Reviewerly/exHarmony huggingface dataset:
Identifikasi Faktor Penyebab Ketidaksesuaian Pelaksanaan Retensi Dokumen Rekam Medik Inaktif di RS Husada Utama Kota Surabaya

Hospitals as a health service facility are required to make medical records Retention is the transfer of inactive DRM to inactive filing to reduce the amount of DRM that is on an active filing rack. The number of visits in the Husada Utama Hospital in Surabaya each year has increased that is not proportional to the large capacity of storage space, causing an incompatibility of the implementation of medical record document retention SOP. The purpose of this study was to identify problems using five elements of management namely man, money, method, material, machine. This research is a type of qualitative research. The results of this study are the identification of problems that occur and the causes of the problem are knowledge, education, training, operational costs, inactive storage space, medical record shelves, scanning equipment, computers and SOP. As a result of these problems will result in a buildup of medical record files which causes narrowing in the storage room that affects the hospital's accreditation standards. The alternative solutions to problems are the existence of SOP socialization, attending training, the existence of a budget for procurement of equipment, the expansion of storage space and the addition of medical record file shelves, the provision of scanning tools and computers as well as SOP evaluation.
Establishment and applications of quality management system for service industries

Purpose: Our research study aimed to analyze the statement of the proverb 'Not-Aid, but-Trade,' for the economy of Pakistan over 1970-2018 based on time-series data collected from the World Development Indicators - World Bank. Research Methodology: Through evaluation of the theoretical and empirical literature, we estimate the influence of official development assistance, trade openness, foreign direct investment, inflation, and gross capital formation on the gross domestic product of Pakistan. To accomplish the required concerns, we implied the Unit-Root test, and the Autoregressive Distributed Lag Model Bound analysis. Results: No significant relationship revealed between inflation and official development assistance. In contrast, the openness of trade and foreign direct investment shows a significant positive relationship with the gross domestic product of Pakistan. Similarly, gross capital formation has a negative but significant connection with the gross domestic product of Pakistan. For the short-run period, trade openness, foreign direct investment, and inflation impart to a positive and significant relationship; however, gross capital formation presents a negative but significant linking with gross domestic product. Limitations: Our study covers the Pakistan economy time-series data over the 1970-2018 period. Contribution: Our study is helpful for the Pakistani economic policy formation, particularly useful for academics and researchers to understand the basic concept related to 'not-aid but-trade' philosophy. Keywords: GDP, ODA, Trade, GCF, Inflation
OPTIMASI ALGORITMA VECTOR SPACE MODEL DENGAN ALGORITMA K-NEAREST NEIGHBOUR PADA PENCARIAN JUDUL ARTIKEL JURNAL

Articles is one part of the scientific work which was manifested in the form of writing and containing a lot of information that are requisite and suited therein to the exclusion of .Many small article day with allah is as a variety of sorts of the title and the methodology that was used , but does not make up for the possibility of a resemblance of the title of the article that is there is .This study aims to for determining the rate of a resemblance between an article of the american journal of public from the point of view of the title of the articles the american journal of public by the use of an algorithm of vector space the model and compare it with an algorithm k-nearest neghbour .The data used pt pgn promised to supply 10 the title of an article of the american journal of public keyword on information retrieval .Testing the data with of these keywords documents produced by the only by the magnitude of the resemblance of its on the highest a method of vsm it will be on a doc 5 , doc 7 , doc 8 and doc 4 .While for the program knn generate a level of the resemblance of its on range doc7 , doc10| doc8 , doc10| doc4 , d10| doc5 , doc10| doc3 , doc10. So that came to the conclusion that the occurrence of the addition of the criteria used to they obtain documents they do similaritas keyword after
Factors influencing customer loyalty in 3rd party automotive shops

This study aims to address the current gaps in knowledge by identifying the main factors that influence customer loyalty to third-party automotive repair shops and provide strategies so that the latter can enhance customer loyalty and retention. The study focuses on third-party independent, automotive repair and service because of the limited and incomplete research on customer loyalty and strategies for improving business processes in this context. The dependent variable was Customer Loyalty and the independent variables were: Service Quality, Perceived Value, Trust, Habit, Reputation &amp; Servicescape. The study found that Service quality, Trust and Reputation have a significant influence on customer loyalty on third party automotive shops.
Image Encryption using Jumbling-Salting Algorithm

