaluate the course based on the features of the courses, which results in attaining a decision. The Aspect based opinion mining is such a methodology which describes the important aspects of each opinion and classify them on their polarity.
Covid-19 Pandemic Spread as Growth Factor using Forecasting and SIR Models
Authors: Vennela Gudimella Sai , Kumar Priyanka
Published: February 2021

The novel Coronavirus outbreak began in Wuhan which is located in China in December 2019 and after the outbreak immediately the virus has spread across the globe. Millions of people across the globe are infected and many more have died. World Health Organization (WHO) declared this virus as global emergency. In this work, main goal is to analyse the spread of virus in India that to particularly for Guntur District within India in order to settle the situation quickly. In order to analyse the spread of virus three types of forecasting methods have been compared and the SIR model is used to predict the number of Susceptible, Infected and Recovered persons for the Guntur district which is located in Andhra State.
Enhancing the performance of social spider optimization with neighbourhood attraction algorithm
Authors: Tamilarasi K , Gogulkumar M , Velusamy K
Published: February 2021

Data clustering is a well-known problem in order to identify the inherent structures and extracting the useful information. Recently, social spider optimization (SSO) algorithm is applied to solve a clustering problem. But, it may fall into premature convergence due to find improper nearest spiders in order to achieve the global solution. In this research paper, the neighbourhood attraction (NA) method is used to enhance the performance of the SSO clustering algorithm. In the experimental results, the proposed NA+SSO clustering method is producing better performance when compared with other conventional clustering algorithm.
IoT based detection of bore-well unclosed holes using automated drone operated cameras in a remote area
Authors: RenugaDevi S , Dharshini M , Gayathri K , Gopalakrishnan B
Published: February 2021

In the current era, most of the accidents occur due to the borewells that are left unclosed and many children got trapped in them. Those borewells remain as a hell to many children. These borewells have played endlessly in most of the innocent lives. This process is very difficult to rescue the children away from the borewells. To avoid this critical situation, we must prevent the children from falling in borewells. Here, we came up with an idea to take precaution in order to save many infant lives. The main objective of the system is to fix a Drone camera in a remote area to find the borewells that remain uncovered. After finding the borewells, we have to find whether it is a normal hole or a depth pothole. So to detect the size of a hole, we attached an ultrasonic sensor on the bottom of the drone for identifying the potholes and also to measure the height and depth of a bore well respectively. If the depth and height of the bore well is large, the information will be send to the respected officials to properly close the bore well accordingly. These details will be updated to the cloud for maintaining the information in timeline. Hence, we can save number of lives of children from falling in borewells.
Hybrid Genetic Algorithm and Simulated Annealing for Clustering Microarray Gene Expression data
Authors: Pandi M , Sivakumar T , Senthil Madasamy N , Sadhasivam N
Published: February 2021

Gene expression is the process by which information in gene is used to create proteins. The gene expression studies generate large amount of data. These data, referred to as the gene expression matrix, represent the expression levels for thousands of genes recorded at a few time instances. A typical microarray experiment involves the hybridization of an mRNA molecule to the DNA template from which it is originated. Many DNA samples are used to construct an array. The amount of mRNA bound to each site on the array indicates the expression level of the various genes. This number may run in thousands. All the data is collected and a profile is generated for gene expression in the cell. Clustering is a process of partitioning a set of meaningful subclasses called clusters. Clustering is a key step in the analysis of gene expression data. Genetic Algorithms are a family of computational models inspired by evolution. The searching capability of genetic algorithms is exploited in order to search for appropriate cluster center in feature space such that a similarity metric of resulting clusters is optimized. The chromosome which are represented as strings of real numbers, encode the centers of fixed number of clusters. The experiment results are demonstrated on real data sets and the performance of GA is evaluated in comparison with the state-of-the art algorithm K-Means with use of internal validation criteria.
A Cluster-based Approach for Finding Domain wise Experts in Community Question Answering System
Authors: Menaha R , Jayanthi VE , Krishnaraj N , Praveen sundra kumar N
Published: February 2021

Community Question Answering (CQA) systems is an emerging web-based information service. CQA enables web users to get precise answers to questions from experts of the specific domain.CQA is used in wide areas such as biomedicine, information technology, tourism, etc. This paper focused on finding experts in community question answering system using unsupervised machine learning technique. Our Proposed system consists of three phases namely i) Clustering tags ii) Determining Experts for the unanswered questions iii) Finding experts for the given Question. By doing the tag analysis process, identified similar tags in a particular domain, and formed a cluster. By doing question analysis, we found the unanswered questions in each domain and identified the experts. For the given question, suggest the expert by doing pattern matching technique. The results section proves that our system predicts the experts for the given question with good accuracy.
Design of an expert system architecture: An overview
Authors: Janjanam Durgaprasad , Ganesh Bharathi , Manjunatha L
Published: February 2021

