Reviewerly/exHarmony huggingface dataset:
On the Evaluation and Comparison of Region Interpolation Methods

Abstract. This work presents a methodology for the comparison and evaluation of region interpolation methods proposed in the spatiotemporal databases literature. An evaluation performed using the methodology proposed is also presented. To the best of our knowledge this is the first time that such a methodology is discussed and presented in the spatiotemporal databases literature, and that region interpolation methods are evaluated and compared using the same dataset and using data from the evolution of real-world phenomena.
Visualization Analysis of Drilling and Logging Data in Offshore Oil and Gas Exploration

Jiang, X.; Wang, M.; Liu, F., and Zhang, Y., 2020. Visualization analysis of drilling and logging data in offshore oil and gas exploration. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 540–543. Coconut Creek (Florida), ISSN 0749-0208.With the implementation of China's marine strategy, the development and application of marine resources has become a current research hotspot. Oil and gas exploration plays an important role in China's marine development strategy, and as an important guarantee of oil and gas exploration, it is of great practical significance to study the data of marine oil and gas exploration and logging. Based on this, this paper first makes a detailed analysis on the demand of drilling and logging data and then extensively researches the design of a drilling histogram module. A visual analysis model of drilling and logging data is designed, and finally a visual analysis platform of drilling and logging data for offshore oil and gas exploration is constructed.
Face Detection and Recognition for Digital Forensics

Surveillance methods are becoming widely popular in many organizations, including law enforcement, traffic control and residential applications.A reliable mechanism to record and track human activities is through analyzing images.In particular, investigations are performed by searching for specific people in pictures.As the numbers of such images are increasing, manual examination of all frames becomes cumbersome.Some degree of computerization is strongly recommended.This paper discusses the possibility of developing a new software to achieve this.On analyzing the potential of various programming languages for image processing, Python has been opted for development as it provides a range of image manipulation libraries.This way, software is created where photos can be imported from different locations in the system and clustered according to the faces in these images.The application designed is helpful during investigation processes and helps in validating claims and evidence.
STATE OF THE ART OF WRITER IDENTIFICATION

The paper analytically reviews the methods and algorithms for solving problems arising in the development of writer identification offline systems. The main applied problems that are solved on the basis of the processing and analysis of handwritten text are considered; the classifications of writer identification systems, as well as the structure of offline systems are given. The paper also reviews handwritten text image databases and shows the tasks to which these databases are aimed. An attempt is made to systematize the algorithms for the preliminary processing of handwritten text images, depending on the task they are tackling at the stage under consideration. Based on the analysis of the most common algorithms of forming the handwritten text feature space, these algorithms are classified into ones for extracting geometric, structural, topological, statistical, and spectral features. A review of the algorithms for selecting each category from the listed features is conducted. Recognition methods used to identify the writer are also reviewed. The results of applying these methods, as well as their benefits and drawbacks are presented.
Challenges to the Utilization of Information and Communication Technology by Entrepreneurs in South-East, Nigeria

This study was aimed at determining the challenges to utilization of Information and CommunicationTechnology by entrepreneurs in South-East, Nigeria.One research question was posed to identify the challenges to utilization of ICT by entrepreneurs in South-East, Nigeria .One null hypothesis tested at 0.05 level of significance guided the study.The design used for the study was descriptive survey and the instrument was structured questionnaire.The population of the study was all the 1251 registered entrepreneurs of medium and large scale enterprises in the private sector, from which a sample of 723 respondents were drawn using proportionate stratifies random sampling technique.Mean and standard deviation were used in analyzing the data collected from the research question and real limit of numbers was used to judge the responses as to whether they were high or low.The t-test statistics were used to test the hypothesis.Findings of the study showed that there are challenges to a high extent in utilization of ICT by entrepreneurs in South-East, Nigeria. The null hypothesis of no significant difference in challenges was not rejected. Based on the findings, recommendations were made which include that government should establish policies which induce reductions in the general burden of regulation, taxation and cost of internet access to spur entrepreneurs on the use of ICT in their enterprises, government should ensure regular power supply to entrepreneurs to reduce the cost of much use of generator, government should make computer education compulsory at all levels of education to make more members of the society ICT compliant and entrepreneurs should organize regular ICT courses for their staff to upgrade their knowledge of new technology.
Path Smoothing With Support Vector Regression

