Reviewerly/exHarmony huggingface dataset:
TRAINING WRITING NONFICIAL STORIES IN STUDENTS OF THE PGSD STUDY PROGRAM WIDYA DHARMA KLATEN UNIVERSITY

Widya Dharma University Primary School Teacher Education (PGSD) Study Program students are expected to have insight and knowledge in writing nonfiction stories or real news. The purpose of this service activity program is to train prospective elementary school teacher students to be able to write nonfiction stories or real news. The method used in this service is the provision of training with lecture, discussion, and question and answer methods. The results obtained in the training of writing nonfiction stories are the participants' interest and the urgency of the news. The trainees writing nonfiction stories have an interest in being interested in writing nonfiction stories or real news because it will be useful information in the community. The urgency of real news must be delivered because real news will provide truth that must be understood by all parties including elementary school children.
Predictive Analysis of Cryptocurrencies for Developing an Interactive Cryptocurrency Chatbot using IBM Watson Assistant

The main objective of this paper is to analyze the characteristics and features that affects the fluctuations of cryptocurrency prices and to develop aninteractive cryptocurrencychatbot for providing the predictive analysis of cryptocurrency prices. The chatbot is developed using IBM Watson assistant service. The predictive analytics is performed by analyzing the datasets of various cryptocurrencies and applying appropriate time series models. Time Series Forecasting is used for predicting the future values of the prices. Predictive models like ARIMA model is used for calculating the mean squared error of the fitted model. Facebook’s package prophet () which implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly and weekly seasonality are further used to predict cryptocurrency prices.
Dialectical epistemology

The article is devoted to epistemology. It is revealed that progress in the direction of the true representation of a natural object occurs when a meaningful representative definition of it organically connects two fundamental dialectical epistemological flows. The first is the intuitive heuristics that are born of the imagination and are purely subjective nouns, the Genesis of which is idealistic. The second is the sensory-rational experience of observation-apperception, which is a purely external, in relation to the subject, induced reaction due to the material nature of the object. The results of verification activities are an indicator of the organic connection of the indicated flows. It is shown that the «parallel» materialistic and idealistic lines in epistemology point to two equal oppositional realities, the contradiction of which, according to the dialectical method of reasoning, is removed through the constitution of a single metaphysical substance — the spirit. These lines are clearly separated through the reflection of two heterogeneous cognitive components. The necessity of changing paradigmatic guidelines in the philosophy of natural science from mechanistic-atomistic to organismic is discussed. In the preceding part, a criticism is rejected of metaphysics of scientism.
Between Irony and Tragedy (To the Discussion about Education and Science in I&amp;I)

This note is a response to the criticism of colleagues who expressed their opinion about the publication: Razumov V.I., Orekhovsky P.A. Carnival Time: Russian Higher Education and Science in the Postmodern Era // Ideas and Ideals. – 2020. – Vol. 12, N 3, pt. 1. – P. 77–94. The article received ten different responses, including both agreements with some of the theses, and objections, as well as alternative proposals. The works represent a wide scientific geography from Abakan to Moscow, although the bulk of the reviews came from Novosibirsk. The authors represent various humanitarian specialties. An analysis of the works published in Ideas and Ideals allows us to conclude that the reforms of science and education undertaken by the Government of the Russian Federation are alarming. At the same time, attention is drawn to both dissatisfaction with the current state of affairs and a wide range of ideas about what strategy for the development of science and education is required in modern Russia. Similarly, very different positions are presented in relation to postmodernism and its role in changes in science and education. The authors make an attempt to characterize the grounds for the coincidence and difference of the positions of the debaters and authors.
Ensure Security for Mapreduce-Hadoop Distributed File System using Encryption Method Over Big Data

Big data security is the most focused research issue nowadays due to their increased size and the complexity involved in handling of large volume of data. It is more difficult to ensure security on big data handling due to its characteristics 4V’s. With the aim of ensuring security and flexible encryption computation on big data with reduced computation overhead in this work, framework with encryption (MRS) is presented with Hadoop Distributed file System (HDFS). Development of the MapReduce paradigm needs networked attached storage in addition to parallel processing. For storing as well as handling big data, HDFS are extensively utilized. This proposed method creates a framework for obtaining data from client and after that examining the received data, excerpt privacy policy and after that find the sensitive data. The security is guaranteed in this framework using key rotation algorithm which is an efficient encryption and decryption technique for safeguarding the data over big data. Data encryption is a means to protect data in storage with containing a key encryption saved and accessible to reuse the data while required. The outcome shows that the research method guarantees greater security for enormous amount of data and gives beneficial info to related clients. Therefore the outcome concluded that the proposed method is superior to the previous method. Finally, this research can be applied effectively on the various domains such as health care domains, educational domains, social networking domains, etc which require more security and increased volume of data.
APIs Rule!

