bluuebunny/crossref_metadata_2025 huggingface dataset:
Self-regulated Learning with Open and Distance Learning for Foundation of Applied Mathematics Course
Authors: Et. al. Nur Azila Yahya,
Published: April 2021

Foundation of Applied Mathematics is one of the mathematics servicing courses for Diploma of Applied Science programme in Universiti Teknologi MARA (UiTM), Malaysia. This course was previously taught in a physical classroom using direct confrontation. A few negative factors were found to contribute to the course’s failure rate: i) inadequate exercises, ii) poor study habit and iii) reluctance to consult the lecturer or opting to study with peers only. Due to the ongoing COVID-19 outbreak, the students are forced to do independent learning at home. Ascribable to this issue, the lecturers were inspired to investigate their students’ motivation and participation in this course, which associate to their self-regulated learning (SRL). This paper presents the implementation of open and distance learning (ODL) in teaching the subject of Foundation of Applied Mathematics. The ODL was intended to promote SRL for student, thereby increasing their motivation and participation in learning activities. At present, no literature has been found study on SRL in current ODL method, mainly for this course. Online questionnaires were collected at the end of March - July 2020 academic semester to investigate students’ perceptions on ODL and its effects to Self-Regulated Learning (SRL).  Descriptive analysis was used to analyze the data. The findings indicated that the level of agreement for ODL has positive contributions to the students’ SRL.
Innovative Approaches and Methods in Teaching Technical Subjects
Authors: Et. al. K.J. Rustamov,
Published: April 2021

: Relevance. In the learning process, it is necessary to pay attention, first of all, to those methods in which listeners identify themselves with the educational material, are included in the studied situation, are encouraged to take active actions, experience a state of success and accordingly motivate their behavior.

Aim. The purpose of our experimental study was to determine the possibility and effectiveness of using active and interactive forms in teaching technical disciplines.

Methods. Scientific methods were applied such as working with documents, comparative analysis, literature review, questionnaires, statistics, etc.

Results. In the results of experimental work, the indicators of students are given for three years in three subjects: theoretical mechanics, practical mechanics and modelling.

Conclusion. In the conclusion, conclusions are given on this topic.
Theoretical Framework Over Vivid Facets on Student’s Intention To Payback Education Loan in India
Authors: Et. al. Khusboo Srivastava,
Published: April 2021

Education loan is a magical solution to address the education financing crises. It bridges the gap between accessibility and sustainability but incidents of defaults in the repayment of education loan are on rise. The Present study covers various theories has been thoroughly analysed to understand the factors which influence the intention of student to repay the education loan. A comprehensive theoretical framework has been designed by reviewing various literatures on student intention. This structural framework encompasses - Attitude to repay or default of education loan, Integrity, Parental influence, awareness of loan agreement, Willingness to invest in educational plans, Student’s characteristics, Financial ability to pay and student’s priority from Theory of reasoned action, Theory of Planned behaviour, Theory of human capital and Theory of ability to pay. In this research study, all efforts have been made to determine the possible linkage between factors that influence student’s intention to pay or default the education loan.
Universality of Arthur Miller’s Death of a Salesman
Authors: Et. al. Dr.K. Ramesh,
Published: April 2021

This paper aims at analyzing Arthur Miller’s Death of a Salesman with a view to bring out its contemporary relevance. During its first performanace in 1949 the play shocked the American audience by its portrayal of the tragedy of the protagonist Willy Loman. The American audience were able to identify themselves with the protagonist and soon the tragedy of Willy Loman is empathised by the audience worldwide transcending spatio-temporal barriers. As put by June Schlueter, “He (Willy Loman) was a character who …encapsulated the spirit of the ordinary man whose work ethic, pride and self-deceptions did not admit defeat” (509). Willy commits suicide at the end of the play because of his inability to accept defeat. In fact, “Willy was the man everyone in the audience feared he would become, the man who unwittingly schooled us as a society on the need to accommodate our failures “ (509). Death of a Salesman will resonate with today’s audience because of its universal theme of an individual’s inability to realize his/her own dreams.
Entrepreneurship skills in the curriculum of a selected vocational college in Selangor
Authors: Et. al. Norlidah Alias,
Published: April 2021

