Reviewerly/exHarmony huggingface dataset:
Diagnosis for Early Stage of Breast Cancer using Outlier Detection Algorithm Combined with Classification Technique

Breast cancer is the most dangerous cancers that lead to women in death. Particularly in the developed countries it takes second leading place that increase the chance of death in women. It can be not easily diagnosed by the lab. It has difficult to identifying at the beginning stage. This cancer begins from breast and disseminate to other body parts. It has cured easily if it is identified at beginning stage. The correct classification of benign cancer can prevent from superfluous treatment for patients. This paper focused on diagnosis early stage of the breast cancer based on data mining algorithms. The automatic diagnosis process plays on important role in data mining. The proposed method has a process of three stages. First, data objects are grouped into clusters using k-means clustering algorithm. Size of the dataset has to shrink gently the computation time also reduced. The second stage, the outlier detection (OD) algorithm has used to detect the outliers from the cancer dataset. Finally, diagnose the cancer is either benign or malignant using decision tree classification algorithm. The breast cancer dataset has been used to test the efficiency of the proposed method. The experiments were conducted in breast cancer dataset before and after removal of outliers. Comparison results prove that the proposed method as serves as the better one with high accuracy. This breast cancer research will help with a medical practitioner to diagnose the breast cancer and so that it helps to recover the patients.
JPR volume 57 issue 1 Cover and Back matter

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This study aims to determine the effect of Emotional Intelligence, Self-Confidence, Positive Reinforcement, Peer Environment, on Economic Learning Outcomes of Class XI IPS Students through Motivation as an Intervening Variable in SMA Negeri 1 Airpura, Pesisir Selatan Regency.The results showed that: 1) Emotional intelligence has a significant effect on student motivation at SMAN 1 Airpura District, with a path coefficient value of 0.341.2) Selfconfidence has a significant effect on student motivation at SMAN 1 Airpura District, with a path coefficient value of 0.204.3) Positive reinforcement has a significant effect on student motivation at SMAN 1 Airpura District, with a path coefficient value of 0.480.4) Peer environment has a significant effect on student motivation at SMAN 1 Airpura District, with a path coefficient value of 0.187.5) Emotional intelligence has a significant effect on student learning outcomes at SMAN 1 Airpura District, with a path coefficient value of 0.280.6) Selfconfidence has a significant effect on student outcomes at SMAN 1 Airpura District, with a path coefficient value of 0.204.7) Positive reinforcement has a significant effect on student learning outcomes at SMAN 1 Airpura District, with a path coefficient value of 0.303.8) Peer environment has a significant effect on student achievement at SMAN 1 Airpura District, with a path coefficient value of 0.172.9) Learning motivation has a significant effect on student learning outcomes at SMAN 1 Airpura District, with a path coefficient value of 0.239.
AFFECT ANALYSIS OF CRIME NEWS IN THE JAKARTA POST AND THE JAKARTA GLOBE: A STUDY OF SYSTEMIC FUNCTIONAL LINGUISTICS

This study explores the affect of appraisal systems by comparing the crime news in The Jakarta Post and The Jakarta Globe. There were six texts of the crime news that were classified into the same topics. These texts were analysed using Appraisal Systems Theory (Martin &amp; White, 2005). The objectives of the present study are to find out the differences of the affect of crime news in The Jakarta Post and The Jakarta Globe and then to know the types of appraising items in The Jakarta Post and The Jakarta Globe. The data is analysed by using the mixed method research. The present writer found out that the writers in The Jakarta Globe present the affect dominantly. The Jakarta Globe shows 63,8% of affect and it is dominated by the affect of dis/satisfaction. However, The Jakarta Post shows 36,2% of affect and it is dominated by the affect of in/security. In addition, the types of appraising items that occur in the affect of crime news are mental process, behavioural process, relational process, attitudinal lexis, minor clause, epithet and grammatical item.
THE EFFECT OF BRAND IMAGE, LIFESTYLE, AND PRICE ON BUYING DECISION ONLINE TRANSPORTATION SERVICE WITH PURCHASE INTENTION AS A MEDIATION :STUDY ON GOJEK CUSTOMERS IN BANDA ACEH CITY

