Reviewerly/exHarmony huggingface dataset:
PENGENALAN SIMBOL LINGKUNGAN DAN KESEHATAN DI SDN 1 POMAHAN KECAMATAN PULUNG KABUPATEN PONOROGO

The school is the best place to introduce children to useful knowledge where they will later become adults. Therefore schools, especially education at the elementary level need to be supported and facilitated as well as possible so as to facilitate students in learning. SDN 1 Pomahan in the Krajan Hamlet stands on a very large area. However, we observed that there were still very few facilities provided for both external and internal activities of students in learning and knowing knowledge. Related externally, which includes the school environment. We see that there is still a lack of symbolic information that should be more available to be presented and introduced to students. Symbols such as preserving the environment, and how to maintain health are very important to be introduced early. Especially children of their age, like to play together but incidentally they rarely care about the environment when it's cool. As well as maintaining health after playing, most children of their age do not yet know the steps to clean good and right hands and so on.
An Efficient Approach on Data Security with Cloud Computing Environment: A Comprehensive Research

this paper discusses the data security in cloud computing. It is a study of data inthe cloud and aspects related to it concerning security. As we all know Cloud computing is anemerging domain and security of the data must be protected over the network. Cloudcomputing is used by many of the organizations for storing the huge amount of data on theclouds. Therefore, there is need to secure the data which may in the form of text, audio, video,etc. There are numerous algorithms designed by the researchers for securing the data on thecloud.The paper will go in to details of data protection methods and approaches used throughout theworld to ensure maximum data protection by reducing risks and threats.
Asthma prediction using Machine Learning

Patient telemonitoring brings about a conglomeration of huge measures of data about quiet illness direction. Notwithstanding, the possible utilization of this data for the early expectation of asthma in grown-ups has not been methodically assessed. The point of this examination was to investigate the information for building AI calculations that anticipate asthma before they happen. The investigation dataset involved 278847 records presented by grown-up asthma patients. Prescient displaying included readiness of preparing informational indexes, prescient component choice, and assessment of coming about classifiers. AI classifiers are utilized to foster these prescient models; including Random Forest, Logistic Regression, Decision Tree, and Naive Bayes strategy. Of the multitude of classifiers carried out, strategic relapse classifier brought about the most elevated expectation precision. Our investigation showed that AI methods have huge potential in creating customized choice help for ongoing illness telemonitoring frameworks. Future examinations may profit with a far-reaching prescient system that consolidates information with different elements influencing the probability of creating asthma. Approaches carried out for cutting edge asthma expectations might be stretched out to early mediation of persistent ailments in patients
Personalized Recommendation And Prediction System For Web Service Using Machine Learning Technique

The dynamic and time-aware Quality of Service attributes are forecasted for the recommendation of efficient web services. The forecasting of QoS attributes are attained primarily by statistical techniques and optimization algorithms. These approaches lack in retrieving the optimized results and the absence of exploitation nature in optimization algorithms results in ineffective performance. To overcome the drawbacks, the optimization and machine learning technique is introduced in this research work. The genetic algorithm (GA) with high exploration ability and grey wolf optimization (GWO) algorithm with high exploitation ability is introduced to acquire the optimized QoS attributes. The performance of the GA-GWO is enriched by minimizing the over fitting issue. The machine learning based gradient boosting algorithm is incorporated for solving the over fitting problem. The proposed GA-GWO is highly efficient in acquiring the QoS attributes, which are prominent in managing and modelling the web services. The recommendation of personalized web services and attaining QoS is investigated by the performance of the proposed GA-GWO algorithm and it outperforms the other QoS attribute retrieving approaches.
Credit Card Fraud Detection on Skewed Data using Machine Learning Techniques

The fraud associated with credit card transaction is increasing at an alarming rate and consequently resulting in huge financial loss for both the cardholders and concerned financial institutions. Most datasets for real-life problems such as this are usuallyimbalanced, which makes the machine learning model not robust for training purposes. Therefore, this research aimed to detect 100% of the fraudulent transactions while minimizing the incorrect classifications by first, balancing the data using under sampling technique and then developing classification models using different machine learning algorithms such as Logistic regression, Random forest, K nearest neighbor and Decision tree classifiers. The performance of the models are evaluated based on accuracy, precision and recall and the results indicated that Random Forest recorded the highest accuracy, precision and recall of 95.19%, 97.94%, and 0.9226 respectively compared to the other three (3) algorithms.
Blockchain in Supply Chain Management