With the advent of digital world today, securing images across internet has become an important issue. There exist many image security techniques viz. steganography, encryption, watermarking etc. Image Encryption is one of such fruitful technique which encrypts an image using random secret key and stores the encrypted image on the server. There are many challenges of implementing image encryption algorithms such as higher computational complexity, loss of information during encryption, universality and applicability of algorithm, less scalability etc. Many image encryption algorithms are selective image encryption algorithm which works for specific part of image. It consists of encrypting only a subset of the data. The aim of selective encryption is to reduce the amount of data to encrypt while preserving a sufficient level of security. The selective encryption algorithms have a problem of scalability and data loss. The paper proposes a new algorithm Jumbling-Salting for images. The algorithm was earlier used in encryption passwords, text files, DNS, payment gateway data etc. An application is developed which incorporates the Jumbling salting encryption stategy for images.
Knowledge transfer for efficient cross domain ranking using AdaRank algorithm

Learning-to-rank has been an exciting topic of research exclusively in hypothetical and the productions in the information retrieval practices. Usually, in the learning-based ranking procedures, it is expected the training and testing data are recovered from the identical data delivery. However those existing research methods do not work well in case of multiple documents retrieved from the cross domains (different domains). In this case ranking of documents would be more difficult where the contents are described in multiple documents from different cross domains. The main goal of this research method is to rank the documents gathered from the multiple domains with improved learning rate by learning features from different domains. The feature level information allocation and instance level information relocation are achieved with four learners namely RankNet, ranking support vector machine (SVM), RankBoost and AdaRank. The estimation results presented that the AdaRank algorithm achieves good performance.
Teacher Training and Skill Enhancement in India using Innovative Techniques

In the present workforce, it is observed that most people are either unskilled or they find their jobs to be redundant or changing so rapidly that their skills become irrelevant. Earlier research suggests that the present-day education system is marksoriented, based mostly on rote learning, and does not train people with the skill sets required by the industry, thus creating a skill gap. Prior research points out that academicians and industry should work together to bridge this gap. In India, various initiatives have been undertaken by the Indian government, like "ITI Finishing Schools" which are implemented with the help of the Confederation of Indian Industry,or initiatives like "Skill India" and "Startup India", which focus on skill development. Quality education and training are the strategic necessities that can deliver employment skills. As a part of skill enhancement, an employee should not only plan for the skills required for the automated world, but also acquire those that go beyond technical competence. Researchers observed that generic skills like creativity, innovation, imagination, decision making, analytical skills, and design skills will take up the priority spots on the employer's agenda. These skills have to be encouraged in the coming years and should be included in the course of formal education. To handle this daunting task, teachers have to anticipate and plan their activities, which would enhance their students' creativity. This asks for the skill development of teachers in the form of on-the-job training while performing regular teaching duties, which is a lifelong learning process. It has been observed that the children educated through Finnish education system have been doing consistently well. Their skill anticipation and teacher training programs have been yielding good results. So, would it be possible to adapt their model to train teachers in India? If so, then how effectively? What changes need to be incorporated for implementing the same in Indian conditions? This research paper attempts to do a comparative study of education systems prevalent in Finland and India, with emphasis on teacher training and skill enhancement. In the process, also find ways for sustained development of prominent stake holders in education.The paper is based on analogies between Finnish education systems and Indian initiative towards quality education in the form of Draft National Education Policy 2019. The paper outlines the comparisons and possible changes in the Indian education system, based on the review of various literature available today.The conclusion is that, though Finnish education system cannot be adapted as it is in the Indian scenario but can definitely be implemented in certain areas which have been mentioned in the recommendations.
Prediction of solar direct irradiance in Iraq by using artificial neural network

Global solar irradiance is one of the main significant factors for designing and considering the volume of any solar station beside of it is usage in agricultural and building issue. Due of lack a precise information about the irradiance in Iraq metrological organization and seismology, this study is aimed to adopt the historical global data, build numerical analysis via using artificial neural network and predicting hourly irradiance. The test is applied over three locations Erbil, Bagdad, and Basra for being references to their closest locations. A foreword neural network (FNN) is the learning algorithm that is used in this study with relying on seven input variables consisting of Temperature, Precipitation, Humidity, Wind speed, Wind direction Sunshine duration and Date. After normalizing and standardizing data, an iteration method is used for determining the optimum number of neuron(s) in a hidden layer. It yields a least Root Mean square error (RMSE) between 2.5 to 3. The computed correlation coefficients are between 0.94 -0.96 for the mentioned locations.
Improving English Spoken Skills through Self Recorded Video for Higher Education Students