Entrepreneurship is important in generating economic growth and social capital. Although entrepreneurship programs have been conducted in educational institutions, there seems to be uncertainty on components of entrepreneurship required in the curriculum. In addition, there has been very few successful entrepreneurs from these programmes. Further, there has been few studies onentrepreneurship in Malaysian Vocational Colleges and hence the implementation of programmes related to teaching entrepreneurship needs to be investigated to determine the skills required for entrepreneurship.A survey among 71 students and teachers at a premier vocational college to investigate current practices and EE components required was administered using a questionnaire and analysed using percentages and cross-tabulation while the open-ended responses were analysed according to emerging themes. The findings indicate that although EE was implemented in all colleges, the stakeholders required autonomy to design the curriculum according to the needs of the local community. Lack of resources and teacher preparedness were the main challenges in implementing EE. Marketing skills were required in most of the courses related to technology (Industrial Machinery Technology, Construction Technology and Computer and Networking System) whilesales management was important for Computer and Networking System, and Accountancy courses. Innovation was important for Electronic Technology. Further, some suggestions for the improvement of the vocational and technical courses in relation to entrepreneurship skills, were made.
Development of a Graphic Design Learning Module for the Deaf and Hard-of-Hearing (DHH) Students Based on Technology and Learning Style in Malaysian TVET institutions.
Authors: Et. al. Zainuddin Ibrahim,
Published: April 2021

Graphic Design is used in many industries and involves both the knowledge and skills in creating artefacts. Many Deaf and hard-of-hearing (DHH) students, especially in the Technical and Vocational Education and Training  (TVET) institutions are attracted in pursuing studies in this field, perhaps due to the visual nature of the course. However, learning graphic design is challenging for DHH students due to the technologies and teaching approach applied in these institutions. A module which was designed with experts, was implemented in a selected polytechnic which offered the graphic design course for the deaf and non-deaf students. The module used videos and other resources for the different learning styles, as well as a discussion platform on Padlet, and quizzes. An exploratory implementation study on 15 DHH students who volunteered to use the module was conducted. The students’ interactions were monitored and the results of their pre and post-tests during the implementation of the module was analysed to determine if the module was effective for learning. The findings indicate that students could use the module based on their learning styles and were active interacting on Padlet. The results of the pre and post-tests show a significant increase in scores, indicating the effectiveness of the module. Hence, the module has the potential to improve understanding in graphic design among DHH students. The findings have implications on the design of modules for DHH and special needs students. This is in line with TVET aspiration, which is to provide equal access to quality education for all. Further investigation should be done to determine whether the module could be used for other programs involving special needs students.
Current Advances In The Nanofiber (NF) Based Polymer Composites
Authors: Et.al Anamika CR
Published: April 2021

Nanofiber (NF) polymeric composites have received more interest nowadays. The majority of the study focuses on characterizing NF and comparing them to traditional composites in terms of mechanical behavior and usage efficiency. There are different varieties of NFs, each with unique possessions that influence whether or not they are used in particular industrial usage. Because of the natural source of these materials, they have an extensive variety of characteristics that are largely dependent on the gathering position and conditions, assembly it tough to choose the right fiber for precise usage. This study aims to map where every form of fiber was located in numerous assets by providing a detailed analysis of the characteristics of NF employed as composite-based materials reinforcement. Recent research on emerging forms of fibers was also discussed. A bibliometric analysis of NF composite applications is discussed. A future trend analysis of NF applications, as well as the essential innovations to extend their uses were also addressed.
Detection of Tumors From MRI Brain Images Using CNN With Extensive Augmentation
Authors: Et.al Y Mohana Roopa
Published: April 2021

Brain tumor is one of the most hazardous and lethal cancers which require effective detection of tumors for diagnosis, here medical image information is extremely essential. Mostly used images are Magnetic Resonance Image (MRI) images which provide a greater differentiation of assorted body soft tissues. In this paper we propose Deep learning architecture, specially the Convolutional Neural Network (CNN) along with augmentation techniques has been developed for Automatic classification of MRI images under study into tumor or no tumor with supervised learning. The proposed system has three stages at first, brain tumor images are re-sized(normalized) into equal size for effective training of model. Next, extensive data augmentation is employed, avoiding the lack of data problem when dealing with classification. Finally building CNN model for image classification.
Detection and analysis of Brain Tumor from MRI by Fully Convolutional Neural Network method
Authors: Et.al T. Sandhya Rani
Published: April 2021

Although it seems that the technology used in MRI is technologically advanced, we now use MRI to detect tumors based on human skills and knowledge. Although this method is proven to be accurate in most cases, sometimes the human eye does not work until it detects a slight deviation. In countries like India, there are no oncologists or neurologists. According to a report from 2018, the country is facing a shortage of health workers, with only 2,000 cancer specialists treating 10 million patients in rural areas, where the number of cancer specialists is very low, and its condition worse.
Effective Procedure to Predict Rainfall Conditions using Hybrid Machine Learning Strategies
Authors: Et.al S.Sakthivel
Published: April 2021