One of moving object problems is the incomplete data that acquired by Geo-tracking technology. This phenomenon can be found in aircraft ground-based tracking with data loss come near to 5 minutes. It needs path smoothing process to complete the data. One solution of path smoothing is using physics of motion, while this research performs path smoothing process using machine learning algorithm that is Support Vector Regression (SVR). This study will optimize the SVR configuration parameters such as kernel, common, gamma, epsilon and degree. Support Vector Regression will predict value of the data lost from aircraft tracking data. We use combination of mean absolute error (MAE) and mean absolute percentage error (MAPE) to get more accuracy. MAE will explain the average value of error that occurs, while MAPE will explain the error percentage to the data. In the experiment, the best error value MAE 0.52 and MAPE 2.07, which means error data Â± 0.52, this is equal to 2.07% of the overall data value.Keywords: Moving Object, Path Smoothing, Support Vector Regression, MAE
Wilson Score Kernel Density Estimation for Bernoulli Trials

We propose a new function estimator, called Wilson Score Kernel Density Estimation, that allows to estimate a mean probability and the surrounding confidence interval for parameterized processes with binomially distributed outcomes.Our estimator combines the advantages of kernel smoothing, from Kernel Density Estimation, and robustness to low number of samples, from Wilson Score.This allows for more robust and data efficient estimates compared to the individual use of these two estimators.While our estimator is generally applicable for processes with binomially distributed outcomes, we will present it in the context of iterative optimization.Here we first show the advantage of our estimator on a mathematically well defined problem, and then apply our estimator to an industrial automation process.
Methodologies and Forensic Analysis Tools on Android Mobile Devices: A Systematic Literature Review

This article describes a study on the mapping and systematic review of literature to identify, analyze and classify published articles on the use of forensic analysis methodologies and tools on Android mobile devices. To develop the review, the technique proposed by Barbara Kitchenham was used, which allowed selecting 24 articles that present information related to this systematic review. The articles were selected from the year 2015 onwards; The main methodologies identified in the review are: NIST methodology, physical acquisition, logical acquisition and Digital Forensics Research Workshop methodology DFRW. The tools analyzed in the articles are: UFED, XRY, Oxygen Forensic, FTK Imager, among others.
Aplikasi Augmented Reality Pengenalan Bangunan Adat Desa Penglipuran

Penglipuran Village is a tourism village on the island of Bali. One of the attractions of Penglipuran Village is the traditional, uniform building that has characteristics that are still maintained since ancient times. Many tourists who visit and take pictures in front of a traditional building, but do not know clear information about the name and function of the building. The purpose of this study is to design an application as an information medium for the introduction of traditional buildings in Penglipuran Village using Augmented Reality technology. The research model used for application design is the waterfall model. This Augmented Reality application was built with Autodesk Maya and Unity software so that it can display 3D custom building information to the real environment by using the brochure media as a marker. The results of the study were successful in designing an Augmented Reality application that can provide information about the traditional buildings of Penglipuran Village in the form of 3D animation, text and audio narration
An introduction to intuition theory and practice: a summary and a research agenda

This introductory chapter outlines new advances in intuition research and summarizes themes that emerged from the Handbook of Intuition Research as Practice that aims to narrow the gap between research and practice. Among the main identified themes are: interaction between intuition and reasoning; contextuality of intuition; effects of feelings and sensations in intuiting; new approaches to study group intuitions; need to integrate non-Western views on intuition; different types of intuition education and training; new methods to bring intuition to consciousness; reconciliation of sensing and sense making as part of intuiting; and unequal balance between intuitive decision-making and problem-solving research.
Pengembangan Media Pembelajaran Interaktif Autoplay Media Studio 8.5 Pada Materi Gejala-Gejala di Atmosfer dan Hidrosfer

This research is based on the ineffectiveness of textbook based learning. The purpose of this study is to produce effective learning media based on validity. Learning media developed based on AutoPlay Media Studio 8.5. This learning media is applied to social studies subjects, especially on symptoms in the atmosphere and hydrosphere learning material. The research location was carried out at Tembeng Putik Islamic Junior Secondary School, East Lombok, NTB. This research design uses research and development. Data were collected using media validation sheets, teacher response instruments and learning achievement tests. The results showed that the validity of the media was declared very valid with a percentage of 91.83%. For practicality based on the teacher's response to the media is very good with a percentage of 93.12%. Whereas student learning outcomes after using the media based on AutoPlay Media Studio 8.5 were stated to be good with a percentage of mastery learning outcomes of 84%. Thus it can be concluded that this media can be used as a supporter of the learning process of social studies subjects in the phenomenon of symptoms in the atmosphere and hydrosphere in Tembeng Putik Islamic Junior Secondary School.
Current trends in cloud computing