This study intends to examine the effect of brand image, lifestyle, and price on buying decisions for gojek transportation services with purchase intention as a mediating variable.The sample taken was consumers of Gojekonline transportation service users in the city of Banda Aceh using a non-probability sampling method with a quota sampling technique so that a sample of 197 people was obtained.Data were analyzed in the form of Structural Equation Modeling (SEM) through the use of Amos software.The research found that brand image, lifestyle, and price directly influence purchase intentions; brand image, lifestyle, price, and purchase intention influence buying decisions, and; purchase intention partially mediates the influence of lifestyle and the effect of price on buying decisions.The novelty lies in the finding of purchase intention which acts as a partial mediator in the use of online transportation services in Banda Aceh.For further research, which can be devoted to online transportation, and the addition of other variables such as gender, distance, or others as moderating variables, which can be an indication of decisions about using online transportation.For practitioners, especially manufacturers of online transportation services, this research model can be the basis for re-establishing service strategies for the work area of the city of Banda Aceh.Producers need to pay attention to social status, expenditure for important things, tariffs, and preferential interests of producers in the future, in order to find the right strategy formulation to increase the use of society in online transportation services.
Decoupling Architecture from Randomized Algorithms in Flip-Flop Gates

Numerous analysts would concur that, had it not been for DHCP, the examination of the segment table may never have happened. In this work, we approve the development of connected records, which exemplifies the normal standards of AI. In this paper, we discredit that the renowned heterogeneous calculation for the combination of hinders by Charles Leiserson et al. [12] keeps running in Ω(logn) time.
Пандемия жағдайында білім берудің трансформациясы

The article offers a general overview of the changes in education during a global pandemic. Particular attention is paid to the difference in the introduction of distance learning in the Republic of Kazakhstan and the difference between online and offline classes, the methods used by the government of the Republic of Kazakhstan and the positive aspects of the pandemic in the field of education and in the life of schoolchildren and youth are also considered. Берілген мақалада әлемдік пандемия уақытында болып жатқан білім саласындағы ӛзгерістер туралыжалпылама шолу жасалды. Қазақстан Республикасының білім жүйесіне жаңадан енген қашықтан оқытудың тәсілдері мен әлемдік тәжірибені ескеру жайлы сӛз қозғалған, сонымен қатар пандемияның білім саласына әкелген тиімді және кемшін тұстары тӛңірегіндепікірлерайтылған.
Hvor godt er lærere forberedt på den digitale hverdagen?

How well are teachers prepared for digital technology in their work? In this chapter, we report on questions in the TALIS 2018 survey concerning information and communication technology (ICT). Teachers were asked how they use digital technology for student activities, how prepared they are for digital practice, and how they assess their own need for continuous professional development (CDP) related to using digital technology in a classroom setting. This chapter is divided into two main parts. In the first part, we introduce previous research in the field of digital competence. We look at how the use of digital technology has evolved in Norwegian schools and how it has been supported by various educational reforms. We also refer to frameworks and various analytical tools to better understand students’ digital competence and teachers’ professional digital competence (PDC). Furthermore, we consider the role of teacher education in developing teachers’ and student teachers’ PDC. In the second part of the chapter, we present findings from TALIS 2018. Here we highlight teachers’ needs and participation in CPD, the preparations they have received in teacher education, and how they use digital technology to promote students’ learning and engagement in various teaching activities. Findings on classroom management in technology-savvy environments are presented, and the general use of ICT within a Nordic comparative perspective is discussed. In conclusion, we summarize the most important findings and raise issues in need of further research.
WORLD ENGLISHES:

The following study aims at highlighting new directions of text complexity studies, giving way to more advanced and varied research in the area. It has become the tradition in Russian linguistics as well as foreign one to assess predominantly the complexity of educational texts, thus allowing the learners to boost text comprehension and better material recognition [1], [2], [3], [4]. Text complexity studies can be directed at other types of texts (fiction or newspaper articles) in order to raise the level of awareness and desire to read in general. Bearing in mind that newspaper articles in English can be written by native and non-native speakers, and both types of newspapers can be used in educational purposes, there is urgent need, as we perceive it, to distinguish the features of authentic and Russian English newspaper texts. The research question of upcoming studies can be accomplished as follows: Are English-language newspapers written by Russian speakers of English as ELF comparable with the texts of authentic publications? The results of this study will be interesting in terms of studying the Russian version of the English language as one of the World Englishes in order to demonstrate whether the differences between the English variants are significant. For this purpose, two tools of computational linguistic analysis can be applied: Coh-Metrix, a computational tool that produces indices of the linguistic and discourse representations (developed by Arthur C. Graesser and Danielle McNamara), and L2 Syntactical Complexity Analyzer (L2SCA) developed by Xiaofei Lu at Pennsylvania State University (a computational tool which produces syntactic complexity indices of written English language texts).
"Challenges of Natural Language Processing: A New Dimension of Research in Computing "

