Reviewerly/exHarmony huggingface dataset:
Pelatihan Editing Video Guru SMK Walisongo Dengan Adobe Premier

The development of technology in this modern era is very fast, currently technology has provided many benefits in advancing in various aspects. This development is not only in a matter of years, months or days, but hours, even minutes or seconds, especially in relation to information and communication technology supported by electronic technology. The use of technology by humans to help complete work is a necessity in life. The development of this technology must also be followed by developments in Human Resources (HR). The concept of service will teach vocational teachers who have minimal knowledge in the field of video editing. The video editing training with Adobe Premiere is expected to be a learning tool to create content for the learning of Walisongo Vocational School teachers. This training activity is carried out at the Walisongo Vocational School Lab and is supported by a question and answer session, a practicum module will also be given to each training participant. The purpose of implementing this community service is to increase the creativity of the Walisongo Vocational School teachers who will create learning content for their students. From the implementation of community service, it is hoped that it can improve skills and creativity by using Adobe Premiere software, so that later when they create interactive and interesting learning content, either making videos to be given to students or uploaded on YouTube and they can have an in-depth understanding of multimedia, especially the field. video editing with adobe premiere.
Characteristics of induced seismicity during hydraulic stimulations

&amp;lt;p&amp;gt;Near-realtime seismic monitoring of fluid injection allowed control of induced earthquakes during the stimulation of a 6.1 km deep geothermal well near Helsinki, Finland. The stimulation was monitored in near-real time using a deep seismic borehole array and series of borehole stations. Earthquakes were processed within a few minutes and results informed a Traffic Light System (TLS). Using near-realtime information on induced-earthquake rates, locations, magnitudes, and evolution of seismic and hydraulic energy, pumping was either stopped or varied. This procedure avoided the nucleation of a project-stopping red alert at magnitude M2.1 induced earthquake, a limit set by the TLS and local authorities. Our recent studies show that the majority of EGS stimulation campaigns investigated reveal a clear linear relation between injected fluid volume, hydraulic energy and cumulative seismic moments suggesting extended time-spans during which induced seismicity evolution is pressure-controlled. For most projects studied, the observations are in good agreement with existing physical models that predict a relation between injected fluid volume and maximum seismic moment of induced events. Some EGS stimulations however reveal unbound increase in seismic moment suggesting that for these cases evolution of seismicity is mainly controlled by stress field, the size of tectonic faults and fault connectivity. Transition between the two states may occur at any time during injection, or not at all. Monitoring and traffic-light systems used during stimulations need to account for the possibility of unstable rupture propagation from the very beginning of injection by observing the entire seismicity evolution in near-real-time and at high resolution could possibly provide a successful physics-based approach in reducing seismic hazard from stimulation-induced seismicity in geothermal projects.&amp;lt;/p&amp;gt;
Complexity of the TDNN Acoustic Model with Respect to the HMM Topology

In this paper, we discuss some of the properties of training acoustic models using a lattice-free version of the maximum mutual information criterion (LF-MMI). Currently, the LF-MMI method achieves state-of-the-art results on many speech recognition tasks. Some of the key features of the LF-MMI approach are: training DNN without initialization from a cross-entropy system, the use of a 3-fold reduced frame rate and the use of a simpler HMM topology. The conventional 3-state HMM topology was replaced in a typical LF-MMI training procedure with a special 1-stage HMM topology, that has different pdfs on the self-loop and forward transitions. In this paper, we would like to discuss both the different types of HMM topologies (conventional 1-, 2- and 3-state HMM topology) and the advantages of using biphone context modeling over using the original triphone or a simpler monophone context. We would also like to mention the impact of the subsampling factor to WER.
SISTEM KONSULASI PENYAKIT KULIT PADA DOMBA MENGGUNAKAN METODE NAÏVE BAYES

Sheep is a grazing animal. In raising sheep, sheep breeders on average have less knowledge in terms of skin diseases that attack their domestic sheep. Consultation system of skin diseases in sheep is used to help an expert or expert in diagnosing diseases in sheep based on existing symptoms. The purpose and benefits of consulting skin diseases in sheep, among others, is to facilitate and speed up knowing the types of skin diseases that attack sheep. To find out sheep disease, researchers made a consultation system by applying the naive bayes method. Consultation of skin diseases in sheep using the Naive Bayes method. In this study the type of skin disease that can be diagnosed as many as 5 diseases. with an accuracy rate of 100%. The conclusion of the research that has been done based on the problems that have been resolved through the creation of this consultation system is a consultation system to determine skin diseases in sheep designed by the naive Bayes method.
Effect of Functional Motivations of Volunteers on Participation Satisfaction and Sustainability

