Reviewerly/exHarmony huggingface dataset:
Demonstration of subjective sound preferences and jury studies in product noise control using countertop blenders

Developing consumer products requires consideration of product noise. Product noise control is usually not as simple as measuring and reducing the sound pressure level as much as possible. For example, consumers will not purchase vacuum cleaners if they are too quiet because of a perception that they do not function as well as louder models. This demonstration uses three countertop blenders to teach students about subjective acoustics and jury studies. The demonstration will start with a blind acoustic comparison of three blenders and the audience will be asked for opinions on the blenders, based on sound alone. Those opinions will be compared to overall measured sound pressure levels, product costs, and product performance criterion. This demonstration is ideal for an introductory noise control course, or for community outreach as it is easily relatable for any level of audience, from K–12 to adults.
Tracking and Grasping of Moving Objects Based on Proximity Sensors Mounted on Fingertips of Multi-fingered Robot Hand

In this paper, we propose a grasping strategy that grasps an approaching object whose position and shape are unknown using a robot hand and a robot arm equipped with a proximity sensor at the fingertip. As a grasping strategy, pregrasping, following, preshaping, and grasping motion necessary for grasping the moving object were created based on a torque control base, and the target joint torque output at the time of each motion was weighted and added. The robot hand and arm movement is generated by the output. It is thought that by gradually changing the weight of each motion in a series of grip control, seamless motion switching is possible, and an appropriate grasping motion is generated.
Keterampilan Belajar Mahasiswa di Masa COVID-19

Student must be have study skill, for study and increase achievement study. This research was based on various problems were still many students who have not had a good study skill . The purpose of this research is to describe internet use for study skill. This research used a quantitative method of descriptive. The population of this research were students in IAIN Takengon. The sample of this research amount to 44 students, that selected by using random sampling technique. The instrument of the research was a Likert Scale. Data is analyzed with descriptive statistic. The research findings show that  on general tudy skill is on quite well category.
The design and implementation of book lending system based on RFID technology

Abstract With the continuous enrichment of library collection resources and the expansion of service connotation and extension, the traditional integrated management system based on paper resources management can no longer meet the needs of the library’s continuous development. Therefore, the research and development of a new generation of library management system urgently needs to be put on the agenda. the library management and lending system have been already reformed. Finding the relevant literature, comparing and analyzing the previous research results. This paper introduce the design and implementation of RFID technology, including the advantages of the library lending system which established by RFID technology, and at the same time it puts forward the deficiency and the application prospect of the future RFID technology.
The influence of teacherâ€™s language impoliteness in triggering studentsâ€™ bullying behavior

The purpose of this study is to examine the influence of teacherâ€™s language impoliteness in triggering studentsâ€™ bullying behavior. The participants are the primary school students in Makassar by using purposive sampling approach. The participants are students who have bullying cases as a perpetrator in the last one month.Â Observation, in-depth interview, and questionnaire are used to collect the data. Data Analysis technique employed was simple linear regression analysis. This study shows that impolite language uttered by the teacher influences studentsâ€™ bullying behaviors. Students who are used to hearing these impolite utterances from their teachers tend to commit bullying behavior verbally at schools since they tend to consider this behavior as an acceptable behavior.
Road, Pendulum and Coil

This study offers an account of a research project focused on developing an integrated loop of influence between long distance barefoot running and drum set performance. Activities described include the creation of a new drumming vocabulary, and associated rhythmic developmental processes, generated as a means to perform rapid, layered multi-subdivision rhythmic forms that draw on organizational procedures including the use of rhythmic archetypes. In addition, this Chapter will describe forms of inter-disciplinary influence allowing for technical, aesthetic, procedural, and vocabulary development through an ongoing dialogue between two complementary physical practices. Developmental activities also include (a) the creation of an organizational system, that I have termed Split locs, allowing one to manipulate rhythmic micro-timing through the use of rhythmic archetypes, (b) an alternative rhythm/sticking vocabulary that I describe as Rhythmic Coils, and (c) an alternative model for producing rhythmic gaps within multi-subdivision phrase forms. The study also offers an overview of three creative projects emerging from the research period.
PENGEMBANGAN SISTEM INFORMASI AKUNTANSI PENGGAJIAN DI GRIYA KAIN TUAN KENTANG