Enterprise API adoption has exceeded expectations. We see the proliferation of APIs in almost all the industries. It is not an exaggeration to say a business without an API is like a computer with no Internet. APIs are also the foundation of building communication channels in the Internet of Things (IoT) domain. From motor vehicles to kitchen appliances, countless devices have started communicating with each other via APIs.
Experimental measurement of crack tip strain field in a single crystal

Crack tip deformation fields in an aluminum single crystal are quantitatively obtained by applying three-dimensional moire interferometry technique. Tensile specimen made of aluminum single crystal has an edge crack on (223) plane with its tip along [10,7,2] direction. Specimen with this specific orientation undergoes power-law hardening with hardening index n being 3.1. The experimental arrangement for moire interferometry results in a displacement sensitivity of 0.47 μm/fringe. Displacement fields at the free surface near the crack tip are mapped with moire fringe patterns. Both effective strain and maximum shear strain within a small region of less than 2 mm from the crack tip have been evaluated. In partial agreement with earlier analytical and numerical solutions, the results of this experiment show that the deformation fields near the crack tip are divided into several different angular sectors, and concentrated shears are found at these sector boundaries where displacements are continuous. The experimental results also show that the effective strain and maximum shear strain remain constant (independent of angle θ) within certain angular sectors.
maskings

"maskings" is an exposition distilled from a wider research project called "how the vibraphone can be a mouth". Using music, prose, and free verse, I seek to highlight the issues that project revealed within jazz and improvised music studies, and studies into vibraphone practice; briefly show the practical-philosophical roots of my methodology in the research; and present the practice-led roots of my current philosophy of the vibraphone.
Blockchain and Internet of Things: A Survey

&lt;p&gt;In the age of next-generation computer, the role of the cloud, the internet and smart devices will become stronger. These days we all know the word smart well. This word is often used in our daily lives. The Internet of Things (IoT) will generate a variety of information from a variety of resources. It can store big data in the cloud. Fog computing acts as a signal between cloud and IoT. Fog extensions in this framework apply to material under IoT. IoT devices are called Fog nodes, which can be accessed anywhere within the network range. A blockchain is a novel way of recording in a secure sequence. Creating a new framework in the development of Internet of Things is one of the critical problems of wireless communication where solving such a problem can lead to continued growth in the use and popularity of IoT. Proposed research creates a framework for providing a framework for middleware on the internet of smart devices network for the internet of things using blockchains technology. Our great offering connects new research that integrates blockchains into the Internet of Things and provides secure Internet connection for smart devices. Blockchain (BC) Internet of Things (IoT) is a new technology that works with low-level, distributed, public and real-time leaders to maintain transactions between IoT sites. A blockchain is a series of blocks, each block being linked to its previous blocks. All blocks have cryptographic hash code, previous block hash, and its data. Transactions in BC are the basic components used to transfer data between IoT nodes. IoT nodes are a variety of portable but smart devices with embedded sensors, actuators, systems and the ability to communicate with other IoT nodes. The role of BC in IoT is to provide a process for processing secure data records using IoT nodes. BC is a protected technology that can be used publicly and openly. IoT requires this type of technology to allow secure communication between IoT nodes in different environments. Events in BC can be tracked and monitored by anyone who is certified to communicate within IoT.&lt;/p&gt;
Computational Security

In the first part of this book we will look at the foundations of modern cryptography in general and the foundations of hash functions in particular. The goal of this part is to introduce the basic primitives such as one-way functions, pseudorandom functions, and collision-resistant hash functions, but also important applications such as encryption or digital signature schemes. We will build up the basics gradually, proving in detail most of the presented results.
ANALISIS RAGAM BAHASA ILMIAH DAN GAYA SELINGKUNG PADA ARTIKEL JURNAL ILMIAH DI INDONESIA

This journal article discusses the comparison between the structure of writing in the journal Retorika, @rtikulasi, Salingka, Litera, and Pena Literasi. This journal article aims to find out the writing format in the journal Retorika, @rtikulasi, Salingka, Litera, and Pena Literasi. The writing of this journal article discusses the comparison of differences and similarities between the five journals. This article will also discuss the selingkung style and the variety of languages used in the five journals. Data in the form of documents analyzed using qualitative descriptive techniques. The purpose of this article is as knowledge for writers, especially beginners in writing journal articles to find out the format desired by a journal page. This as a condition of a journal article is published on the journal page. The results of journal articles show that there are differences and similarities between the five journals.
PSO Optimized Log Gabor QBIC System

