Reviewerly/exHarmony huggingface dataset:
Web development on Earth-Quake Measurement in Seismic Scale

Seismometer is an instrument that generates seismic wave signals and accurately reflect the movement of the ground. With the development of science and technology, especially when the introduction of electronic feedback technology and the development of digital seismic, the development direction of seismometer was high sensitivity, wide band, anti-interference and low power consumption. Looking forward to the new development direction of seismometer, the research development and application prospect of seismometer are widening. In this paper, the complexity faced in the seismic wave is introduced. The seismometer (newton-meter) calculated by the seismometer instrument during earth-quake has complexity in it due to large amount of magnitude therefore converting it into logarithmic moment (magnitude) becomes ease in data representation. Conversion of given seismic-moment (newton-meter) value to logarithmic magnitude should be performed by using simple logarithmic calculation and also conversion of given logarithmic magnitude value to a logical Seismic - moment value should be performed vice versa. The data visualization is enhanced easily since data of infinite value is converted into measurable finite value .Therefore convertion eases analyzing data during underground nuclear weapon test, occurance of natural tremors etc.
Named Entity Recognition for a Low Resource Language

Kokborok named entity recognition using the rules based approach is being studied in this paper. Named entity recognition is one of the applications of natural language processing. It is considered a subtask for information extraction. Named entity recognition is the means of identifying the named entity for some specific task. We have studied the named entity recognition system for the Kokborok language. Kokborok is the official language of the state of Tripura situated in the north eastern part of India. It is also widely spoken in other part of the north eastern state of India and adjoining areas of Bangladesh. The named entities are like the name of person, organization, location etc. Named entity recognitions are studied using the machine learning approach, rule based approach or the hybrid approach combining the machine learning and rule based approaches. Rule based named entity recognitions are influence by the linguistic knowledge of the language. Machine learning approach requires a large number of training data. Kokborok being a low resource language has very limited number of training data. The rule based approach requires linguistic rules and the results are not depended on the size of data available. We have framed a heuristic rules for identifying the named entity based on linguistic knowledge of the language. An encouraging result is obtained after we test our data with the rule based approach. We also tried to study and frame the rules for the counting system in Kokborok in this paper. The rule based approach to named entity recognition is found suitable for low resource language with limited digital work and absence of named entity tagged data. We have framed a suitable algorithm using the rules for solving the named entity recognition task for obtaining a desirable result.
Exhibition Narrative and Historical Educational Meaning of the Korean War History Memorial Facility

In recent history education, interest in civic education has been increasing, and attention has been paid to the influence of the form and contents of exhibition narratives of museums or historical memorial facilities that are delivered to visitors in the context of citizens’ social memories and memory culture. Among the historical memorial facilities, war memorial facilities have great social influence. In particular, memories of the “Korean War” have been deeply involved in the historical consciousness and historical culture of members of post-war Korean society. Thus, the “Korean War” as a theme of history learning or exhibition has significant meaning in the context of history education oriented toward citizen education. With this in mind, this study analyzed the potential wartime history of The Warmemorial of Korea, Patriot and Peace Memorial, DMZ Museum, and War and Women’s Human Rights Museum focusing on the importance of the educational and social role of historical memorial facilities and the growing influence of the Korean War. The theory of historical consciousness and type of narrative (traditional type, typical type, critical type, and genetic type) of Jörn Rüsen was borrowed to analyze the exhibition narrative of the historical memorial facilities. Using Rüsen’s historical consciousness as a tool to analyze the history of the Korean War, Rüsen analyzed the exhibition narratives of each historical memorial facility by linking the past to the present and the future in a way that embodies the past. After reviewing and analyzing the large narrative of the exhibition and the ‘Narrative abbreviation’, historical memorial facilities showed overlapping narrative and historical consciousness types. Meanwhile, traditional and typical types of wartime narratives stood out at the War Memorial of Korea and Patriot and Peace Memorial. In particular, the Patriot and Peace Memorial wanted to convert traditional and typical narratives into memories for local identity. The War and Women’s Human Rights Museum showed critical and genetic exhibition narratives from the perspective of approaching the ''war'' itself, although it is not a memorial facility directly related to the Korean War. While revealing typical and traditional war narratives and their corresponding historical consciousness, the DMZ Museum attempted various angles of narrative, conscious of critical discourse. We learn history and try to understand the direction of our lives through understanding history. As historical memories are valued, the impact of memories other than textbooks on our perception of history is growing. The memory of war is stronger in that character. In particular, war memories by monuments are typical. Since it is an interface between knowing about war and learning how to remember war, it is necessary to think about the historical educational meaning of developing the power to analyze the exhibition history of historical memorial facilities.
Key Indicators for Linguistic Action Perspective in the Last Planner® System