The purpose of this study is to identify the effects of the functional motivations of volunteers on participation satisfaction and sustainability.The study was conducted on 198 volunteers in Seocho-gu, Seoul.For the analysis method, frequency analysis, reliability analysis, and correlation were performed using the SPSS 22.0 program, and regression analysis was performed on causality among variables.The study found that the functional motivations for volunteers to do volunteer work have a significant effect on their satisfaction with volunteer work.Second, the functional motivations for volunteers to do volunteer work have been found to have a positive effect on the sustainability of volunteer work.This can be said to be a positive tool in increasing the level of participation satisfaction, will to continue, and intensity for participation in volunteer work, such as self-protection, value-seeking, and social skills, which are the functional motivations for volunteers to do volunteer work.Therefore, it is thought that this study will be the basis for preparing programs to satisfy volunteers' participation in volunteer activities and to enhance their sustainability.
Data Mining Power Determination Nurses Sultan Sulaiman Hospital With C4.5 Algorithm

The hospital is an agency engaged in health services in the which there are a number of special professions that can provide health services to the community items, namely doctors, Midwives and nurses and other professes. In this discussion, Arise and problems that can be raised into case studies to find out the results and information of each process in data mining Carried out with the C4.5 algorithm items, namely nurses. However, there are Several obstacles to Determine the nurses who will be declared passed or failed and accepted to work and can provide health services to the community, especially Patients who come for treatment. Therefore we need a method to identify nurses in a hospital. Data Mining with c4. 5 Algorithm can be used to the make predictions or classifications of nurses who are eligible to perform health services in hospitals by making decision trees based on existing data. This study aims to apply the data mining algorithm C4.5 in Determining nurses based on four attributes of used items, namely Accreditation, GPA, Age, and the value of each criterion has been determined in advance. The results of the study in the form of a decision tree Obtained from the data mining process with the C4.5 algorithm will provide information on the determination of nurses in the Sultan Sulaiman Regional Hospital.
An Analysis of Challenges and Trends in Digital Library

In the course of recent years, libraries all through the world have been in a condition of change because of the effect of data innovation. No territory of the library has stayed unblemished. The effect on assortments, administrations, staff, and offices has had significant consequences on spending plans, arranging, and preparing. Along these lines, the idea of an advanced library has come. It centres around access and administration not on structures and volume. Libraries should hold up users in their looking and obtaining of data and their association will reflect the administrations as opposed to a physical area. Innovation, law and financial matters are for the most part getting increasingly significant for libraries who are requiring library staff. Maybe the most significant issue for the long haul will be the ability of libraries to co-work in the conveyance of the new administrations. The library is a centre of instructing and learning exercises where understudies, specialists and instructors can investigate the huge assets of data accessible . The conventional library users possess to burn through more effort for looking through a little snippet of data and for which they need to only rely upon library staff. Yet, in the period of data and correspondence innovation, the PCs are being utilized for everyday housekeeping exercises of the library which spares the user and the library expert's significant measure of time. This forestalls replication of work and empowers the smooth and successful lead of the library.
Health and Wellness Monitoring Using Intelligent Sensing Technique.

This work develops a monitoring system for the population with health concerns. A belt integrated with an on-body circuit and sensors measures a wearer’s selected vital signals. The electrocardiogram sensors monitor heart conditions and an accelerometer assesses the level of physical activity. Sensed signals are transmitted to the circuit module through digital yarns and are forwarded to a mobile device via Bluetooth. An interactive application, installed on the mobile device, is used to process the received signals and provide users with real-time feedback about their status. Persuasive functions are designed and implemented in the interactive application to encourage users’ physical activity. Two signal processing algorithms are developed to analyze the data regarding heart and activity. A user study is conducted to evaluate the performance and usability of the developed system.
Research on the Application of Virtual Classroom in Computer Online Education

Computer; Online education; Virtual classroom; Live broadcast
On Stochastic Fitness Landscapes: Local Optimality and Fitness Landscape Analysis for Stochastic Search Operators

Fitness landscape analysis is a well-established tool for gaining insights about optimization problems and informing about the behavior of local and evolutionary search algorithms. In the conventional definition of a fitness landscape, the neighborhood of a given solution is a set containing nearby solutions whose distance is below a threshold, or that are reachable using a deterministic local search operator. In this paper, we generalize this definition in order to analyze the induced fitness landscape for stochastic search operators, that is when neighboring solutions are reachable under different probabilities. More particularly, we give the definition of a stochastic local optimum under this setting, in terms of a probability to reach strictly improving solutions. We illustrate the relevance of stochastic fitness landscapes for enumerable combinatorial benchmark problems, and we empirically analyze their properties for different stochastic operators, neighborhood sample sizes, and local optimality thresholds. We also portray their differences through stochastic local optima networks, intending to gather a better understanding of fitness landscapes under stochastic search operators.
Extractor Lower Bounds, Revisited