In modern years, there is substantially technical progression in research area pertaining to image retrieval, in specific Query By Image Content (QBIC) system. It has turned out to be essential to deliver adept and effective method to retrieve images from the gigantic collections of images utilized in heterogeneous applications. In this paper, a hybrid QBIC retrieval system known to be PSO optimized Log Gabor QBIC system that retrieves color features, texture features and shape features of the images in three consecutive stages has been developed. In the proposed system, color features are retrieved by means of color histogram in the first stage. In subsequent stage, the texture features are extracted by tuning Log Gabor filters using Particle Swarm Optimization(PSO). Lastly, shape features are retrieved by polygonal fitting algorithm. The recommended method displays enhanced retrieval rate in terms of mean recall and mean precision when compared to the prevailing standard systems.
Decision Support Based Resource Allocation for Cost Reduction in Cloud Storage using Big Data Analytics

Provision of highly efficient storage for dynamically growing data is considered problem to be solved in data mining. Few research works have been designed for big data storage analytics. However, the storage efficiency using conventional techniques was not sufficient as where data duplication and storage overhead problem was not addressed. In order to overcome such limitations, Tanimoto Regressive Decision Support Based Blake2 Hashing Space Efficient Quotient Data Structure (TRDS-BHSEQDS) Model is proposed. Initially, TRDS-BHSEQDS technique gets larger number of input data as input. Then, TRDS-BHSEQDS technique computes 512 bits Blake2 hash value for each data to be stored. Consequently, TRDS-BHSEQDS technique applies Tanimoto Regressive Decision Support Model (TRDSM) where it carried outs regression analysis with application of Tanimoto similarity coefficient. During this process, proposed TRDS-BHSEQDS technique finds relationship between hash values of data by determining Tanimoto similarity coefficient value. If similarity value is ‘+1’, then TRDS-BHSEQDS technique considered that input data is already stored in BHSEQF memory. TRDS-BHSEQDS technique enhances the storage efficiency of big data when compared to state-of-the-art works. The performance of TRDS-BHSEQDS technique is measured in terms of storage efficiency, time complexity and space complexity and storage overhead with respect to different numbers of input big data.
Tugas ADM

In the implementation of every substance of education management in it, it must start from the planning process to the final process (supervision). Supervision can affect the planning process that will come, because with supervision can be known weaknesses and errors that occur so that it can be avoided in the future. Supervision must be done as well as possible so that the goals achieved can be realized. Supervision is a systematic effort to establish performance standards in planning to design an information feedback system, to compare actual performance with predetermined standards, to determine whether a deviation has occurred, and to take corrective actions needed to ensure that all resources education has been used as effectively and efficiently as possible to achieve educational goals
Detection of Tampered Images using Watermarking Technique

Over the most recent couple of years there is a gigantic improvement in advanced innovation . Most the data is in the form of images, videos and audios. But there are various software’s to modify these images. So the data we transmit through the digital images may not be secure. For example if we are using an image as an evidence then there may be a chance of modifying that image. There may be a risk of using a digital image as evidence. So, it’s not secure to use digital images as evidence. So we decided to do a research on technology that provide security to tampered images. But there are many technologies to detect tampered images. Our project mainly focused on watermarking technique to detect tampered images.
Configuring the Search Service Application

Search is a very important part of SharePoint, and many companies rely on the strong SharePoint Search Engine to find documents and information for their day-to-day jobs.
Application of Analytical Hierarchy Process (AHP) Method as Decision Support in Determining Internet Service Providers

Internet service providers that are used today are growing rapidly with various advantages and disadvantages. Because of this, there are many criteria that can be used as basic internet service providers that are most suitable for use. In this study, the author raised several network providers namely Telkomsel and Indosat. To choose a good Internet service provider is by using an AHP (Analytical Hierarchy Process) method, with this method respondents are guided to make decisions based on two-level criteria. Level 1 criteria: data transfer speed, type of service, and type of card. While for level 2 there are three alternatives, namely Telkomsel and Indosat. From the results of the selection of internet service providers, Telkomsel is the best compared to Indosat.
COMPARISON STUDY OF PERFORMANCE ANALYSIS OF INFORMATION SYSTEM USING THE METHODS OF END-USER COMPUTING SATISFACTION AND IT BALANCE SCORE CARD