Since 2001, a link has been established between the Last Planner ® System (LPS) and Linguistic Action Perspective (LAP).However, to date, it has not been studied in sufficient depth.This research developed a system of indicators to measure and control the management of commitments, through the Design Science Research (DSR) methodology, and thus contribute to the development of the social dimension of sustainability that is often neglected in construction management research.The main contributions of this paper are a proposal of five main activities to apply the DSR method, a checklist to analyze the engagement of meeting participants, a notebook for last planners, delve into the variations that can occur to the basic movements of LAP, and the creation of a system of indicators hence updating the Percent Plan Complete (PPC) with a reliability indicator.The main limitation of this research is that the system was only validated in two South American countries that implemented LPS.In future studies, we propose to apply case studies in weekly planning meetings in other industries www.videleaf.comworldwide and to determine the recommended values to improve communication and achieve the proper implementation of LAP with LPS and without LPS.
Correction: Italian norms and naming latencies for 357 high quality color images

[This corrects the article DOI: 10.1371/journal.pone.0209524.].
Potential Detection Application of Nodular Melanoma on Melanocytic Nevi Image Based on Android

Nodular melanoma is a deadly rare type of skin cancer. Nodular Melanoma has characteristics asymmetrical shape, border irregularity, nonhomogeneous or has several color variations and the diameter is more than 6 millimeters. Nodular melanoma has a physical form similar to melanocytic nevi, therefore nodular melanoma can be detected from melanocytic nevi spread throughout the body. This research aims to detect nodular melanoma through melanocytic nevi by utilizing the android system in order to ease the user by using camera smartphone in detecting cancer. This application uses image processing and feature extraction of the ABCD method to process images with decision tree c4.5 classification method to detect potential of nodular melanoma diagnosis from melanocytic nevi image. The ABCD method is a medical method used to detect the possibility of skin cancer using 4 parameters including asymmetrical shape, border irregularity, color and diameter. Decision tree c4.5 is classification method that using entropy and gain to make rules of decision tree. The image data test is obtained from the results of the android-based smartphone camera shooting and from medical record. Output of this application is a diagnosis condition of melanocytic nevi is healthy or nodular melanoma potentially. The accuracy of this application is 97.5%.
PHATIC COMMUNION IN THE PERSPECTIVE OF LANGUAGE DIGNITY

The efforts to dignify the Indonesian language must not stop at the elaboration of grammatical rules. The Indonesian grammatical rules have long been standardized but it is still debatable whether the Indonesian language has achieved its dignity or not. As a rule, the dignified language should carry the various functions which cater to several different interests and is learned by the wider audience. The formulation of rules interconnecting with language use as in the pragmatic studies must be promoted. Essentially, the linguistic study and pragmatic study of language have the same purpose despite their different manners of doing it.
Identifying emerging priorities in Knowledge Translation from the perspective of trainees

As the Knowledge Translation (KT) field advances, there is an increasing need to identify priorities to help shape future directions for research. An important source of KT priorities is ‘experts’ who are well-established researchers and practitioners. Another potential source for identifying priorities is trainees. Given that many KT trainees are developing their programs of research, understanding their main concerns and priorities for KT research and practice is critical to supporting the development and advancement of KT as a field. The purpose of this study was to identify priorities for research and practice in the KT field from the perspectives of KT researcher and practitioner trainees.
Semi-Automatic Depth Map Generation in Unconstrained Images and Video Sequences for 2D to Stereoscopic 3D Conversion