A supply chain is the connected network of all the entities involved in the manufacture and final distribution of a product or service. It starts with the delivery of raw materials from a supplier to a manufacturer and ends with the delivery of the finished product or service to the customer. Supply chain management is the management of the flow of goods and services in order to cut excess costs and better meet customer expectations. Although supply chains have existed for a long time, the way they are managed is not as efficient as expected. The use of blockchains in supply chain management offers a number of advantages. A blockchain is a constantly growing ledger which keeps a permanent record of all the transactions that have taken place, in a secure, chronological and immutable way and can be shared by all the entities in the supply chain. The combination of supply chain management and blockchain adds trust in partners' interactions, reduces paperwork, increases security as well as transparency of records and transactions. Such an enhancement, indeed cuts excess costs and better meets customer expectations.
Comparative Study Of Load Balancing Algorithms For Cloud Computing

One of the emerging technology in large-scale computing is Cloud computing where data processed from large data centers. One of the big challenges with this is to do balancing in the load between all the nodes. It is also required for proper utilization and of resources and evenly distributing the work. High user satisfaction and efficient resource utilization can be ensured by effective allocation and sharing of available computing resources. Load balancing is required to achieve this goal in high data centric and huge network. Load balancing problem is considered as an optimization problem and a good load balancing algorithm can helps to get some of the advantages like scalability enabling, bottleneck avoidance, minimizing resource consumption etc. Many researches have been proposed many algorithms to solve the load balancing problems in Cloud Environment. This paper is aims to analyze and compare some of the load balancing algorithms in the cloud computing scenario.
Existence Of Ψ - Bounded Solutions for Lyapunov Systems

In this research paper, the researchers present an indispensable and adequate condition for the existence of Ψ-bounded solution for the linear non- homogeneous Lyapunov matrix differential system on R. Besides, it is given a result in connection with the asymptotic behaviour of the Ψ- bounded solutions of a linear non- homogeneous Lyapunov matrix differential equation.
New Trends and Design of User Centric Services in the Mahatma Gandhi University Library: A Study

University Libraries play vital role in education, learning, teaching and research, and acting as centre of learning in the higher education sector. University libraries have been acting as per the directions of the University Grants Commission and the parent university authorities subject to the basic norms of the concerned universities. User centric systems and services are basically meant for providing quality of services to its users and to empowerment of their leaning capacity. The services offered by the libraries differ from one another and based on the nature of the university and its discipline they depend. This paper attempts to bring out the new trends and changes introduced in the M G University by adopting new techniques and technologies in delivering user centric library services in changing digital era. This paper also attempts to study and evaluate the procedure of design of user centric services .
Research on Weekly Load Characteristics and Physical Effect of Physical Education Training Based on Data Mining Technology

in Sports Training, the Training Load is the Most Important Factor That Affects the Sports Performance.Reasonable Arrangement of Training Means, Load Amount and Load Intensity Before the Competition is the Keyand Basic Factor to Cause Athletes' Body Function Changes, Obtain Good Training Effect and Improve SportsPerformance. in This Study, Based on Data Mining Technology, Using the Methods of Literature Review,Questionnaire Survey and Mathematical Statistics, the Weekly Load Characteristics and Physical Effects ofPhysical Education and Training Are Comprehensively Studied, Aiming At Sorting out and Analyzing theCharacteristics and Laws of Players' Annual Periodic Physical Training Load, and Providing Theoretical andQuantitative Indicators for the Formulation and Implementation of the Annual Periodic Physical Training Load ofBasketball Teams in China in the Future. the Results Show That Using Data Mining Technology to Analyze theApplication of Athletes' Healthy Sports Behavior Makes Sports Related Data Mining More Accurate and StatisticalAnalysis More Reliable.
Sistem Pendukung Keputusan Pemilihan Guru Berprestasi Dengan Metode Simple Additive Weighting di SMKN 5 Kota Tangerang

Schools are facilities created by the government to develop the potential that exists in humans through learning activities. To get a good school quality requires a teaching team that has good competence as well. To provide a motivation so that the teaching team is enthusiastic in providing teaching to students, the school will give a reward to teachers who excel. But in giving these rewards the school still uses the manual method so that in the selection of outstanding teachers it still takes a long time. Therefore, this research will try to provide an alternative for the school in deciding the teachers who excel in accordance with the criteria and methods used. In this study using the Simple Additive Weighting (SAW) method. In decision making, the Simple Additive Weighting (SAW) method is used in the selection of teachers who excel so that it will help the school in determining the teachers who excel. The results of the study were tested with TAM and got a score of 229 criteria. The results of the calculation will get a figure of 83.273%. The usability level of the application for selecting high-achieving teachers can be obtained a value of 83.27 %
Differential Rights Consciousness: Teachers’ Perceptions of Privacy in the Surveillance School