An area of Artificial intelligence (AI) that can claim a large measure of responsibility for the current heightened AI awareness is Knowledge Based Expert System (KBES), computer programs that embody human expertise. KBES specifically enable the computer to assist in solving ill-structured and non-deterministic problems such as design activities including synthesis, evaluation, modeling and decision-making process. The paper explains the role of Backward Chaining method, Forward Chaining method, Rule-Value method as three major methods involved in solving these problems to differentiate the Knowledge Based Expert System programming from normal programming. The development of an expert system requires a tool that will provide for better means of knowledge acquisition, inference mechanism and user interface. This paper brings out an overview of Expert System, a systematic study involving a critical analysis of the Expert System (ES) development, specifying its requirements. Further it highlights the features of Expert System and its implementation.
Smart maintenance of continuous duty cycle motors
Authors: Benin Pratap C , Samson Kenny , Shine Let G , Chandrasekaran G
Published: February 2021

Maintenance is a considerable part in the efficient working of the continuous duty cycle motor, especially in the motors used in day-to-day usage. It is practically impossible to do routine manual checkups to ensure the motor is safe and working conditions. The only relevant solution is to automate the routine checkups of the motor. This work’s primary objective is to develop an automated solution to the task of regular maintenance of the continuous duty motor. Here a wireless module using Arduino is integrated with the motor to wirelessly oil the motor. The proposed system can be used for regular oiling and machine maintenance without having the hassle of going to the site. Using this machine, the employee can check the working condition of the machine and turn ON and OFF the oiling system for the required duration. The proposed system prototype working has been tested and verified.
An Image Encryption Algorithm with Hermite Chaotic Polynomials and Scan Pattern
Authors: Sivakumar T. , Pandi M. , Senthil Madasamy N. , Bharathi R.
Published: February 2021

In today’s digital world, massive amount of sensitive information is being generated in the form of image and further it is shared via Internet. Maintaining the confidentiality of these data has become a major issue due to security vulnerability present in the network and transmission media. Image encryption algorithms are developed by various researchers to permit only authorized users to access and view sensitive images. This paper presents a novel image encryption scheme based on Hermite polynomials chaos function. First, random key stream is generated by using Hermite polynomial with different initial and incremental values of the variables. Next, the original image is scrambled with scan pattern to rearrange the pixels position. The scrambled image is XORed with the random key stream to get the encrypted image. The proposed method is experimented and observed that it is efficient and confirms the confusion and diffusion properties of a secure image encryption method. Large key space, low relation between the pixels of encrypted image, and sensitivity to initial seed value of the key are the strength of the proposed image encryption method.
Next Generation Digital Forensic Investigation Model (NGDFIM) - Enhanced, Time Reducing and Comprehensive Framework
Authors: Thakar Akash A , Kumar Kapil , Patel Baldev
Published: February 2021

Rapid technological advancement can have a substantial impact on the process of digital forensic investigation and presents numerous challenges to the investigator. With these challenges, it is imperative to have a standard framework for the digital forensic investigation to be implemented within most incidents. This induces a great stride to formulate a nonspecific framework that may be applied to most digital investigation procedures. The Next Generation Digital Forensic Investigation Model (NGDFIM) formalizes the framework to facilitates the practitioners in the investigation process. This framework could potentially generate more evidence during the incidence response through on-site triage as compared to conventional investigations process. Moreover, the framework diminishes the analysis time and provides the suspect with privacy protection by incorporating custom content imaging.
An element-wise generalized singular value decomposition (GSVD) based image encryption algorithm
Authors: Suresh Babu V , Vijaykumar V R , Gopalakrishnan T
Published: February 2021

The image encryption algorithm aids a secure data transmission. In our proposed method, we use the generalized singular value decomposition (GSVD) as the encryption tool. Here, the secret image will be decomposed with respect to the key and generates the ciphered text. Further, to improve its security, the Arnold transforms and the XOR operation is used respectively. The region-wise applied GSVD reduce the time consumption of the conventional image encryption methods. Here, the GSVD decomposition is element-wise, so, the algorithm is more robust. The generated cipher text is transmitted and the key is generated with the combination of the key used to decompose the secret image pixel in GSVD module, the Arnold transform key and the XOR operator key. In receiver end, the ciphered image is synthesized with the key received in a separate channel. This proposed model is lossless encryption method.
Robust transmission of medical records using dual watermarking and optimization algorithm
Authors: Amrit Preetam , Anand Ashima , Kumar Sushil , Singh AK
Published: February 2021

Nowadays, security of medical records is an important issue for tele-health system. Motivated by importance of such critical issue, we propose a robust watermarking method in the DWT-SVD-optimization domain. To solve the security issue, traditional watermarking schemes uses manual scaling factor to manage balance between imperceptibility, robustness and capacity. However, selection of manual scaling factor loses their optimize trade-off between these important parameters of watermarking. The suggested scheme encourages protection of medical data via techniques of dual watermarking and optimization scheme. In our scheme, the data owner imperceptibly embeds the dual watermarks in the medical cover image for extra level of security. Here, appropriate optimization schemes are used to find the scaling factor for embedding purpose. Further, the performance of this scheme is examined and compared. Moreover, the patient text data is coded via hamming code before inserting in to the cover so that bit error rate can be avoided or eliminated, if any. We show that the suggested scheme not only offers the high imperceptible but also robust for various attacks. Compared with existing schemes, our work offers more robustness while imperceptible and good capacity at the same time.
Design Of Interlock High Voltage Bay Transformer 150/20 kV System Simulator
Authors: Dinata Seflahir , Asroni Muchlis , Bakhri Syaiful
Published: February 2021