In this work, we describe a system for accurately estimating depth through synthetic depth maps in unconstrained conventional monocular images and video sequences, to semi-automatically convert these into their stereoscopic 3D counterparts. With current accepted industry efforts, this conversion process is performed automatically in a black box fashion, or manually converted using human operators to extract features and objects on a frame by frame basis, known as rotoscopers. Automatic conversion is the least labour intensive, but allows little to no user intervention, and error correction can be difficult. Manual is the most accurate, providing the most control, but very time consuming, and is prohibitive for use to all but the largest production studios. Noting the merits and disadvantages between these two methods, a semi-automatic method blends the two together, allowing for faster and accurate conversion, while decreasing time for releasing 3D content for user digest. Semi-automatic methods require the user to place user-defined strokes over the image, or over several keyframes in the case of video, corresponding to a rough estimate of the depths in the scene at these strokes. After, the rest of the depths are determined, creating depth maps to generate stereoscopic 3D content, and Depth Image Based Rendering is employed to generate the artificial views. Here, depth map estimation can be considered as a multi-label image segmentation problem: each class is a depth value. Additionally, for video, we allow the option of labeling only the first frame, and the strokes are propagated using one of two techniques: A modified computer vision object tracking algorithm, and edge-aware temporally consistent optical flow./p pFundamentally, this work combines the merits of two well-respected segmentation algorithms: Graph Cuts and Random Walks. The diffusion of depths, with smooth gradients from Random Walks, combined with the edge preserving properties from Graph Cuts can create the best possible result. To demonstrate that the proposed framework generates good quality stereoscopic content with minimal effort, we create results and compare to the current best known semi-automatic conversion framework. We also show that our results are more suitable for human perception in comparison to this framework.
Cyber Security Challenges through the Lens of Financial Industry

The paper aims at drawing attention on cyber security risks the financial industry is exposed to, which recently started to raise increased concern among European and international authorities, in terms of proper prevention, identification, assessment and management.It is an issue of utmost importance the more so that the financial landscape is continuously changing, to keep pace with the technological innovations applied to banking activity, digitization, large-scale use of internet banking/mobile banking.Cyber security risks are included in the broader framework of IT fraud; neglecting their careful monitoring would trigger serious financial and reputational implications for the financial industry.The paper synthesizes the guidelines and reports recently published by the International Monetary Fund, World Bank, Bank of International Settlements, European Central Bank, European Commission, big-four audit companies as well as research centres, to illustrate which is their response to the digital environment trend and cyber security challenge.Then, it reviews the main typologies of threats included in the cyber security risk, graphically depicts the perceived exposure to cyber risks in comparison with other categories of risks, delineates between key risks and emerging risks, and discusses the risk management responsibilities to be assigned to bank's board, operational management, risk/internal control/compliance oversight function and internal audit function (known also as the three lines of defence).
ACRL in Washington, D.C.: ACRL programs at the ALA Annual Conference

ALA’s 138th Annual Conference was held June 20–25, 2019, in Washington, D.C. More than 21,400 librarians, library support staff, exhibitors, writers, educators, publishers, and special guests attended the conference. Ed. note: Thanks to the ACRL members who summarized programs to make this report possible.
A Graphical Evaluation Tool to Utilize ECG Data without Reference Annotation

Without reference annotation, statistical metrics such as sensitivity and positive predictive value (PPV) cannot be calculated.Annotating a large ECG database may not be feasible, hence, the interest in developing an evaluation tool that does not require reference annotation.We developed a tool for evaluating key performance attributes (KPA) including arrhythmia detection, heart rate, ST value, and noise tolerance.The tool has three layers of KPA graphics.The top layer includes interactive distribution graphs of the KPA values for aggregated results for the entire database.From this top layer the user can select an individual record to launch interactive trending graphs that display the KPA values, or their discrepancies, for a time span on that particular record.From this second layer the user can identify any KPA value of interest (e.g., a specific arrhythmia label) to view the underlying ECG waveform.Navigating through these three layers, the user is able to quickly confirm the validity of KPA reported by the algorithm.We modified the noise tolerance of an exercise ECG arrhythmia algorithm.Then used this tool to visually verify the resulting improvement on the Telemetric and Holter ECG Warehouse (THEW) stress database E-OTH-12-0927-015.We confirmed the visual verification of improvement by manually annotating a small subset of records in this database.
IoT Based Image Processing Filters

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing image processing algorithms and the result of the processing is an image with black and white for edge detection and Thresholding models and gray color image for gray enhancement model.
SISTEM INFORMASI PREDIKSI MAHASISWA PUTUS KULIAH MENGGUNAKAN METODE DATA MINING DENGAN ALGORITMA CHAID

College life cannot be separated from problems faced by students. This problem is one of the obstacles in completing the study. Droped out students are detrimental to higher education institutions because it will reduce the performance index and harm the students themselves. The purpose of the research is to produce a prediction system for students who will drop out of college using data mining by processing data from ITB Swadharma for the period 1992 to 2019 and modeling using the Chaid algorithm, the results are visualized with the tableau application. The results of the study reveal the fact that the study time is the main factor that influences the prediction of dropout students with a chi-square value of 15,714, factor of accreditation status with a chi-square value of 16,874, gender is the factor with a chi-square value of 5.292.
Cleaning Sensor Data in Intelligent Heating Control System