We revisit the fundamental problem of determining seed length lower bounds for strong extractors and natural variants thereof. These variants stem from a change in quantifiers over the seeds of the extractor: While a strong extractor requires that the average output bias (over all seeds) is small for all input sources with sufficient min-entropy, a somewhere extractor only requires that there exists a seed whose output bias is small. More generally, we study what we call probable extractors, which on input a source with sufficient min-entropy guarantee that a large enough fraction of seeds have small enough associated output bias. Such extractors have played a key role in many constructions of pseudorandom objects, though they are often defined implicitly and have not been studied extensively.Prior known techniques fail to yield good seed length lower bounds when applied to the variants above. Our novel approach yields significantly improved lower bounds for somewhere and probable extractors. To complement this, we construct a somewhere extractor that implies our lower bound for such functions is tight in the high min-entropy regime. Surprisingly, this means that a random function is far from an optimal somewhere extractor in this regime. The techniques that we develop also yield an alternative, simpler proof of the celebrated optimal lower bound for strong extractors originally due to Radhakrishnan and Ta-Shma (SIAM J. Discrete Math., 2000).
Review of Logic and Set Theory

The natural sciences are unavoidably led to incorporate numbers and therefore mathematics. Mathematics, in turn, is based upon the derivation or deduction of properties or propositions with respect to given objects or elements belonging to a given set. The process of derivation/deduction of properties/propositions is called logic. The general properties of elements and sets is called set theory. In this chapter, we will present basic elements of logic and basic elements of set theory that we will be applying in the study of real numbers.
Effect of Human Resource Practices on Employee Retention in Public Universities in Kingdom of Saudi Arabia

As nursing schools embrace e-learning during and beyond the COVID-19 crisis, academic nursing institutions must first assess the attitude or perception of students to achieve successful transition and transformation to e-learning.However, there is limited information about the psychometric properties that measure the attitudes towards e-learning among nursing students in the Philippines.The objective of the study is to determine the validity and reliability of the attitudes towards e-learning scale Filipino nursing students.This descriptive cross-sectional study included 111 Filipino nursing students in selected public and private universities were selected through purposive sampling.The attitude toward e-learning scale was assessed for construct validity through exploratory factor analysis using varimax rotation and internal consistency reliability using Cronbach's á and -item-total correlation.The nineitem attitude towards e-learning scale was loaded on one component with factor loadings ranging from -0.907 to 0.893, explaining 61.92 percent of the total variance.The KMO test revealed a value of 0.900, while Bartlett's test was 644.380 (df =55, p=0.000).The corrected item-total correlation of each item varied in between 0.409 to 0.854, and the Cronbach's alpha coefficient of the 9-item scale was 0.917.The 9-item instrument was valid and reliable in assessing the attitude towards e-learning among nursing students.Further studies should be done in order to test it among varied health science students.
The Challenge for Practitioners to Adopt Requirement Prioritization Techniques in Practice

Background: Requirements prioritization and its technique is still an important research topic. However, industry adoption of its techniques is still lack of research and has many challenges. As we ...
Projection of the corpus for the speech recognition service from standard French to French regional accents in field of French media

Standard French means French pronounced without any regional accent and whose syntax, morphology and spelling are described in dictionaries, grammar books and textbooks. Although standard French is taught at school and used in written communication, administrative documentation and Radio/TV national channels, most of regional and local Radio/TV channels as well as specific shows promoting touristic areas can typically carry out regional French accents. In this work, we focus on the problem of speech recognition service for the French media. Our goal is to build useful resources to extend language models that can be used in speech recognition APIs. Over the past few years, the APIs for automated speech recognition (ASR) are playing an increasing crucial role for a variety of media applications. In this paper, we present a lightweight open source framework STT-FTV that allows users to easily connect 4 different ASR tools to be trained with different French regional accents. The speech corpus has been collected and transcribed from various TV and radio contents especially fit in order to represent the major differences with the standard French. This STT-FTV system offers a relative reduction of the Word Error Rate in the context of regional accent transcription.
Configuring a Hybrid Taxonomy with SharePoint Server 2019

Managed metadata is one of the useful service applications in SharePoint. Primarily it supports setting up a taxonomy for representing hierarchical business information. It also supports setting up a content type hub that centralizes the content types used across the sites.
Different Tools for Implementing ML Algorithms in Data Mining Tasks