This paper is an approach to some new dimensions of research in the field of Natural Language Processing (NLP).The objective of this paper is to discuss some key challenges which are required to be addressed in this field.Researcher could be beneficial who wish to study and learn about applications and tools & technology of NLP.NLP is an arising area of research and development in the domain of computational linguistic.Till date, there are a number of NLP research dimensions already evolved.Among them, text analysis and speech recognition are the primary moto of NLP research.To achieve this, researcher need to concentrate on various tasks like speech recognition, text to speech conversion & vice versa, text summarization, story generation, named entity recognition, auto correct of grammar while typing, sentiment analysis, machine translation and automated answer generation etc. NLP is a challenging field since it deals with human language, which is extremely diverse and can be spoken many ways.The key challenges are resolving ambiguity in words, common sense representation, contextual information retrieval, pragmatic analysis etc. Though there are various applications and techniques are used to address these challenges in NLP, these are found in infant stage till date.This paper gives emphasis on some key areas of NLP where researchers can involve their research to enrich the NLP work.
Multi-level QR code with Hill Climbed Encrypted Public Level for Secured Message Transfer

With the world turning into a worldwide town, the data sharing requires abnormal state security with substantial verification of the data which ought not be undermined with the time, hence providing food all the above necessities we propose another brisk reaction (QR) code containing two stockpiling levels specifically open and private stockpiling levels, which can go above and beyond in validating the inventiveness of the reports. The open stockpiling level can be perused by any traditional QR code scanners while it's not the equivalent for the private stockpiling level as its being produced with exchanging the dark modules with finished examples of the first QR code consequently it tends to be perused by just explicit QR scanners. The data's being put away in the private stockpiling level is being encoded sing q-ary code substituted by mistake amendment systems along these lines expanding the QR stockpiling limit while the open stockpiling level data's are being scrambled with the key which will be sent to the private stockpiling level where it experiences all the procedure like the private data's and will be moved by means of QR to the required gatherings. The size can be expanded by the information's or with the finished example estimate
Authenticated Encryption using Lightweight Cryptographic Primitives for Wireless Sensor Networks

Wireless Sensor Networks (WSN) transmits sensitive data from physical environment to digital medium. Thus, security is essential to transmit these vulnerable data. Authenticated Encryption aim to provide security in WSN with integrity, confidentiality, and authentication of data transmitted. Block cipher modes of operations provide different cipher text for identical plain text which further enhances the security. Sensor nodes have its own operational constraint which makes security algorithm to be light in terms of area and low power consumption. In this paper novel architecture of authenticated encryption of lightweight symmetric cipher PRESENT and lightweight hash function SPONGENT in OFB mode is proposed. Proposed design is evaluated in terms of Gate Equivalent (GE), operating frequency and power consumption using Cadence Genus® tool using 180 nm technology library.
Analisis Faktor Penyebab Keterlambatan Pendistribusian Dokumen Rekam Medis ke Poli Bedah di RSUPN Dr. Cipto Mangunkusumo

Based on research at RSUPN Dr. Â Cipto Mangunkusumo, Central Jakarta, there was a delay in the distribution of medical record documents to arrive at the surgical clinic more than 30 minutes. The purpose of this research was to identify the causes of the delayed in the distribution of medical records documents to arrive at the surgical clinic based on 5 management elements, such as man factors, materials factors, machine factors, methods factors, motivation factors and the factors of arrange the recommendations effort for improvements in the supply of medical record documents at RSUPN Dr. Cipto Mangunkusumo. This type of the research uses qualitative analysis. Based on the results and discussion, in the man factor there are filing staffs who still lack discipline such as, often come late, the one of the filing staff often absen. The material factor there is still a medical record document which folder / cover is torn, and therefore the medical record number and the patient's name are not visible or unclear, so that the staffs has trouble when searching for the medical record documents. The machine factor, which is EHR, usually occurs loading or could not be a accessed so the tracer not coming out and when the EHR can be accessed, the tracer will come out with a lot. Ther methods factor is KPI percentage of the speed of providing medical records of patients without agreement arrived at the Â polyclinic in 2019 still has not reached the target of 90%. After an evaluation, in 2020 the time of the document arrived at the polyclinic would be less than 30 minutes by reducing the target to 75%. Motivation factor there is no external motivation provided by the head of the medical recordÂ .The conclusion is the filing staffs did not come on time and did not come, the materials of the cover on medical record documents are easily torn, EHR is often difficult to access, the achievement level has not yet reached the target of providing medical record documents, and there is still no motivation from the head of medical record.
Revision of paper taking three Referees comments in Referee1, Referee 2 and Rémi Gandoin