The research is aimed to analyze the improvement of English speaking skills for higher education students by means of Self Recorded Video. The focus of this research is on four speaking skill categories; Pronunciation, Vocabulary, Grammar and Fluency. The recorded videos are analyzed.To get the answer of the aims, descriptive method is used. The data is students’ self recorded videos which were done in one semester (semester 1). The result obtained is that practising speaking English through self-recorded video can improve student speaking skills. The improvement can be in one or more categories.Keywords: fluency, self-recorded video, descriptive method
Myco Indus., Inc. v. BlephEx, LLC United States Court of Appeals of the Federal Circuit, 2020 955 F.3d 1

Biotechnology Law ReportVol. 39, No. 3 As presented by Chris HolmanMyco Indus., Inc. v. BlephEx, LLC United States Court of Appeals of the Federal Circuit, 2020 955 F.3d 1Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:3 Jun 2020https://doi.org/10.1089/blr.2020.29176.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 39Issue 3Jun 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Myco Indus., Inc. v. BlephEx, LLC United States Court of Appeals of the Federal Circuit, 2020 955 F.3d 1.Biotechnology Law Report.Jun 2020.248-255.http://doi.org/10.1089/blr.2020.29176.cmhPublished in Volume: 39 Issue 3: June 3, 2020PDF download
Multi-agent approach for data mining-based bagging ensembles to improve the decision process for big data

Today, data growth is accelerating to create a big data in various fields, such as social media, websites, e-mails, finance, and medicine. It needs analysis and knowledge extraction. In addition, data mining is a technology whose purpose is to promote information and knowledge extraction from a big data. In this paper, a multi-layered approach based on agents is proposed to extract knowledge from big dataset with bagging algorithm. To achieve this, we call the paradigm of a multi-agent system in Hadoop to distribute the complexity and processing of large datasets across several autonomous entities called agents. The goal is to predict the target class or value for each case in the data using the bagging technique that is dedicated to the task of classification or regression. This proposition will help decision-makers to take right decisions and provide a perfect response time by the use of the multi-agent system in Hadoop. Therefore, to implement the proposed architecture, it is more convenient to use the Apache Hadoop framework, Apache Spark MLlib framework for building scalable machine learning algorithms and JADE platform which provides a complete set of services and agents.
Cervical Cell Segmentation from Overlapped Cells using Fuzzy C-Means Clustering

Cervical cancer is the symptomless disease to cause death amongst women due to cancer. Most of the cervical cancer diagnosis process microscopic images are taken as sample to identify Segmentation of cervical cells. In this paper, Fuzzy c-means clustering algorithm is used to preserve the colour and data loss during segmentation is minimal. It accurately segments the individual cytoplasm and nuclei from a cluster of overlapping cervical cells. Recent methods cannot undertake such absolute segmentation due to various challenges involved in delineating cells coping with overlap and poor contrast. Improved method for detecting overlapping cervical cells using advanced tests yields better results in detection. The cervical cancer can be prevented through both early detection and best treatment based on the acuteness of the disease.
Recognition of Teeline Shorthand using Deep Learning.

Recognition of the Teeline shorthand is the interesting research problem. The accurate recognition of the Teeline patterns which helps the journalists to summarize the VIPs talk during the press meets which reduces the writing time. In order to address the above issues, the proposed method addresses the automatic recognition of the Teeline symbols which is used to provide alphabets as output. The framework consists of obtaining the input image, pre-processing it, perform the background subtraction on grayscale image and prepare the dataset for recognition. To prepare the dataset, the letters are written using the digital pen, it generates the pixelsand it is recorded in the Android application. Later these pixels are used to convert them into the image dataset. The prepared database is fed to the manually designed eleven layered Convolutional Neural Network (CNN). CNN is designed in such a way that it accepts the input Teeline alphabet and it able to say the equivalent English alphabet based on the training process. It has been carried out on the MATLAB 2018b and achieved the accuracy of 95%.
Effect of Virtual Reality-based Training Program on Patients with Mild Cognitive Impairment

Exercise programs using virtual reality (VR) been proven effective in relieving symptoms of dementia and delaying the deterioration of it.Nintendo Wii (Wii), a VR game, has been proposed as an easy-to-install and accessible device because it is cheaper and lighter than conventional VR systems.This study aimed to define the effect of a rehabilitation program using Wii, upon the level of cognitive function, depression, and independent performance of daily activities, in early dementia people.The research target population were 40 old men/women suffering with mild cognitive impairment (MCI), who were randomly allocated to the VR-game group and the control group, with each group consisting of 20 patients.The VR-game group was provided with a training program using Wii, while the control group received no intervention except conventional elderly care.The intervention period was 12 weeks, during which time a total of 36 sessions were provided, at the rate of three sessions per week of 15 minutes each.The cognitive function was found to have improved in the VR-game group, whereas it got worse in the control group after the program.A comparison of the scores in the Geriatric Depression Scale and the ADL(activities of daily living) showed statistically significant decrease in the VR-game group.The findings in this study suggest that the Wii-based VR training program would reduce depression and enhance or maintain the quality of life in older people with MCI, while delaying the development of moderate dementia.The result may be attributed to the fact that the participation in the program was regarded as a leisure activity by the participants with MCI.Wii can replace the expensive and large-scale existing VR system in the field of the exercise intervention treatment of MCI patients.
Grammatical rules are discrete, not weighted, and not vulnerable