In the present information technology stream supports many natural disaster prediction schemes to save several people from disaster scenarios. In such case, rainfall prediction and analysis is the most important concern to take care as well as the prediction of high rainfall saves many individual's life and their assets. This kind of rainfall prediction schemes provides a facilitation to take respective precautions to avoid huge damages further. The rainfall predictions are categorized into two different variants such as Limited Period Rainfall Prediction and the long period Continuous Rainfall Prediction. Several past analysis and literatures provide accurate predictions for limited period rainfall but the major problem is to identify or predict the continuous long period rainfall. This kind of drawbacks leads many researchers to work on this domain and predict the rainfall status exactly for both limited period as well as long period continues rainfall. In this paper, a new hybrid machine learning strategy is implemented to predict the rainfall status exactly, in which the proposed methodology is named as Intense Neural Network Mining (INNM). This proposed approach of INNM analyze the rainfall prediction scenario based on two different machine learning logics such as Back Propagation Neural Network and the Rapid Miner. The general machine learning algorithms train the machine with respect to the dataset features and predict the result based on testing input. In this approach two different variants of machine learning principles are utilized to classify the resulting nature with better accuracy levels and cross-validations are providing best probabilistic results in outcome. And these two logics are integrated together to produce a new hybrid machine learning strategy to predict the rainfall status exactly and save human life against disasters. In this paper, a novel dataset is utilized from Regional Meteorological Centre Chennai to predict the rainfall summary in clear manner and the summarization of specific dataset is described on further sections. The proposed approach of INNM assures the resulting accuracy levels around 96.5% in prediction with lowest error ratio of 0.04% and the resulting portion of this paper provides a proper proof of this outcome in graphical manner.
Proposal for a Data Size Saving Office System That Can Be Stored on a Floppy Disk
Authors: Et.al Miki Sunakawa
Published: April 2021

With the development of computer software and applications, various types of recording media have emerged and evolved. This is a result of the rapid increase in the amount of data created by computers and the constant demand for large-capacity storage media. As large-capacity recording media have become available at low prices, the number of content production without being aware of the data capacity is increasing. Rather, content production often contains unnecessary features and effects for personal use. In this research, we will examine the feasibility of a practical system by carefully selecting the functions required for general use without excessive modification of effects. A floppy disk is used as the recording medium to limit the data size of the system.
Fabrication and characterization of nano structured honeycomb absorbers and thermal analyses on solar air heating collector
Authors: Et.al S.Selvakumar
Published: April 2021

Fabrication of nano structured absorber is mandatory for reaping the enhanced thermal performance of solar collectors. In this connection, the nano carbon and aluminium composite was coated on aluminium substrate, which was similar to the hexagon shaped honey comb, and the solar absorber was developed. It was characterized through X-ray Diffractometer (XRD), Fourier Transform Infrared (FTIR) spectrometer and UV–Visible spectrophotometer (UV). It was also thermally analyzed not only in outdoor conditions but also in stagnant conditions in solar air heating collector. The research results pertaining to characterization of solar absorber showed that the crystallite size was in nano ranges and the nano particles had face-centre cubic structure. The research results pertaining to characterization of solar absorber also showed that the nano composite had excellent absorption in UV and visible region. The research result related to thermal analysis in outdoor environment revealed that the enhancements of temperature on solar absorbers coated with carbon and aluminium nano composite in the mass ratio of 60:40, 70:30 and 80:20 were 23.5oC, 25.1oC and 24.4oC respectively. The research result related to thermal analysis in stagnation environment also revealed that the enhancements of temperature on glass cover, carbon and aluminium nano composite coated absorber and working fluid were 69.4oC, 110.6oC and 99.0oC respectively. On the basis of research outcomes, it could be concluded that nano carbon and aluminium composite coated solar absorber would be used for photo thermal applications due to their desirable optical and thermal properties. It could also be concluded that nano carbon and aluminium composite coated solar absorbers would be used in photo thermal appliances due to their positive impact on thermal performances.
Universal Measurement Matrix Design for Sparse and Co-Sparse Signal Recovery
Authors: Et.al Sudha Hanumanthu
Published: April 2021

Compressed Sensing (CS) avails mutual coherence metric to choose the measurement matrix that is incoherent with dictionary matrix. Random measurement matrices are incoherent with any dictionary, but their highly uncertain elements necessitate large storage and make hardware realization difficult. In this paper deterministic matrices are employed which greatly reduce memory space and computational complexity. To avoid the randomness completely, deterministic sub-sampling is done by choosing rows deterministically rather than randomly, so that matrix can be regenerated during reconstruction without storing it. Also matrices are generated by orthonormalization, which makes them highly incoherent with any dictionary basis. Random matrices like Gaussian, Bernoulli, semi-deterministic matrices like Toeplitz, Circulant and full-deterministic matrices like DFT, DCT, FZC-Circulant are compared. DFT matrix is found to be effective in terms of recovery error and recovery time for all the cases of signal sparsity and is applicable for signals that are sparse in any basis, hence universal.
Analysis of Cyber Threats in the Connection Section of the Control System and Countermeasures Required
Authors: Chun Yangha
Published: April 2021