Simulator is a tool or means that is needed in learning to replace the role of a real system or equipment. The simulator providing a solution for repetitive operation of equipment. This is not possible on the actual equipment such as in a high voltage transformer of electrical distribution system. The purpose of this study was to design a simulator of a 150/20 kV transformer bay interlock system using a PLC as a control device and computer monitor as a display (human machine interface). In this simulator there are 15 states to describe the interlock system between the circuit breaker and the disconnecting switch both on the 150 kV side and on the 20 kV side. Interlock system design using state diagram method. PLC Ladder diagrams are written with CX-programmer software and HMI programming using CX-Supervisor software. The validity test of the simulator is done by using event validity techniques. The design results show that the overall interlock system runs as a whole with the percentage of validity is 100 percent or with a validity index 1, so it can be concluded that the simulator of the 150/20 kV transformer bay interlock system can be used as a learning tool to replace the real system.
Neutronics analysis of PWR core using DRAGON, TRIVAC, and DONJON computer codes
Authors: Sukarno D H
Published: February 2021

Operation of NPP has potential of nuclear hazard and radiation hazard. Therefore, all efforts are absolutely needed to be performed to ensure the safety of NPP operation. Neutronics analysis has important role in ensuring that safety aspect. In neutronics analysis, computer codes that could well simulate the neutronics condition in reactor core are needed. In this paper, neutronics analysis of 2652 MWt PWR core has been performed using DRAGON, TRIVAC, and DONJON computer codes. The purpose of simulation is to conduct the calculation of neutronics parameters which are important for safety. The neutronics analyses was conducted in two stages, i.e. cell calculation using DRAGON and full core calculation using TRIVAC and DONJON. For verification, the comparation between the calculation results of DRAGON, TRIVAC, and DONJON, and those of other computer codes results found in literature was performed. The effective multiplication factors calculated by DONJON for conditions where all control rods were fully up and fully down, and for ‘one stuck rod’ condition were 1.23399, 0.69705, and 0.91340, respectively. The core maximum power and average power were found to be 21166.1 kW and 16891.7 kW, respectively, with the power peaking factor of 1.2530. The maximum and average neutron fluxes in the core were 4.019038E+14 n/cm2s and 9.035312E+13 n/cm2s, respectively. The results of fuel cell calculation using DRAGON and the full core calculation using TRIVAC and DONJON have the differences of 4% and 1.3%, respectively, compared to the calculation results using other computer codes. This research shows that DRAGON, TRIVAC, and DONJON have capabilities to perform the calculation of neutronics parameters for NPP, specifically PWR type.
Day and Night Thermal Mass Performance Studies on Wetland Settlement in Palembang
Authors: Triyuly Wienty , Triyadi Sugeng , Wonorahardjo Surjamanto
Published: February 2021

The phenomenon of urban heat island was affected by the thermal mass of the area. The massive development of settlement in the wetland of Palembang had changed the natural thermal mass composition. This paper discussed the effect of the settlement development in the urban thermal environment of the wetland of Palembang. We measured the effect of building, pavement, water body and vegetation factors in the day and night air temperature of the settlement area. Direct field measurement was done using the wet and dry thermometer, anemometer and globe thermometer for 3x24 hours. The result showed that there were differences in day and night air temperature in the area with different thermal mass composition. It was also affected by wind direction and weather conditions. We concluded that the day and night temperature balance of the area could be control by the composition of thermal mass in the settlement area.
Fuzzy logic-based power control system of a supercritical-pressure light water fast reactor
Authors: Sutanto  , Lestari Erpina Dwi , Puspitasari Ayu Jati
Published: February 2021

Supercritical-pressure light water fast reactor is one of the current concepts of the Generation IV reactors which have significant improvement on the efficiency, safety and economy. A change of power to flow ratio leads to a change of the outlet coolant temperature in second. The temperature deviation must be suppressed as small as possible to keep the integrity of the reactor structures, like the reactor outlet nozzles, main steam line, etc. The plant dynamics analysis was carried out by giving perturbations of power to flow ratio, and then its influence on the reactor power and outlet coolant temperature were observed. A fuzzy logic-based power control system was designed and applied to the plant to compensate the effects of the perturbations. The control’s parameters, like the member functions of fuzzification were optimized to satisfy the criteria of allowable outlet coolant temperature deviation and stability. The power could be controlled stably by the optimized control design and the criterion of the outlet coolant temperature deviation is satisfied against perturbations of power to flow ratio.