This article explores the rights consciousness of teachers as agents having a professional obligation to promote students’ rights. The case study comprises Israeli teachers, whose social status is low, in the context of school CCTV surveillance. Based on 55 interviews, the findings revealed three clusters of perceptions: dismissing students’ privacy as a discrete consideration in assessing school surveillance; acknowledging students’ privacy as a discrete consideration; and merging students’ and teachers’ privacy. Almost all teachers considered their own privacy. Our conclusions focus on teachers who had differential rights consciousness and alluded to privacy justifications only when they concerned their own rights.
구어성(orality)의 국어 교과서 적용 방안 연구 - 초등 국어 교과서 구어성의 실제성 구성을 중심으로 -

This study aims to suggest how ''orality'', a key attribute of oral communication, can be applied to Korean language textbooks in terms of the ‘authenticity’. To this end, first of all, the concept and reality of orality have been clarified. Orality was defined as the ''language culture style of oral thinking and expression'' and the empirical reality of orality was confirmed as ‘communicative event’, which include the act of communication and the production of discourse. Subsequently, the textbook authenticity composition perspective, ‘learner authenticity’. ‘authenticity awareness’ was established. Based on this, the application of orality in elementary Korean textbooks was explored using part of the content. As a result, the actual act of communication could be presented as a scene in a textbook, and the production of discourse could be revealed as an activity of awareness.
An Improved Technique for Computer Aided Detection of Breast Cancer using Mammograms and Image Mining

Image mining focuses finding unusual patterns in images and deals with making association between different images from large image database. It deals with the extracting inherent and embedded knowledge, image data relationship, or other patterns and which is not explicitly found in the images. It is more than just an expansion of data mining to image domain.  It is well known in the medical community that breast cancer is a leading cause of death in women (and to a lesser extent also affects men). When early detection of abnormalities is combined with proper medical attention, however, the risk of death and/or severe medical ramifications can be drastically reduced. Many devices and techniques (e.g., mammography) are currently under development to detect breast abnormalities earlier, and with greater accuracy than conventional devices. Presently Computer Aided Detection of breast cancer uses digital mammogram which has become the most effective technique for early breast cancer detection modality. Digital mammogram takes an electronic image of the breast and stores it directly in a computer. High quality mammogram images are high resolution and large size images. Processing these images require high computational capabilities. The transmission of these images over the net is sometimes critical especially if the diagnosis of remote radiologists is required. The aim of this study is to develop a research technique with Particle Swarm Optimization for feature subset selection and Association rule based classification to detect the mass whether normal, malignant or benign. It can be used to investigate the state of art of computer aided detection systems for digital mammograms, and evaluate the related techniques in image pre-processing, feature extraction and classification of digital mammograms. Furthermore, this paper will suggest the further research directions for next generation CAD for mammograms.
PHOENIX SYSTEM: A Tap for the Better Life

Abstract Nowadays, lots of people are deaf and dumb. They have problems in their living existence. Communications between normal person and a deaf-dumb people have always been a challenging task. The preference in embedded systems provides platform to design and develop a sign language translator system to benefit the deaf and dumb people; there exists a number of supportive tools. The main objective is to develop a real time embedded device for physically challenged for advancement of their communication in effective means. This system uses Raspberry Pi Camera for capturing the signs and controller for displaying in textual form and audio form. Keywords: Gesture recognisation, Indian sign language, Pi camera, controller Cite this Article Ranipa Arzoo R, Vora Vishal S. Phoenix System: A Tap for the Better Life. Journal of Image Processing & Pattern Recognition Progress . 2019; 6(1): 6–10p.
Perpetual: For Alto Saxophone and Live Electronics

“Perpetual” is a composition conceptualized around the idea of thought loops and the mental cacophony constructed through the accumulation of these echoing thoughts. “Perpetual” is comprised of four short movements inspired by an accumulation of some repetitive energy as interpretted through musical gesture - [A] Pulse, [B] Ripple, [C] Swirl, [D] Crash. These descriptors reflect the energy building up in the alto saxophone part in terms of pitch, timbre, and rhythmic intensity over the course of the piece. The saxophone part is a graphic score made up of short saxophone phrases and gestures connected using box notation. A single starting point at the beginning of each movement branches into a number of different possible progressions of gestures leading to a single endpoint in each movement. The means by which these gestures or phrases move between one another in the score is also inspired by the title of each movement, perhaps most clearly visible in [C] “Swirl”, in which gestures progress in several interlinked circular patterns. The electronic performer is responsible for triggering echos of various previously heard gestures in Ableton using a combination of manipulated MIDI playback, live audio capture, and audio effect. Pre-loaded MIDI clips correspond with gestures played by the saxophonist. These echoes accumulate, becoming more dense and cacaphonous over the course of the piece, culminating in a sea of echoes accompanying the frantic gestures and phrases in the saxophone that abruptly collapse into silence at the end of the piece. The varying paths available to the saxophonist encourage an interactive interplay between the saxophone and computer performance, as the saxophonist’s progression dictates which gestures can be echoed in the electronic accompaniment.
Implementasi TOGAF Pada Perancangan Sistem Informasi Reservasi Berbasis Progressive Web Application