In the past, the general practice for the control system network that manages and controls industrial facilities such as electric power, gas, oil, water, chemicals, automobiles, etc. was to install and operate this as an independent system, but over time the practice has gradually shifted toward the use of an open and standardized system. Until recently, most industrial control systems consisted of an independent network, and the possibility of cyber threat infringement was very low. As information storage media such as laptops or USB are connected to the control system for maintenance or management purposes, the possibility of cyber infringement is increasing. When the use of the control system's operational information increases due to beingVinked with the internal business system network or the Internet, countermeasures against external cyber threats must be provided.This paper analyzes and organizes the cyber threat factors that exist in the linking section connected to the industrial control system and other networks, examining domestic and foreign incidents of hacking of control systems to identify the vulnerabilities and security measures for each scenario in the control system network linkage section. Through this analysis, a method is suggested for establishing a control network that secures both availability and security, which are important in the control system, as well as the safe relay system in the configuration of the linkage between the control network and the business network, while addressing the vulnerabilities in the structure due to long-term use of the control system.This study analyzes cyber threat factors and real-life examples of infringements with the aim of providing approaches that will ensure industrial control systems can be operated safely and the risk of cyber hacking threats that occur in connection with other networks can be managed, and suggesting cyber security measures for the control system connection sections.
Study on Automatic Arrangement Algorithm for Tower Cranes with Applying Lifting Limit Axis
Authors: Et.al Kyeong-Tae Jeong
Published: April 2021

Recently construction projects are becoming more high-rise, and for this reason, efficient operation of tower crane is very important. Therefore, we conducted a study on the development of automatic arrangement algorithm for the efficient operation of tower crane. In this study, a new concept, the 'lifting limit axis' concept was applied to develop automatic arrangement (optimal arrangement) algorithm of tower crane. Through this process, the 'three-dimensional figure' was created and the research was carried out considering the weight of the material, the working radius of the tower crane, and the lifting capacity. In this study, we carried out the study in three dimensions to apply the concept of ‘lifting limit axis', which is different from the existing studies conducted in two dimensions. This is not simply a three-dimensional and two-dimensional difference. The reason for this is that the lifting work can be considered by applying the change in the lifting capacity according to the working radius of the tower crane in three dimensions. Therefore, it is a concept that enables highly efficient and stable lifting work. In this study, we developed an algorithm by applying this concept of 'lifting limit axis', which is divided into four steps. The first step is information input, the second step is identifying the intersection area where the tower crane can be arranged, the third step is to arrange the 'three-dimensional figure' and the last step is to select the minimum-cost simulation out of a number of simulation. This algorithm provides the basic guidelines for tower crane arrangement through the above process. In this study, we applied the new concept of 'lifting limit axis’. Therefore, continuous follow-up research is essential, and it is expected that this will lead to an efficient lifting plan of tower crane.
UAV Collision Detection Algorithm based on Formulafor Fast Calculation
Authors: Et.al Jung Kyu Park
Published: April 2021

Collision Avoidance System (CAS) is known as a pre-collision system or a forward collision warning system, and research has first begun as a vehicle safety system. In this paper, we propose an algorithm for collision detection of UAV. The proposed algorithm uses a mathematical method and detects the collision of the UAV by modeling it in a two-dimensional plane. Using the mathematical modeling method, it is possible to determine the collision location of the UAV in advance. Experiments were conducted to measure the performance and accuracy of the proposed algorithm. In the experiment, we proceeded assuming three environments and were able to detect an accurate collision when the UAV moved. By applying the algorithm proposed in the paper to CAS, many collision accidents can be prevented. The proposed algorithm detects collisions through mathematical calculations. In addition, the movement time of the UAV was modeled in a 2D environment to shorten the calculation time.
Research Article Properties of The Water-Based Paint Mixed With The Purple Bacteria
Authors: Et.al Byungcheol Choi
Published: April 2021

Recently, as carbon dioxide emission increases, global warming is rapidly progressing, and indoor air quality is also affected. In this study, a functional paint was prepared by mixing purple bacteria in an water-based paint, and carbon dioxide adsorption, alkali resistance, and impact resistance were tested. The mixing ratio of purple bacteria is set to 0, 5, 10, 15 (%), and the carbon dioxide adsorption experiment is divided into the case of no light and the case of light. As a result, In the absence of light, complete sealing is achieved as the carbon dioxide concentration in the empty chamber according to the mixing ratio of purple bacteria is considered to be kept constant as 100%. The carbon dioxide concentration of the paint without the purple bacteria was higher than that of the purple bacteria. In the case of light, the decrease of the carbon dioxide concentration tended to be more active than in the case of no light. There was no difference in alkali resistance and impact resistance when comparing the paint without the purple bacteria and the paint mixed with it. In addition, there was no difference even when the incorporation rate of purple bacteria increased. Finally, as for the viscosity, the faster the fall time of the paint, the lower the viscosity of the paint, and the drying time, the lower the viscosity of the paint, the longer the drying time. Therefore, It is believed that water-based paints mixed with purple bacteria can improve indoor air quality by adsorbing carbon dioxide.
A Study on The Minimum Exposure Dose For Image Formation In X-Ray Imaging of Extremity
Authors: Yu Sinyoung
Published: April 2021

Excellent performance of the digital detector can generate medical images at a lower dose. However, if a certain level of dose exposure of the sensor detector can generate an image to recognize it.