The development of payroll accounting information System is focused on several problems, namely the payroll system is done manually, Data loss because there is no Backup and salary calculation is sometimes not appropriate. The purpose of computerized accounting information system is chosen because the system is more flexible and easy to use. The method that will be used in this activity is preliminary analysis, drafting the proposed implementation of analysis system, implementation of the analysis system and the preparation of report system analysis results. The implementation of this activity will involve lecturers majoring in accounting and scheduled for 5 months.
Automatic Detection of Security Misconfigurations in Web Applications

Improper configuration of web applications or servers can lead to various security flaws. Security misconfiguration is ranked number 6 on the OWASP top 10 2017 list, meaning it is a critical risk in web applications that web developers need to focus on. The exploitation of this kind of vulnerabilities can lead to exploitation of other severe vulnerabilities and complete compromise of web applications. In this paper, we collaborate with security experts from a web security company to propose a tool to detect security misconfigurations in web applications. Our proposed tool, BitScanner, can effectively identify misconfiguration issues in all web applications regardless of the platform and technology they are built. The proposed tool is to enable web developers to fix any misconfiguration issues in applications before deployment in real development scenarios. Evaluation results show that our proposed tool has higher detection coverage and avoids false positives.
Deep Learning for Human Action Recognition with Convolution Neural Network

In recent years, deep learning for human action recognition is one of the most popular researches. It has a variety of applications such as surveillance, health care, and consumer behavior analysis, robotics. In this paper to propose a Two-Dimensional (2D) Convolutional Neural Network for recognizing Human Activities. Here the WISDM dataset is used to tarin and test the data. It can have the Activities like sitting, standing and downstairs, upstairs, running. The human activity recognition performance of our 2D-CNN based method which shows 93.17% accuracy.
idris-ct: A Library to do Category Theory in Idris.

We introduce idris-ct, a Idris library providing verified type definitions of categorical concepts.idris-ct strives to be a bridge between academy and industry, catering both to category theorists who want to implement and try their ideas in a practical environment and to businesses and engineers who care about formalization with category theory: It is inspired by similar libraries developed for theorem proving but remains very practical, being aimed at software production in business. Nevertheless, the use of dependent types allows for a formally correct implementation of categorical concepts, so that guarantees can be made on software properties.
Russian Higher Educational Export Strategies in Digital and Global Perspective

The purpose of this article is to determine the features of export development of Russian higher education at the level of a particular region, taking into account situations typical of ordinary regional universities and branches regarding the national policy to stimulate educational export and digital technologies use.The authors also substantiate the need for the development and adoption of measures aimed at solving interregional and interuniversity inequality problems taking into account financial and other resource opportunities of a given university.When writing the paper, we applied methods of system analysis which include comparisons, dynamic analysis, other methods of statistical analysis, a set of expert methods, including in-depth interviews, surveys, brainstorming, and SWOT analysis.The research results include the collection and processing of in-depth interviews with experts who are employees of international departments of universities of the Volgograd region, a survey of foreign students studying in regional universities and branches, on the basis of which the features of the implementation of the higher education export growth strategy by regional universities were determined and SWOT-analysis was conducted in order to identify risks and opportunities of regional universities and regional economy for educational export and its development.The authors' findings include justification of digital technologies growing role in increasing the accessibility of Russian higher education to foreign students, justification of high role of higher education export for the regional economy and developed measures for the strategic development of export of higher education on the example of a regional university.
A Comparative Study of PCA and LBP for Face Recognition Under Illumination Variations

Changes in lighting conditions are an important factor for facial recognition applications. The algorithms used in these applications have various approaches and are directly affected by environments under difficult lighting settings. In this study, we investigate two appearance-based local and global approaches, namely Principal Component Analysis and Local Binary Patterns algorithms, examine important studies on these algorithms and compare their facial recognition performances on images from the Extended Yale Face Database B. Experiments show that the LBP method provides better results under varying lighting conditions.
PENGEMBANGAN APLIKASI PENGENALAN RUMAH ADAT SUMATERA BERBASIS AUGMENTED REALITY

AbstractAugmented Reality (AR) is a technology that combines virtual objects into a real environment in real time. Augmented Reality is applied in various fields, one of which is in education as a learning medium. In this research, Augmented Reality technology is included in the fruit recognition book in early childhood with the aim of making this fruit recognition learning media for early childhood more interesting and interactive. The application is designed and then realized using functions in the ARTool Library for camera activation, tracking markers and displaying 3D virtual objects from the fruit on the markers contained in the fruit recognition book.
Enhancement of Mammograms with Periphery Brightness Compensation