The paper defends the following positions: Grammaticality and acceptability must not be regarded as virtually coextensive.Grammaticality is discrete; acceptability is gradient.Acceptability can be measured directly; grammaticality can only be tested indirectly.Acceptability is a refl ex of performance factors interacting with the mentally represented grammatical rule system; grammaticality is a theoretical concept.Acceptability is a theory-independent behavioral property; grammaticality is defi ned by the cognitively encapsulated grammar, which is the empirical research target of grammar theory.
role of linguistics studies on the political debate

The paper is to find out the linguistics role contribution towards the political debate event at the election party. The presidential debate's primary purpose is to sponsor and produce debates for the United States presidential and vice-presidential candidates and to undertake research and educational activities relating to the debates. A leaders' debate or presidential debate is a public debate held during a general election campaign, where the candidates expose their political opinions and public policy proposals, and criticism of them, to potential voters. They are normally broadcast live on radio, television and the internet. Increasing learners' confidence, poise, and self-esteem. Providing an engaging, active, learner-centered activity. Improving rigorous higher-order and critical thinking skills. Enhancing the ability to structure and organize thoughts.
IoT Based Healthcare System

Health is a fundamental need. It is also a human right to have access to high-quality health care. Due to a lack of resources, India is now dealing with a slew of health problems. This review article discusses the concept of utilizing cutting-edge technology, such as the Internet of Things, to solve health problems. It provides an architectural assessment of a smart health care system based on the Internet of Things that aims to serve everyone with high-quality health care. Patients' bodily parameters may be measured in real time using this system design. Sensors gather patient body characteristics and send them to an Arduino Uno, which then sends the data to the cloud via a WiFI module.This information is saved in a MySql database server, which handles information and makes it accessible. The Android App may be used to see this information. Which may be installed on a smartphone, tablet, or computer? Authentication, privacy, security, and data management are all handled via cloud computing. If the data is abnormal, the patient and caretakers will be notified through email. Different decision-making algorithms may be used to make choices, and individuals can access the database based on them. The patient has access to their medical records. As a result, this system offers everyone with high-quality health care as well as error-free and seamless contact with patients.
An Optimal Enhancement of the Dynamic Features of Recommender Systems

Recommendation systems come under the domain of Data mining and Big Data analytics. It is useful tool that is used to predict the ratings or preferences of a user from a pool of resources. The preferences of user are dynamic in nature. The immeasurable usage of internet is having a great impact on the way we deal our lives and communicate with each other. As a result, the requirements of user browsing the internet are changing radically. Recommender Systems (RSs) provide a technology that helps users in finding relevant or preferential information among the pool of information using internet. This paper puts forward not only the issues related to the dynamic nature of user’ requirements but also the changes in the systems’ contents. The Recommendation Systems which involves the above stated issues are termed as Dynamic Recommender Systems (DRSs). This paper first defines the concept of DRS and then explores the various parameters that is taken into account in developing a DRS. This paper also discusses the scope of contributions in this field and concludes citing in possible extensions that can improve the dynamic qualities of recommendation systems in future.
Verifiable Essential Secret Image Sharing with Multiple Decryptions

We know that the essential secret image sharing (ESIS) scheme differs from traditional visual secret sharing with respect to the essentiality of the shares. In ESIS, to reconstruct the secret image, threshold number of the shares are required which includes all the essential shares. All the shares are very sensitive because it carries the secret information. Hence, reliability and authenticity of the shares before the decoding of the secret image are required which prevents a participant from intentionally or unintentionally to provide invalid shares. Proposed method is a novel verifiable essential secret image sharing (VESIS) with multiple decryption. Multiple decryption means that the decoding and verification process is done by human visual system as well as by EX-ORing the shares. Apart from this, proposed scheme also eliminates unnecessary encryption constraints of VSS like pixel expansion, explicit codebook and the number of the participants and it is also required simple computation and O(k) complexity for the decoding process.