In this study, the exposure conditions of the forearm, femur, and ankle joint tests currently used in clinical trials were tested with lower doses. The resolution pattern was analyzed using the Image J program, and the results were obtained by analyzing the Interactive 3D Surface Plot. In addition, by measuring the surface dose and absorbed dose, the digital detector finds the minimum conditions to make an image, and also checks the effect of dose reduction.

The image of the obtained resolution pattern was analyzed by Plot profile using Image J program. It was confirmed that the gray value width decreased at the same pixel distance as the exposure conditions decreased. Even if the exposure conditions were lowered from step 1 to step 4, which is the standard condition of the forearm test, the resolution showed no difference at 1.4 Lp/mm.

In the Interactive 3D Surface Plot, as the range of the gray scale lowered the exposure condition, the shape of the surface contours gradually became blurred and the contrast of black and white shades decreased. The resolution from step 1 to step 3, which is the standard condition of the femur bone test, was 1.2 Lp/mm, indicating no difference. Even if the exposure conditions were lowered from step 1 to step 4, which is the standard condition for ankle examination, the resolution showed no difference at 1.4 Lp/mm.

It is thought that it is necessary to accumulate a lot of data by further subdividing the stage of exposure conditions according to the thickness in more areas.
Analysis Of Eddy Current Loss Of IPMSM According To The Material Of Permanent Magnet
Authors: Et.al Byeong-Chul Lee
Published: April 2021

In order to reach the performance of the permanent magnet embedded rotor, the choice of magnet is very important. It must be thermally stabilized, and at this point, discussion of eddy current losses is necessary.To proceed with this study, a permanent magnet embedded synchronous motor used in the compressor currently being designed was selected. To derive the eddy current losses in the neodymium-magnets, current density was calculated through the equation. The eddy current loss was mathematically derived using the magnetic conductivity and residual magnetic flux density. Finally, comparative verification was performed through finite element analysis simulation. In this paper, eddy current losses in a N series magnet are mathematically analyzed and we perform comparative verification through simulation using finite element analysis. The Br value indicating the residual magnetic flux density is the lowest in N30 series and the largestin the N48 series. In the case of using the N30 series, the amount of magnetic flux that can be generated is low, so in order to increase the same output, the electric field must be increased by drawing more current from the stator winding. That is, the torque can be further increased. However, since the magnetic flux density experienced by the permanent magnet also increases, eddy current loss that may occur in the  magnet eventually increases. There are also a method of using a split magnet to reduce eddy current losses. Inthe case of a permanent magnet holding a large residual magnetic flux density, the magnets loss is reduced, but there is a disadvantage that the price may be expensive. The losses in the permanent magnet are dissipated as heat. If the eddy current loss increases, the magnet demagnetizes, which in turn leads to a decrease in performance. In the selection of magnets, analysis of losses is essential.
Effects of Military Training Based on the Virtual Reality of Army Using AHP Method
Authors: Et.al Soo-Yun Kim
Published: April 2021

In order to enhance the effectiveness of military training, military education authorities are very interested in the use of virtual reality (VR), which is the core technology of the 4th industrial revolution. The purpose of this paper is to analyze effects of the army’s VR-based military training. For this purpose, we draw evaluation factors of AHP through related literature and Delphi technique and divide them into two levels: equipment effects and learning effects. The sub-factors of each factors consist that equipment effects are reality, safety, and availability, and learning effects are interest, immersion, and understanding. The questionnaire for evaluation factors was composed of pairwise comparison on 9-point scales. The 14 experts who had experience of teaching the VR-based training participated in a pairwise comparison survey. As a result of this study, the top six factors determined are as follows: interest, reality, immersion, understanding, availability, and safety. The VR-based training showed higher values in term of Interest (6.3), reality (5.2), immersion (3.5), and understanding (3.1) than existing training method of video contents (VC)-based training. On the other hand, availability (0.9) and safety (0.9) were lower. It is expected that the result of this study will be used as the basic data for the military’s VR-based training policy in the future.
Improve a Human Resource Allocation Guide in Construction Management based on Case study
Authors: Et.al Seongmi Kang
Published: April 2021