Evaluation of information system performance is needed to get an overview of the ease of end-users in utilizing a new technology. This study aims to evaluate the performance of information systems in a state-owned company (PT PLN Madya Langsa) based on an end-user perspective that is separated into two categories: employees and managers. The level of employee satisfaction (primary user) is measured using EUCS (aspect of: content, accuracy, format, ease of use, timeliness, and satisfaction). The manager's satisfaction level (secondary user) is measured by using IT BSC (aspect of: company contribution, user, operational excellence, and future orientation). The evaluation on the primary user showed that it was low at 25.6%, moderate at 56.64% and high at 18%. The percentage of user satisfaction with the information systems is 72.9% of the results expected by users. Meanwhile, evaluation on the secondary user obtained the following results: low at 10.5%, moderate 84.2% and high at 5.3%. The percentage of user satisfaction with the information system was 92.8% of the results that is expected by users. This study also discusses why there are differences in the percentage of primary user satisfaction compare to the secondary user and provides suggestions how to improve the level of satisfaction of the end users in the future.
SIGNCRYPTION SCHEME BASED ON SCHNORR DIGITAL SIGNATURE

This article presents a new signcryption scheme which is based on the Schnorr digital signature algorithm. The new scheme represents my personal contribution to signcryption area. I have been implemented the algorithm in a program and here are provided the steps of the algorithm, the results and some examples. The paper also contains the presentation of the original Signcryption scheme, based on ElGamal digital signature and discusses the practical applications of Signcryption in real life.
A MULTI-STREAM HMM APPROACH TO OFFLINE HANDWRITTEN ARABIC WORD RECOGNITION

In This paper we presented new approach for cursive Arabic text recognition system. The objective is to propose methodology analytical offline recognition of handwritten Arabic for rapid implementation. The first part in the writing recognition system is the preprocessing phase is the preprocessing phase to prepare the data was introduces and extracts a set of simple statistical features by two methods : from a window which is sliding long that text line the right to left and the approach VH2D (consists in projecting every character on the abscissa, on the ordinate and the diagonals 45° and 135°) . It then injects the resulting feature vectors to Hidden Markov Model (HMM) and combined the two HMM by multi-stream approach.
GCMA: Guaranteed Contiguous Memory Allocator

The importance of physically contiguous memory has increased in modern computing environments, including both low- and high-end systems. Existing physically contiguous memory allocators generally have critical limitations. For example, the most commonly adopted solution, the memory reservation technique, wastes a significant amount of memory space. Scatter/Gather direct memory access (DMA) and input-output memory management units (IOMMUs) avoid this problem by utilizing additional hardware for address space virtualization. However, additional hardware means an increase in costs and power consumption, which is especially disadvantageous for small systems and they do not provide real contiguous memory. Linux Contiguous Memory Allocator (CMA) aims to provide both contiguous memory allocation and to maximize memory utilization based on page migration, but they suffer from unpredictably long latency and a high probability of allocation failure. Therefore, we introduce a new solution to this problem, the guaranteed contiguous memory allocator (GCMA). This guarantees efficient memory space utilization, short latency, and successful allocation. The GCMA uses a reservation scheme and increases memory utilization by sharing the memory with immediately discardable data. Our evaluation of a GCMA on a Raspberry Pi 2 finds a latency that is 15-130 times lower compared to a CMA, and a latency that is up to 10 times lower when taking a photo. Using a large working set in a memory-fragmented high-end system, the GCMA is able to produce a 2.27× speedup.
Learning Match Kernels on Grassmann Manifolds for Action Recognition

Action recognition has been extensively researched in computer vision due to its potential applications in a broad range of areas. The key to action recognition lies in modeling actions and measuring their similarity, which however poses great challenges. In this paper, we propose learning match kernels between actions on Grassmann manifold for action recognition. Specifically, we propose modeling actions as a linear subspace on the Grassmann manifold; the subspace is a set of convolutional neural network (CNN) feature vectors pooled temporally over frames in semantic video clips, which simultaneously captures local discriminant patterns and temporal dynamics of motion. To measure the similarity between actions, we propose Grassmann match kernels (GMK) based on canonical correlations of linear subspaces to directly match videos for action recognition; GMK is learned in a supervised way via kernel target alignment, which is endowed with a great discriminative ability to distinguish actions from different classes. The proposed approach leverages the strengths of CNNs for feature extraction and kernels for measuring similarity, which accomplishes a general learning framework of match kernels for action recognition. We have conducted extensive experiments on five challenging realistic data sets including Youtube, UCF50, UCF101, Penn action, and HMDB51. The proposed approach achieves high performance and substantially surpasses the state-of-the-art algorithms by large margins, which demonstrates the great effectiveness of proposed approach for action recognition.