Sometimes, smart heating control applications are partially equipped with missing values and outliers in the sensor data due to software/hardware failures/human errors. To provide an effective analysis and decision-making, erroneous sensor data should be cleaned by imputation of missing values and smoothing outliers. In this paper, we present a case of the Smart Heating Control System (SHCS) installed in the South Ural State University, and describe the structure and development principles of Data Cleaning Module (DCM) of the system. We implement DCM through data mining and neural network technologies as a set of the following subsystems. The preprocessor extracts raw data from the system's data warehouse and prepares a training data for further processing. Predictor provides Recurrent Neural Network (RNN) to forecast the next value of a sensor based on its historical data. Reconstructor determines if the current value of a sensor is an outlier, and if so, imputes it by the synthetic value from Predictor. Finally, Anomaly Detector subsystem discovers anomalous sequences in the sensor data. In the experiments on the real sensor data, DCM showed relatively high and stable accuracy as well as adequate detection of anomalies.
STIMULASI SPASIAL-VISUAL DENGAN BUILDING SIMULATOR GAME ANAK USIA 5 TAHUN

Game play at this time can no longer be avoided, both by adults and children, the reasons for playing games are diverse ranging from filling spare time to eliminate the boredom experienced by humans at different age levels. So that game play does not only end with activities that are not useful, then as an adult must direct that the game play can be useful and used as a stimulating tool for children and can improve children's spatial-visual intelligence. This research was conducted on a child who is five years old, by conducting research using a game on a smartphone, the Building Simulator Game, which is specialized in Block Craft 3D level 1. The activity carried out is collecting data by exploring the ability of children in game play, doing observation and directly involved in directing children to play games. In stimulating spatial-visual intelligence with Building Simulator Games there are a number of children aged 5 years. First: determine the simplest building simulator game, Second: introduce block-shaped block media, Third: choose the type of building to be made, Fourth: Block Craft 3 D consists of level 26, but researchers only introduce children to level 1 according to their abilities. With the Block Craft 3 D game, it is expected that spatial-visual stimulation will be beneficial for children in the future
Trusted and Efficient Request Processing Using Packet List on Cloud

Distributed computing information is put away over the dispersed servers, which can be gotten to with the assistance of client questions. In distributed computing, a large number of client inquiries are handled by circulated server with less dormancy, high accessibility and high dependability. Be that as it may, giving privacy client inquiries is as yet a testing undertaking because of the high defenselessness exist in the cloud condition. The current components experience the ill effects of high computational and correspondence overhead, notwithstanding vulnerabilities still exists in their security instruments. In our proposed methodology, any client sends the spatial inquiries to the specialist co-op, at that point the specialist co-op utilize these spatial questions to keep an eye on the spatial scrambled information. Client utilizes the RC5 key to decode the reaction messages. In this whole procedure, clients can shield the information from the information spillage, diminishes the correspondence overhead when contrasted and other existing systems.
Descriptive Analytics on Crime in India using Clustering Techniques

Understanding the perspectives of crime happenings by exploiting crime data helps early detection and prevention of crimes. Ruling Government and Policing systems are aware the importance of realising the changing aspects of crime. As technology is advanced, there are many ways to comprehend the trends and the patterns of crime activities. The paper presents a hybrid model using AGNES and K-means clustering algorithms to focus on different views and representation of crime in India and aims to recognize the crime types that cluster the regions of India. Accuracy of model is measured using log loss and the patterns and trends in crime are presented.
A Study on the Impact of Total Quality Human Resource Factors On Organizational Engagement in Reliance Jio, Chennai

Employee engagement is one of the key factors that is needed for a dynamic industry like telecommunication in India. The attrition rate of the sector is a high post Jio impact. Hence the alternate of human resource practices, total quality human resource management variable are taken up for the study. TQHRM is the addition of TQM concepts in HRM practices. Therefore, TQHRM practices and employee engagement are key latent variables considered for the study. The present research involved an investigation on a sample of 159 employees Reliance Jio Company usingquestionnaires.All the data were analysed applying appropriate statistical tools by using SPSS 24.0.In our study it is found that there is a significant influence of TQHRM practices (p-value less than 0.05) on organizational engagement.