Mammography is an effective way for early diagnosis of breast cancer. The enhancement of mammograms is essentially important for the diagnosis. This can be achieved by high-pass filtering and grayscale mapping. However, the details in the periphery of the breast may be lost because the breast is bright except its dark periphery in the mammogram. In this paper, we present a technique for the enhancement of mammograms with periphery brightness compensation. First, the image is decomposed into a base image and a detail image. Especially, the decomposition is adaptive such that no artifacts are made on the boundary of the breast in the detail image. Then, the periphery brightness is compensated by a Gamma correction in the base image, and the detail image is linearly amplified. Finally, the base image and the detail image are summed and mapped to obtain an image with significantly enhanced details, even in the periphery of the breast. Some experimental results indicate the effectiveness and the advantage of this technique.
Prediction of the Solar Resource through Differences

Experience shows that solar resource prediction is a difficult task. The available solar irradiance where a photovoltaic plant is located or is planned to be installed depends mainly on the cloud incidence at the site. This incidence of clouds depends on the climate system of the region, which is well known to be a non-linear, chaotic, and extremely complex, for which there is no exact mathematical model. In fact, the chaos level has been determined for various time series of wind and solar irradiance, and it turns out that the chaos level of the solar time series is greater than that of the wind series. This indicates that the complexity of solar irradiance prediction is considerable. In previous works of solar irradiance prediction, using Artificial Neural Networks, it has been observed that the trained models fail to predict irradiance spikes in conditions of intermittent cloudiness. By conducting a study in this area, we have found that, for a given date, there exist a model to determine the ideal solar irradiance in any geographical location of the planet. These models, so-called clear sky models, have been taken as a reference to predict not the solar irradiance, but the amount of irradiance occluded by the clouds. That is, the difference between ideal irradiance and that measured by the weather station. The proposed model is called SolarDiff, which predicts this difference using Artificial Neural Networks. This article empirically demonstrates that the SolarDiff model exhibits better behavior than models based on direct data. The performance, as in most forecast models, is measured by quantifying the forecast error. In this case the symmetric MAPE error is used.
One way quantum bit commitment using classical correlation and its implementation in IBM Q experience

Here, we develop a one way partial quantum bit commitment protocol using the states with built-in classical correlation, which are completely independent of entanglement. A procedure to enhance the security of the protocol is explicated.
The Effects of Reluctant and Fallible Users in Interactive Online Machine Learning

In interactive machine learning it is important to select the most informative data instances to label in order to minimize the effort of the human user. There are basically two categories of inter ...
Developing a cross-platform federated code repository for speech research

The increasing proliferation of code, scripts, and programming language libraries for use in speech science research raises concerns over the maintenance and organization of this disparate code base. These concerns have motivated us to explore the development a federated code repository under the umbrella of the Acoustical Society of America. Our primary goal for this repository is to serve as a central point from which researchers in the speech sciences can access code and data from the community that adheres to a set of established standards for documentation. The code will also be reviewed by other researchers for errors, vulnerabilities, and algorithmic misspecifications. Further, this repository will serve as a starting point for the future development of parallel libraries in open-source languages like R, Python, and Julia. In this talk, we will outline our plans for the repository and identify key open challenges and questions to be answered by contributors regarding repository structure, the code submission and review process, and documentation standards to adopt.
Black Box Model and Blockchain Technology

As the black box model of consumer behavior deals with the external factors that influence consumer resulting in different purchasing behaviour the application of blockchain technology will also influence the consumer similarly. This new trend will surely have a huge impact on the brand image, brand identity and brand impact.
Providing security to remote digital signature systems in case of semi-trusted secure environment

The task of providing security to remote digital signature systems (“cloud” signature) for cases of end user running client-side components on devices without potential of ensuring trusted environment (most common examples of such devices are smartphones with iOS or Android operation systems) is considered. This task has become particularly topical recently: users are used to performing (or at least confirming) their operations with smartphones, however, such usage of digital signature is still evolving.  Main issues and functional requirements are dealt with, ways to construct systems employing devices with cryptographic software running in weakly secure environment are discussed. The task of remote issuance of digital certificates is also considered: such a process can make completely remote usage of digital signature (from the very beginning, without even one personal appearance to a certification authority) possible. Taking functional and information security requirements into account, a scenario is developed in the current paper to solve the mentioned task.
AN ADOPTION OF 2D-PCA/ICA BASED POST-PROCESSING DIMENSIONALITY REDUCTION ALGORITHM FOR FACIAL RECOGNITION SYSTEM