The object of this paper is to analyze difference Human Resource allocation Guide, and suggest improved Human Resource allocation Guide to meet the owner’s needs. This paper analyzed the present situation of Human Resource allocation Guide by announcement and law through case study of construction management service about public office awarded by Public Procurement Service (PPS) from 2011 to 2013, and considered proper Human Resource allocation Guide in design process, during and after construction process. Based on the findings of current study, the following problems were identified; difference between announcement and legal Human Resource allocation, Human Resource allocation problem during the whole phase of project, and Human Resource allocation problem of work types. For the improvement, this paper suggests specifying minimum Human Resource requirement in RFP (Require For Proposal) so that it is available to manage flexible Human Resource allocation, proper Human Resource allocation Guide, in design process, to reduce the workload in construction process, and Human Resource allocation in construction process for appropriate compensation package. This study is anticipated to help the next following study to improve inefficient Human Resource allocation Guide.
Development of a Cable Damage Detection Deep Learning Method based on Acceleration Response of Cable-Stayed Bridge
Authors: Et.al Park Gi-Hun
Published: April 2021

The purpose of this thesis was to select a cable-stayed bridge to which external force may cause damage as the subject, to develop a damage detection deep learning method capable of detecting cable damage, and to test and verify the developed damage detection deep learning method. The damage detection method was developed as a system that utilizes the acceleration response of a structure measured for maintenance purposes. To extract information capable of identifying the damage locations from among the measured acceleration responses, a CNN ID was used to develop the damage detection deep learning method. The developed damage detection deep learning method was developed in a way not independently arranging 1 machine learning model per each measuring point and finally predicting the damage location based on the decision-making results collected from each machine learning model. The developed damage detection deep learning method performed the learning per each machine learning model by utilizing the acceleration response of a structure acquired based on the preliminary damage test. Finally, the damage detection deep learning method that completed the learning verified the cable damage location detection performance by utilizing the data acquired based on the cable-stayed bridge damage test. As a result, it was confirmed that the developed damage detection deep learning method predicted the damage location of a cable-stayed bridge at an average accuracy of 89%. In the current research, only the cable-stayed bridge of the Seohaegyo Bridge was studied, but in the improved study, the research will be conducted on other bridges and damage assessment will be conducted on all cables.
A Study on The Fully Enclosed Housing Of Interior Permanent Magnet Synchronous Motor
Authors: Et.al Ho-Joon Lee
Published: April 2021

Approximately 2.5 billion won can be saved every year by replacing existing induction motors, which are traction motors for urban railway vehicles, with permanent magnet motors. This paper presents a study on the structural design of a completely enclosed motor to commercialize an interior permanent-magnet synchronous motor (IPMSM) for the traction of urban railway vehicles. The proposed solution provides protection from an inflow of dust and magnetic powder into the rotor that can deteriorate the motor performance and cause burnout. In addition, unless it is a water-cooled or oil-cooled structure, cooling of an electric motor used in medium and large-sized equipment is not easily accomplished. However, completely enclosed motors are vulnerable to overheating; therefore, research into housing design is required to provide cooling. Additionally, the permissible current density through the stator winding must be considered in the design to prevent the occurrence of thermal demagnetization of permanent magnets. Furthermore, IPMSMs require a separate driver for operation and speed controls for a wide range of operating conditions such as rail traction. Thus, a study has been conducted on IPMSMs and other related driver and control technologies, and their suitability has been validated through performance tests.
Associated Factors Of Metabolic Syndrome And The Role Of Oral Health Among 50 And Older Adults: from the 6th KNHANES
Authors: Kwon Moon-Hee
Published: April 2021

The study on relationship between metabolic syndrome and oral health, is rare. We investigated to find out the correlation of metabolic syndrome and oral health. We investigated to find out the correlation of metabolic- syndrome and oral health with the data from the 6th Korea- National- Health and Nutrition- Examination- Survey. This is the cross-sectional designed study. 2433 subjects (aged 50 ≤) were included. Metabolic- syndrome was defined as NCEP-ATP (National- Cholesterol- Education- Program-Adult- Treatment- Panel Ⅲ). To analyze influencing factors of metabolic syndrome, multi-variable- logistic- regression was used. Our results showed that gender(male) (OR 1.86; 95%CI: 1.27-2.72; p<.05) and not taking dietary supplements (OR 1.74; 95%CI: 1.22-2.48; p<.05) factors were the most influencing factors of metabolic syndrome. And then, presence of stress(OR1.59; 95%CI: 1.28-1.98; p<.05), lowest education level(elementary)(OR1.48; 95%CI: 0.98-2.21; p=.05),  and oral health(periodontitis) (OR1.39; 95%CI: 1.09-1.78; p<.05) factors were showed as the next strong factors of metabolic syndrome in order.  While chewing ability was not related with metabolic syndrome. We highlighted on the impact of oral health in metabolic syndrome including chewing difficulty as well as periodontitis. And to prevent metabolic syndrome cause of serious disability and lowering quality of life, we tried to find out the influencing factors of metabolic syndrome considering of this study with diverse view point such as adding the dietary supplements as dietary habit, stress as psychological value, and sedentary time as health-related factors. The government and public health associates should do urgently preparing the policies and strategies focusing on gender disparities, dietary supplements and oral health to prevent metabolic syndrome among ageing population.
Pothole Region Extraction Based On Similarity Evaluation Scale Classification Using Image Processing
Authors: Et.al Min-Jeong Kim
Published: April 2021