Response to Referee #1 Thank you very much for your review with helpful suggestions for improvements.Line 22 Font size is smaller than the other.-Now it is font size 10.Line 49 "in prep", Paper in the preparation should not be referred.Other paper should be cited.-(Hahmann et al. in prep.) is deleted.Line 145 Table 2 should be Table 1 corresponding to the line 137.-Corrected Line 248 "the dense population of large ships" will be "the congestion of large ships" or "the overcrowding of large ships"."Population" is not appropriate for ship conditions.-Changed to "congestion" Line 240 "sped" should be "speed".-Corrected Line 258 What is the example of "coastal atmospheric ï ň Ćow phenomena"?-The sentence is expanded:. .."such as land-sea breeze and flow intensification.See Beal et al. 2015 for further details on coastal C1
Implementation of Improved Association Rule Mining Algorithms for Fast Mining with Efficient Tree Structures on Large Datasets

ARM is a significant area of knowledge mining which enables association rules which are essential for decision making. Frequent itemset mining has a challenge against large datasets. As going on the dataset size increases the burden and time to discover rules will increase. In this paper the ARM algorithms with tree structures like FP-tree, FIN with POC tree and PPC tree are discussed for reducing overheads and time consuming. These algorithms use highly competent data structures for mining frequent itemsets from the database. FIN uses nodeset a unique and novel data structure to extract frequent itemsets and POC tree to store frequent itemset information. These techniques are extremely helpful in the marketing fields. The proposed and implemented techniques reveal that they have improved about performance by means of time and efficiency.
Security and Privacy of E-Health Data using Two Fish Encryption Algorithm

The rapid growth development of the Internet of Things (IoT) has supported communication between various smart devices and it helps to exchange data between them. IoT is very highly demand topics between the researchers. The main goal of IoT in health care is to provide real time monitoring of the patient. But these new challenges also introduced the privacy and security to the health care data. Security is a major concern of the data. A system requires with authentic protocol for maintaining privacy of health care data. After going through all methodologies of the protocol encryption will be carried out of data of the health care with “two fish” encryption technique. At server side, it will automatically get decrypted after applying key. Two fish encryption algorithm is a block cipher algorithm of 128 bit. The key length vary until 256 bit. Key is divided in two parts as the first half of the key will encrypt the plain text and second half of the key will modify the encryption algorithm.
A Translation System That Converts English Text to American Sign Language Enhanced with Deep Learning Modules

A recent surge in interest to create translation systems inclusive of sign languages is engendered by not only the rapid development of various approaches in the field of machine translation, but also the increased awareness of the struggles of the deaf community to comprehend written English. This paper describes the working of SILANT (SIgn LANguage Translator), a machine translation system that converts English to American Sign Language (ASL) using the principles of Natural Language Processing (NLP) and Deep Learning. The translation of English text is based on transformational rules which generates an intermediate representation which in turn spawns appropriate ASL animations. Although this kind of rule-based translation is notorious for being an accurate yet narrow approach, in this system, we broaden the scope of the translation using a synonym network and paraphrasing module which implements deep learning algorithms. In doing so, we are able to achieve both the accuracy of a rule-based approach and the scale of a deep learning one.
A Simulation Tool for a Large-Scale NoSQL Database

The amount of data on the Web and the number of users accessing those data drastically grows every year. Web-based services have to be able to receive and process those requirements within the shortest possible time. Additionally, they have to manage sudden and unpredictable peaks of user requirements for accessing the data. To tackle these problems, NoSQL databases have been designed to provide scalability and good performance. However, it is important to know in advance the number of resources (i.e. computers, network capacity) to efficiently deploy a database application. In this work, we propose a simulator for a NoSQL database named MongoDB. Our simulator aims to detect saturation levels of the resources to ensure an efficient execution of MongoDB upon different users demands and upon failures of resources.
Computing Paradigms

As a starting point with regard to what will be presented in the current chapter, we consider the distinction between procedure-oriented programming and object-oriented programming [1, 2]:
Certain investigation on biomedical impression and image forgery detection

In today's digital age, the trust towards image is distorted because of malicious forgery images. The issues related to the multimedia security have led to the research focus towards tampering detection. As the source image and the target regions are from the same image so that copy move forgery is very effective in image manipulation due to its same properties such as temperature, colour, noise and illumination conditions. In this paper, we have analysed some papers related to copy move forgery detection and finally concluded with comparative analysis with some parameters and also medical and biomedical image analysis, databases, search engines, devices and system security. And the main objective our work is to find forged region detection based on block-based and key-point image forgery detection method with the original image and forged image data set. In this paper, we have investigated some comparison regarding future works, forgery types, metrics and forgery detection types.