Objectives: This work reviewed the latest, state-of-the-art works in the area of Cloud Computing to help researchers, developers and stakeholders in decisionmaking.Method: The reviewed works are filtered after the rigorous process by using renowned indexing database of ACM and IEEE along with the subject based journals on Cloud Computing of international repute.These papers are further filtered by selecting papers published in last 4 years only.Our initial findings lead our reviews to five major areas of Cloud Computing including Load balancing, resource scheduling, resource allocation, resource sharing, and job scheduling.In this work we have limited ourselves to only technical aspects of cloud computing while excluding areas of security, privacy and economics (for example CapEx).We have presented our findings in the form of tables and graphs showing trends in Cloud Computing towards research community on the basis of five aspects as mentioned above.Findings: Our findings show that researchers are working in the area of Job Scheduling while low attention has been given in Resource Scheduling.Moreover, an open source robust framework for research community is needed covering all the aspects shown above for running experiments.Currently these features are available in commercial and proprietary frameworks including Amazon Web Service, Microsoft Azure, and Google Cloud Platform.
Data Augmentation for Pipeline-Based Speech Translation

Pipeline-based speech translation methods may suffer from errors found in speech recognition system output. Therefore, it is crucial that machine translation systems are trained to be robust against such noise. In this paper, we propose two methods for parallel data augmentation for pipeline-based speech translation system development. The first method utilises a speech processing workflow to introduce errors and the second method generates commonly found suffix errors using a rule-based method. We show that the methods in combination allow significantly improving speech translation quality by 1.87 BLEU points over a baseline system.
A FORMATIVE EXPERIENCE IN REALITY AUGMENTED WITH PHYSIOTHERAPY DEGREE STUDENTS

V. Perez-Cabezas1R. Martin-Valero2C. Luque-Moreno1M.C. Ruiz-Molinero1A. Galan-Mercant1J.A. Moral-Muñoz1B.M. Nuñez-Moraleda1
A Study on Mouse Movement Features to Identify User

Identifying real user is a vital issue in information security.Various processes are using to identify user like password, punch card, PIN etc which identify some characters of a user but not the real user.Biometric identification techniques can identify real user like face decoction, finger print, iris technology etc but these are cost effective and not user friendly due to requirements of extra devices and systems.For this reason, researchers are giving emphasis on mouse movement based user identification technique.This technique solves current problems of real user identification and need no extra device.In this technique features are generated from mouse movement data and based on these features users are identified.Different researchers are proposing different types of features for identifying user from mouse movement data.Selecting and calculating these features is very important issue for this technique.In this paper we have shown such features collectively those are using by different researchers.We have tried to categorized and describe such features in different types with accuracy.Recommendation is mentioned in this paper for further using of mouse movement features.
Application of a New Greyscale Descriptor for Recognition of Erythrocytes Extracted from Digital Microscopic Images

In the paper an algorithm for description of greyscale objects extracted from images is applied for recognition of human red blood cells visible on digital microscopic images.This is a part of an approach for automatic (or semiautomatic) diagnosis of selected diseases based on the deformation of erythrocytes.The disease is concluded by means of the recognition of types of red blood cells visible on an digital microscopic image, stained using MGG method and converted into greyscale.The applied algorithm is based on the polar transform of pixels belonging to an object and a specialized method for constituting the resultant description, where derived coordinates are put into matrix, in which the row corresponds to the distance from the centre, and the column-to the angle.This assumption was previously applied only for shape features.The proposed algorithm includes several auxiliary steps, e.g.median and low-pass filtering in order to pre-process the extracted object in greyscale.The algorithm is experimentally evaluated and analysed.It is compared with four other greyscale descriptors, namely: Scale-Invariant Feature Transform, Gabor filter, Polar-Fourier Greyscale Descriptor, and the approach based on polar transform and projections.
Learning and Teaching Model on Covid 19 Era at UIN Maulana Malik Ibrahim Malang Indonesia

In practice, the implementation of the teaching and learning process is less encouraging on achieving critical thinking skills. In this Era of the 4.0 industry revolution, technology-based learning innovations are needed. Revitalizing learning systems, new literacy movements, digital literacy, technological literacy, human literacy become a necessity as the breadth and deepening of learning materials are capable of information technology. Technology in the educational world has created a huge influence, one of the learning models needed by the E-Learning Model. E-Learning is an application with Internet access that can connect between educators and students in an online study room. The purpose of this research is to know the E-Learning model of learning in improving students ' critical thinking. The method used in this study is qualitative research using a descriptive method. The type of case study with one site design. Research results show the E-Learning model can encourage students to think critically on the subject’s material.
Application of Blockchain Technology in the Field of Accounting Supervision