Pavement deterioration and abnormal climate induced by global warming lead to a constant rise in the number of potholes. Accordingly, the loss cost for maintenance and accidents also increases. Therefore, it is necessary to develop a method of classifying pavement potholes and detecting their locations. This study proposes the pothole region extraction based on similarity evaluation scale classification using image processing. The proposed technique sets up a classification threshold appropriately by considering the structure, brightness, and other factors of the grayscale-converted image through SSIM (Structural Similarity Index Measure). It binarizes porthole images classified according to the threshold, and then extracts pothole regions through the threshold based segmentation. A conventional image classification method utilizes the rules found in objects or the label selected by a user. The proposed method can take into account detailed factors by comparing image similarity in the unit of pixel. According to the performance evaluation, the proposed classification method’s F1-score is 0.83, and its accuracy of pothole region extraction is 0.851. Therefore, with the proposed technique, it is possible to make classification in consideration of similarity between images. In addition, the proposed method makes it possible to detect the regions similar to actual potholes accurately.
Structural, Opticaland Morphological Properties Of Zn And Mg Co-Doped V2O5 Thin Filmnanostructures
Authors: Et. al. Sandesh Kumar Rai,
Published: April 2021

The research study reveals metallic co-doping of Zinc(Zn) and Magnesium (Mg) on vanadium pentoxide(V2O5) thin ﬁlm nanostructures by spray pyrolysis deposition technique. The studyfindings have been made into how the morphological, structural and optical properties of the materials change for the different co-doping percentage of 1%,3%,5%10% of Zn-Mg. X-ray diffraction (XRD)clearly showsan orthorhombic crystalline structure with polycrystalline nature.The dopantZn and Mginfused into the V2O5 matrixand is confirmed by EDAX images. A field emission scan electron microscope was used to examine surface morphology whichreveals that grain structure has beenmodified by increasing the doping content. It is evident from theatomic force microscopy (AFM) images that the effect of Zn and Mg on V2O5 thin filmshave enhanced surface roughness.The transmittance and energy bandgap (Eg) of the film found to be decreased with an increase in doping concentration whereas absorbance varieswith doping levels.The research findings suggest that the Zn-Mg co-doped V2O5 thin films could be a potential source for energy,optical and sensor-based device applications.
Commognitive Analysis Of Students' Errors In Solving High Order Thinking Skills Problems
Authors: Et. al. Lili Supardi,
Published: April 2021

This study aims to describe the commognitive analysis of students' errors in solving High order thinking skills problems. The problem of this study is that students have difficulty of solving mathematical problems because students do not build their own knowledge of mathematical concepts but tend to memorize concepts so that when students solve math problems students often make mistakes and do not find solutions to solve these problems. Students also taught themselves that math is difficult. This type of research is a qualitative description. The research subjects were three grade X students of Senior High school 1 Pamekasan. The instruments used in this study were mathematical problem seets and semi-structured interviews. The results showed that students experienced faults in 1) word use (mistake writting mathematical symbol and not consisstent in writting naming. the factors are hasty, inaccurate, not understanding the questions, incomplete writing is known, and asked, not understanding the material.); 2) Visual mediator (mistakes in drawing or illustrating the problem. Student is not using visual mediators, some students use visual mediators but are still wrong and use it,); 3) Narrative (not writing the formula but writing the results directly. Student mistakes also occur because students do not know the strategy that will be used to solve them, while the students' mistakes made at this stage are: students are wrong in writing the formula definition sine and wrong for not writing the formula.); 4) Routine (inaccurate in arithmetic operations so that the final answer is wrong. The mistakes of some students in general in doing routine are the students doing wrong calculations, wrong in substituting values or numbers that are known in the formula.). With this research, teachers can find out where the difficulties and misconceptions of students are in doing it so that it becomes new learning for students to improve learning outcomes and minimize errors.
Sentiment Analysis Of Twitter Data By Using Deep Learning And Machine Learning
Authors: Et. al. Prof. Manisha Sachin Dabade,
Published: April 2021