Face images undergo considerable amount of variations in pose, facial expression and illumination condition. This large variation in facial appearances of the same individual makes most Existing Face Recognition Systems (E-FRS) lack strong discrimination ability and timely inefficient for face representation due to holistic feature extraction technique used. In this paper, a novel face recognition framework, which is an extension of the standard (PCA) and (ICA) denoted as two-dimensional Principal Component Analysis (2D-PCA) and two-dimensional Independent Component Analysis (2D-ICA) respectively is proposed. The choice of 2D was advantageous as image covariance matrix can be constructed directly using original image matrices. The face images used in this study were acquired from the publicly available ORL and AR Face database. The features belonging to similar class were grouped and correlation calculated in the same order. Each technique was decomposed into different components by employing multi-dimensional grouped empirical mode decomposition using Gaussian function. The nearest neighbor (NN) classifier is used for classification. The results of evaluation showed that the 2D-PCA method using ORL database produced RA of 92.5%, PCA produced RA of 75.00%, ICA produced RA of 77.5%, 2D-ICA produced RA of 96.00%. However, 2D-PCA methods using AR database produced RA of 73.56%, PCA produced RA of 62.41%, ICA produced RA of 66.20%, 2D-ICA method produced RA of 77.45%. This study revealed that the developed face recognition framework algorithm achieves an improvement of 18.5% and 11.25% for the ORL and AR databases respectively as against PCA and ICA feature extraction techniques. Keywords: computer vision, dimensionality reduction techniques, face recognition, pattern recognition
Corpora Compared : The Case of the Swedish Gigaword a Wikipedia Corpora

In this work, we show that the difference in performance of embeddings from differently sourced data for a given language can be due to other factors besides data size. Natural language processing ...
Penggunaan Metode Multiscale Retinex Untuk Peningkatan Bayangan dan Sorotan dengan Reflectance dan Iluminasi Citra

In an image there is an image that has a highlight and shadow. The shadow that is produced from an object is highlighted by the emitted light. In this case the picture shows an object that looks faint and looks not visible at all. In overcoming this, try to increase the highlights and shadows on the image. With the process of counting and being able to count objects with reflected, transmitted, or subjective light colors. To overcome this, input values ​​of red / green / blue and balanced lighting are needed for each pixel. By using the multiscale retinex method with the help of reflectance and illumination of the image in an increase in highlights and shadows. The results that can be done in this process produce a new image that has been improved from the previous image. Applications used in Enhancing highlights and shadows use the matlab application.
Power Micro-Blog Text Classification Based on Domain Dictionary and LSTM-RNN

The micro-blog texts of the national grid provinces and cities will be analyzed as the main data, including the micro-blogs and corresponding comments, which will help us understand the events of power industry and people’s attitudes towards these events. In this work, the data set is composed of 420,000 micro-blog texts. Firstly, the professional vocabulary of electric power is extracted, and these vocabulary are manually labeled, thus proposing a new field dictionary closely related to the power industry. Secondly, using the new power domain dictionary to classify the 2018 electric micro-blogs, and we can find that classification accuracy increased from 88.7% to 95.2%. Finally, a classification model based on LSTM (Long Short-Term Memory) and RNN (Recurrent Neural Network) is used to deal with the comments under the micro-blog. The experimental result shows that the classification of the LSTM-RNN is more accurate. The rate was 83.1%, which was significantly better than the traditional LSTM and RNN text classification models of 78.4% and 73.1%.
Public Response Analysis toward Poverty Reduction Program in Indonesia 2014-2018 through Twitter Data

Poverty reduction is the main priority of national development, it aims to encourage the improvement of the welfare of the poor in order to enjoy increasingly quality economic growth . But, every government program really needs an evaluation and how the response from the public. Social media monitoring can be used to understand and provide real-time feedback about policy reform. Therefore, government are expected to consider using similar technology in the current evaluation and operational framework. So they need tools to analyze the public response to poverty reduction programs in Indonesia by using Big Data through twitter data. With this research, it is expected that the public response from social media twitter can be a critique and suggestion for the government in establishing and implementing future poverty reduction policies. This research conducted to use twitter data on poverty reduction policies in Indonesia, such as: “Bedah Kemiskinan Rakyat Sejahtera(BEKERJA)” Program, “Padat Karya Tunai” Program, and “Program Keluarga Harapan”. Data are sourced from all community tweets related to the programs. There are analyzed using the text mining method. The results of this study indicate that in general the public response received and supported three poverty reduction programs in Indonesia for the 2014-2018 period. So public response can be used as an evaluation and input to the government.