&lt;p&gt;Accounting supervision, one of the most basic functions of accounting, plays an extremely important role in accounting subject. As a new term in the field of information technology, blockchain technology has been continuously developed and improved in recent years, and it has gradually become a social focus. This paper introduces that blockchain can supervise accounting more effectively with its characteristics of openness, transparency, de credit, tamper proof and timing. Accounting supervision is a guarantee system to improve the quality of accounting information, but in recent years, due to the weakening of the ability of accounting supervision, financial fraud occurs from time to time. Because accounting supervision is not enough, accounting information is distorted and capital market is confused. Therefore, this paper analyzes the application of new information technology combined with accounting supervision, the reasons for weakening and the solutions.&lt;/p&gt;
Cloud Data Transfer and Secure Data Storage

Using shippable devices which means the utilization of physical shippable gadgets when you need to do disconnected one-time data transfers.If company send disk or a protected specific tool.Besides that, we can buy and ship your very own disks.Your duplicate information to the gadget and afterward deliver it to Azure where the information is uploaded.The accessible choices for this case are Data Box Disk, Data Box, Data Box Heavy, and Import/Export (utilize your disks) [1].In this Paper we will focus Cloud computing risk, ship cloud data, storage and best practice of incident management.
<i>iRyP</i>

With the growing popularity of mobile devices that have built-in cameras, capturing images has become a trivial job for ordinary people, who share the images with their friends or the public online. However, such digital images are often taken without the consent of some photographed persons, hence leading to privacy concerns. In this paper, we propose iRyP, a purely edge-based privacy-respecting system for mobile cameras. In order to meet the requirements of efficiency and usability, we propose to piggyback privacy policies in the advertising messages of Bluetooth Low Energy (BLE), which has been widely deployed in most mobile devices. As such, privacy policies of people in a photo view can be delivered timely and automatically. Moreover, we propose to use a perceptual hashing algorithm for fast face matching. To improve detection accuracy, we also design several new techniques for face-related image processing. We implement and evaluate a prototype system purely based on the Android platform. Our experiments show that iRyP can meet our design requirements and is practical and ready to use.
PENGEMBANGAN KETERAMPILAN MEMBACA PUISI DENGAN TEKNIK PERMODELAN PAR (PARTICIPATORY ACTION RESEARCH) PADA SISWA

The purpose of this study is, First, to examine poetry reading skills in third grade students of Madrasah Ibtidaiyah in Kudus district. Secondly, developing poetry reading skills in MI III students in Kudus district. This research uses modeling techniques with PAR approaches and methods. The data obtained from various data collection techniques were analyzed using descriptive analysis. The results of this study showed that the development of modeling techniques was able to improve poetry reading skills in third grade MI students who became research sites. Through the development of this PAR modeling approach students are given examples in advance so that students can develop their poetry reading skills. The teacher's role in this research is as a facilitator as well as a student motivator to read poetry well. From the analysis, there was a finding that students' poetry reading skills improved after the application of modeling techniques in learning Indonesian, especially in poetry reading material. Based on the results of the study, it was concluded that, the development of modeling techniques can improve students' poetry reading skills.Keywords: Development, PAR, Poetry Reading Skills
The Analysis of Alternative Distance Learning Implementation into the System of General Professional Training of Teachers

The purpose of the study was to justify and check experimentally the efficiency in the application of distance learning technologies to ensure future teachers’ readiness to pedagogical work in the process of general professional training. The quasi-experimental research was conducted while delivering the disciplines of “Pedagogics” and “Psychology” included in the cycle of general professional training. The levels of motivational, activity-oriented, and cognitive components of future teachers’ readiness to pedagogical work were measured using the determination methodology for the factors of the profession’s attractiveness developed by Yadov, the questionnaire entitled “The identifier of problematic dominant level in the process of addressing pedagogical tasks”, and the results of the final tests. To analyse the results obtained and to study objectively dynamics of changes in activity orientated, cognitive, and motivational elements, the research has used methods of mathematical data processing and a STATISTICA software for statistical analysis. The research found the efficiency of distance courses implementation with active teaching methods on the development of all components of future teachers’ readiness to pedagogical work. The author concluded that in the context of the general professional training of teachers and adaptation to the peculiarities of distance learning, the most efficient methods are the following: case-study, a problem-oriented lecture, a method of projects, portfolio, and discussion. In the view of the author, distance educational technologies, means of virtual visualisation and interactive content help broaden the didactical potential of active methods of pedagogical interaction and diversify delivery of the training material.