&lt;p&gt;&lt;em&gt;The reservation system at the Ryvet Animal Care veterinary clinic, which still uses the manual reservation method, makes it difficult for consumers, company management, and veterinarians to access the availability of certain required information. This paper presents a reservation information system model based on Progressive Web. The system was analyzed using the Togaf Architecture Development Method, which was developed with MongoDB with CSS, HTML, and JavaScript programming languages. The test results show that the resulting system can streamline the reservation process at the Ryvet Animal Care veterinary clinic in accordance with the set targets.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; Animal Clinic, Reservation System, The Open Group's Architecture Framework (TOGAF), Progressive Web Application (PWA).&lt;/em&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;ABSTRAK. Sistem Reservasi pada klinik hewan &lt;em&gt;Ryvet Animal Care&lt;/em&gt; yang masih menggunakan cara reservasi manual menyulitkan para konsumen, manajemen perusahaan, serta dokter hewan untuk mengakses ketersediaan informasi tertentu yang diperlukan. Paper ini menyaikan sebuah model sistem informasi reservasi berbasis Progressive Web. Sistem dianalisis menggunakan &lt;em&gt;Togaf Architecture Development Method, &lt;/em&gt;yang dikembangkan dengan MongoDB dengan bahasa pemograman CSS, HTML, dan JavaScript. Hasil pengujian dari menunjukkan bahwa sistem yang dihasilkan dapat mengefektifkan proses reservasi di klinik hewan &lt;em&gt;Ryvet Animal Care&lt;/em&gt; sesuai dengan target yang ditetapkan.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Kata Kunci: &lt;/strong&gt;&lt;em&gt;Klinik Hewan, Sistem Reservasi, The Open Group’s Architecture Framework (TOGAF), Progressive Web Application (PWA).&lt;strong&gt;&lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;
Examining The Relationship Between Pre-Service Turkish Teachers Digital Writing Attitudes and Digital Reading Tendencies

This research aims to determine the relationship between pre-service Turkish teachers` digital writing attitudes and their digital reading tendencies. In this context, 167 teacher candidates from different grades studying in the Turkish language teaching program of a state university in the west of Turkey were consulted. The relational surveying method, one of the quantitative research methods, was used. "Digital Writing Attitudes Scale" and "Digital Reading Tendencies Scale" were used as data collection tools in the study. The obtained data were analysed with the SPSS package program. Since it was determined that the data showed normal distribution due to the assumption analysis of the findings, independent sample t-test and one-way ANOVA analyses were used in the research. In addition to these parametric tests, mean scores and standard deviation scores of the descriptive analysis results were used. As a result of the data analysis, it has been seen that pre-service Turkish teachers` digital writing attitudes and digital reading tendencies are at a high level. There has been no significant difference observed in the results in terms of participants gender for the convenience and motivation sub-dimensions of the scale. However, digital writing attitudes show a significant difference favouring female teacher candidate in the effect sub-dimension. According to the class variable, Turkish teacher candidates' digital writing attitudes show a significant difference in favour of small classes. The research findings concluded a moderate, positive, and significant relationship between pre-service Turkish teachers` digital writing attitudes and their digital reading tendencies. In order to provide digital transformation and dispositions, the positive and negative aspects of reading and writing in digital tools can be thoroughly researched, and improvements can be made by reviewing the existing tools.
DESIGNING A SPECIFIC EFL WRITING RUBRIC FOR A GENRE-BASED WRITING ASSESSMENT

The goal of this research is to design an assessment rubric that specifically designed for a genre-based EFL writing assessment.The ability to construct fair and valid methods of assessing students' progress and achievement in learning process is a necessary skill for teachers.The main objective of this research is to design an assessment instrument in the form of a genre-based writing rubric.The rubric designing was carried out in several stages, they are conducting needs analysis, designing the first draft of rubric, validating the product by experts as validators, trying out and revising the product.This development model refers to the research and development model developed by Borg and Gall (2007).The result of the combination of the theory and the rubric model produces a model that is slightly different from the EFL writing rubrics in general.The rubric design focuses on the structural aspects of the text in the hortatory exposition text, which are Thesis, Arguments, and Recommendations.An aspect that is no less important to assess and often overlooked is the title of the text.It as an aspect that was also assessed as a whole text.In addition, this use of percentages (%) to replace the numbers that are usually found in EFL writing.The final product of this research is an EFL writing rubric that can be used widely in a genre-based writing assessment.