In this paper I would like to discuss about the different tools which can be used for implementing machine learning algorithms for the tasks in data mining using java, etc.There are various tools which are available as open source or for free to use for executing or implementing various algorithms depending up on our project requirement.We are discussing about various machine learning tools here, about the features of each tool, about various algorithms related to each tool, the languages they support, the flexibility, the pros and cons of each tool, the cost if any etc.The main objective of this paper is to how efficiently and effectively we have to choose the tools for implementing or executing or deploying applications depending up on our requirement based on their features of the tools.
Modularity by Design for Safety-Critical Software Systems

Simplicity is about subtracting the obvious and adding the meaningful.- John MaedaA sentence which describes exactly the goal of this work. But why is simplicity a desirable goal in the first place? To understand this, we investigate how Consumer-Grade Software Systems (CGSS) have evolved over the past decades in terms of complexity. A subsequent comparison with Safety-Critical Software Systems (SCSS) shows that these lag behind the CGSS by about 5-10 years. The complexity of these systems increases to such an extent that they are no longer controllable with the previous methods, languages and tools and therefore new methods, languages and tools were invented to master this complexity again. Hereby, simplicity is the groundbreaking goal and in most cases this simplicity is achieved by abstraction and encapsulation.Therefore, in this thesis we show how to build on the observed developments in CGSS to bring about improvements for SCSS. We use an oppinionated approach which already specifies the methods, languages and tools to use in order to provide a better overall workflow and developer experience. We show how to start with a semantically well-defined modeling language to generate standardcompliant high-level language code for SCSS. Thereby, reducing the time spentfor recurring and error-prone tasks regarding the writing of timing-, structure-, and communication-related code. The only task a programmer then is left with, is the writing of business logic which corresponds exactly to the aforementioned quote about simplicity.Subsequently, we add modularity by design on top of the aforementioned approach in order to provide better maintainability of the generated systems. This is achieved by reusing an existing modularity framework on top of the chosen high-level language. Thereby, enabling a developer to also use additional benefits of this framework, like predefined, modular services and a well-defined lifecycle that can be reused to achieve even more abstract goals, like mapping modes of the modeling language to runtime reconfigurable modules in code.Finally, we complement the existing approaches with additional compile- and runtime checks in order to enable a developer of a SCSS to easily show semantic equivalence of exchanged or newly added modules to existing modules in a generated system.All approaches are evaluated via a qualitative and quantitative evaluation. The qualitative evaluation uses a running example based on a real-world quadrocopter autopilot, whereby the quantitative evaluation makes heavy use of Java Microbenchmark Harness (JMH) benchmarks in order to compare our approaches with a handwritten solution as well as comparing the approaches among themselves.
Algoritmos, afinal, o que são?

Resumo: Este artigo aborda o tema dos algoritmos. Nos ultimos anos houve uma verdadeira proliferacao de sistemas e produtos baseados em inteligencia artificial, contudo, ainda nao se tem muito claro a definicao quanto a sua estrutura algoritmica, que e a base dos sistemas de inteligencia artificial, e necessario entender minimamente o que sao algoritmos, para assimilar melhor o contexto da sua utilizacao. O metodo utilizado foi o fenomenologico hermeneutico. A tecnica de pesquisa foi a bibliografica, em fontes secundarias. Palavras-chave: Algoritmo, Sistemas de Inteligencia Artificial, Base de dados, Linguagem, Programacao. Abstract: This article addresses the theme of algorithms. In recent years, there has been a real proliferation of systems and products based on artificial intelligence, but it is not yet clear how much their algorithmic structure, which is the basis of artificial intelligence systems, is minimally understood or which algorithms, for assimilate the context of its use better. The method used was the phenomenological hermeneutic. One research technique was bibliographic, in secondary sources. Keywords: Algorithm, Artificial Intelligence Systems, Database, Language, Programming.
อิทธิพลของสื่อสังคมออนไลน์ที่มีต่อความพึงพอใจของลูกค้าตลาดนัดเซฟวัน จังหวัดนครราชสีมา|THE INFLUENCE OF SOCIAL MEDIA ON CUSTOMER SATISFACTION OF THE SAVEONE MARKET, NAKHON RATCHSIMA

The objective of this research is to examine the relationship between effects of social media and customer satisfaction in the Saveone market, Nakhon Ratchasima. This research was conducted using quantitative approach by collecting questionnaires from 400 people. Number of customers was being selected by simple random sampling. This research analyzes the data using descriptive statistics method and multiple regressions for hypotheses testing. The results demonstrate that social media (Facebook and YouTube) a significant and positive effect on customer satisfaction. The study indicate that executives of business can implement and should understand social media in order to communicate effectively and fulfill customer needs. Therefore, managers have to keep themselves updated about what customers are interested, offers advantageous campaigns, and offers prevalent contents. However, conclusion and discussion include directions for future research are discussed in the last section of this research.