In today’s world, social media is viral and easily accessible. The Social media sites like Twitter, Facebook, Tumblr, etc. are a primary and valuable source of information.Twitter is a micro-blogging platform, and it provides an enormous amount of data. Such type of information can use for different sentiment analysis applications such as reviews, predictions, elections, marketing, etc. It is one of the most popular sites where peoples write tweets, retweets, and interact daily. Monitoring and analyzing these tweets give valuable feedback to users. Due to this data's large size, sentiment analysis is using to analyze this data without going through millions of tweets manually. Any user writes their reviews about different products, topics, or events on Twitter, called tweets and retweets. People also use emojis such as happy, sad, and neutral in expressing their emotions, so these sites contain expansive volumes of unprocessed data called raw data. The main goal of this research is to recognize the algorithms by using Machine Learning Classifiers. The study intends to categorize Fine-grain sentiments within Tweets of Vaccination (89974 tweets) through machine learning and a deep learning approach. The study takes consideration of both labeled and unlabeled data. It also detects emojis from tweets using machine learning libraries like Textblob, Vadar, Fast text, Flair, Genism, spaCy, and NLTK.
Algorithm On Complete Graph And Their Folding
Authors: Et. al. H. Ahmed,
Published: April 2021

In this paper, introduce algorithm on complete graph K4, when the graph weighted, and discusses the folding of algorithm graph of weighted complete graph K4, the folding at some cases such as folding of the edges as all cases, and folding of the vertices, some theorems related to these result are obtained and prove of this theorems are obtained, also some life applications are introduced.
Attack Prediction By Using Greedy Algorithm For Diminishing The Drop And Delay In Wireless Sensor Networks
Authors: Et. al. Dr. B.Shadaksharappa,
Published: April 2021

The essential constraint of the internet is that forwarding the data packets of data among the restricted and trustworthy data nodes. If the receiver node is attacker node then it'll drop the data rather than forwarding the data to ensuing neighbor node. Therefore, efficient and secure data transmission is extremely necessary within the network data transmission. Each router node within the network can accept the data packets up to its buffer size only. Once the queue value reached the buffer threshold value then congestion can occur at the node. Once congestion happens then it would lose the data packets. By sending the data packets to the next neighbour node this problem will be resolved. This congestion will be handled by the Fully Distributed Congestion Control FDCC and Cooperative and Memory Efficient Token Bucket (CMTB) algorithms. Because the data is transmitted to the next neighbour node predicting the node behavior is extremely necessary because it is an attacker or the conventional transmitter node because it has to transmit the efficient data securely to the destination node. In this paper, the node behavior will be predicted by analyzing the trace file. The simulation results show that this proposed method would provide a lot of security in data transmission. The WSN comprises a group of sensor nodes that are disseminated on the network. These sensor nodes initially exchange their data packets to the near nodes to send the data packets to the target node. During the transmission of these data packets some data packets drop may also happen inside the network. This packet drop should be kept up as low as feasible for correct data transmission to the target node or destination node. This algorithm highlights the routes with high link quality, low packet delay and with low packet drop. Simulation results show that this proposed algorithm can provide the most effective path for transmitting the data to the destination meanwhile it reduces the packet drop and packet delay.
On The Anti-Synchronization Of Fractional-Order Chaotic And Hyperchaotic Systems Via Modified Adaptive Sliding-Mode Control
Authors: Et. al. A .Othman Almatroud,
Published: April 2021

This paper investigates the anti–synchronization problem between two different fractional-order chaotic and hyperchaotic systems using the modified adaptive sliding mode control technique in the presence of uncertain system parameters. To construct the proposed scheme, a simple sliding surface is first designed. Then, the modified adaptive sliding-mode controller is derived to guarantee the occurrence of sliding motion. Based on the Lyapunov stability theory, the adaptive controllers with corresponding parameter update laws are designed such that the different chaotic and hyperchaotic systems can be anti–synchronized asymptotically. Finally, numerical simulations are presented to demonstrate the efficiency of the proposed anti–synchronization scheme.
Roger 3450 Vs RF4 Martials - Based Frequency And Pattern Reconfigurable Rectangular Patch Slot Antennas For RFID Applications
Authors: Et. al. Salah Mohmad Alsadiq Aboghsesa,
Published: April 2021

Rectangular Patch Slot Antennas RPSA are getting becoming more likable and popular for practice in wireless implementations such as RFID applications especially in the UHF band thanks to its low-profile structure. This kind of antenna is able to deliver large communication distances but this antenna coverage is very weak which is part of the main drawbacks of these antennas. In this paper, Rectangular Patch Slot Antenna RPSA with different slots has been designed and simulated to be suitable for RFID applications. Circular polarized CP antenna that has been designed to use feed structure with vertical ground encircling a radiating component. The feeding method to feed this antenna is coaxial probe. The paper will concentration on both substrate materials Roger 4350 and FR4 Glass-Epoxy material to model and simulate the designs. The other factor of the design is the patch antenna will cut at the four truncated corners to enhance the antenna gain which will affect considerably the operating frequency. This paper aims to show and find the best feed point area that has an exceptional antenna return loss (S11) and high gain. S11 describe the power reflected from the antenna, which is known as the reflection coefficient S11 must be ≤ -10dB. The design and simulation results of RPSA has been done by high frequency simulation system (HFSS 13.0).