Reviewerly/exHarmony huggingface dataset:
러시아 북극 주민의 사회ㆍ경제적 변화에 대한 인식 : 사하공화국 주민의 설문 조사를 중심으로

This study focuses on exploring socio-economic changes caused by environmental changes and industrial development in the Arctic and on analyzing the new perceptions of Russian Arctic residents, especially those of the republic of Sakha. First, the socio-economic changes of Arctic residents are summarized using existing research results and various statistical data. Then, based on the results of surveys on the residents of the Republic of Sakha, we looked at how Arctic residents perceive their socio-economic environment. According to various statistical data and survey results, the socio-economic situation and perceptions of the residents of the Republic of Sakha are not good. The socio-economic situation has not improved compared to the 2000s, and the residents of the Republic of Sakha are of course perceived negatively. In particular, the 25-34 age group, men, local residents, and other ethnic minorities, including Evenki, are the main groups with negative perceptions. However, the residents of the Republic of Sakha are evaluating highly themselves for their personal life satisfaction, optimism level, happiness level, and material evaluation level. In order to raise the quality of life of Arctic residents, residents of the Sakha republic point out that it is necessary to expand various welfare and subsidies by the state along with regional economic development. It is also necessary to support various socio-economic infrastructure, roads, medical care, and education. In particular, in relation to everyday life, wage increases, employment, and price cuts are the means to improve the quality of life that Arctic people most desire.
A Study on the Energy Reduction Measures of Data Centers through Chilled Water Temperature Control and Water-Side Economizer

The degree of integration of IT devices and consumption of cooling energy are consistently increasing owing to developments in the data center industry. Hence, to ensure the smooth operation and fault prevention of IT devices, the energy consumption of cooling systems has increased, leading to active research on improvements in cooling system performance for reducing energy consumption. This study examines the reduction in cooling energy consumption using a simulation by applying chilled water control and a water-side economizer (WSE) system to enhance the cooling system efficiency. The simulation results showed that the energy consumption was reduced by 1.8% when the chilled water temperature was set to 11 °C in a conventional system and by up to 19.6% when WSE was also applied. Furthermore, when the changes in chilled water temperature were applied for efficient operation of WSE, the energy consumption was reduced by up to 30.1% compared to that in conventional energy systems.
Long-term Person Re-identification: A Benchmark.

Existing person re-identification (Re-ID) works mostly consider a short-term search problem assuming unchanged clothes and personal appearance. However, in realworld we often dress ourselves differently across locations, time, dates, seasons, weather, and events. As a result, the existing methods are unsuitable for long-term person Re-ID with clothes change involved. Whilst there are several recent longterm Re-ID attempts, a large realistic dataset with clothes change is lacking and indispensable for enabling extensive study as already experienced in short-term Re-ID setting. In this work, we contribute timely a large, realistic long-term person re-identification benchmark. It consists of 171K bounding boxes from 1.1K person identities, collected and constructed over a course of 12 months. Unique characteristics of this dataset include: (1) Natural/native personal appearance (e.g., clothes and hair style) variations: The degrees of clothes-change and dressing styles all are highly diverse, with the reappearing gap in time ranging from minutes, hours, and days to weeks, months, seasons, and years. (2) Diverse walks of life: Persons across a wide range of ages and professions appear in different weather conditions (e.g., sunny, cloudy, windy, rainy, snowy, extremely cold) and events (e.g., working, leisure, daily activities). (3) Rich camera setups: The raw videos were recorded by 17 outdoor security cameras with various resolutions operating in a real-world surveillance system for a wide and dense block. (4) Largest scale: It covers the largest number of (17) cameras, (1082) identities, and (171K) bounding boxes, as compared to alternative datasets.
Artificial Intelligence Random Forest Algorithm and the Application

Random forest (RF) refers to a combined classifier of machine learning algorithms or a representative algorithm of integrated learning. Bagging algorithm is used to realize the integration of multiple decision trees and output results by voting, which has been well evaluated in industry and academia. This paper analyzes the random forest algorithm of artificial intelligence, hoping to provide a foundation for the subsequent optimization research of the algorithm.
Social Modality for the Success of Cimanuk River Flood Disaster Management in Garut Regency

Social Modality for the Success of Cimanuk River Flood Disaster Management in Garut Regency, is a study that aims to provide an overview of how the social modalities in handling post-flood Cimanuk River in Garut Regency, successes, shortcomings and strategies undertaken. This research uses qualitative research methods with an organizational case study approach. Qualitative case study research is a research strategy in which researchers carefully investigate a program, event, activity, process, or group of individuals (Creswell, 2016: 23). Researchers collect complete information using various data collection procedures based on a predetermined time. The results showed that social modality is one of the factors that support the success of post-cimanuk flood handling in Garut Regency. Therefore, social modalities are needed as a strategy in post-flood handling of the Cimanuk River in Garut district. It is also necessary to reform the institutional system during a disaster, before a disaster. To overcome this, several strategic steps are required.
LibGuides: Computing: Books

A guide for computing students bringing together information about all the books, journals and e-resources for your subject area How to find books for your courses
Grand Theft App: Digital Forensics of Vehicle Assistant Apps

Due to the increasing connectivity of modern vehicles, collected data is no longer only stored in the vehicle itself but also transmitted to car manufacturers and vehicle assistant apps. This development opens up new possibilities for digital forensics in criminal investigations involving modern vehicles. This paper deals with the digital forensic analysis of vehicle assistant apps of eight car manufacturers. We reconstruct the driver's activities based on the data stored on the smartphones and in the manufacturer's backend. For this purpose, data of the Android and iOS apps of the car manufacturers Audi, BMW, Ford, Mercedes, Opel, Seat, Tesla, and Volkswagen were extracted from the smartphone and examined using digital forensic methods in accordance with lawful government-approved forensics guidelines. Additionally, manufacturer data was retrieved using Subject Access Requests. Using the extensive data gathered, we successfully reconstruct trips and refueling processes, determine parking positions and duration, and track the locking and unlocking of the vehicle. These findings show that the digital forensic investigation of smartphone applications is a useful addition to vehicle forensics and should therefore be taken into account in the strategic preparation of future digital forensic investigations.
Modern approaches to the process of socialization of university students

The relevance of the research is determined by the socio-economic situation in modern society. Its specificity is caused by rapid development of information and communication technologies and the introduction of innovative methods in industrial practice. The result is an increase in the number and intensity of social contacts. Thus, the current specialists are required to possess not only professional competence, but also the ability to interact effectively with various social agents in a changing situation, to make responsible decisions, to combine personal and public interests, to execute civil duties and to function as a full-fledged member of society.in other words, be socially mature. The above-mentioned requirements are formulated in the social order presented in key normative documents: federal state educational standards regulating the functioning of the system of higher education. The novelty of the research lies in the development of a continuous- synergetic approach and establishing peculiarities of its realisation to the formation of university undergraduates’ social maturity. As a result, objective laws were revealed, principles were outlined, and the rules for the formation of university undergraduates’ social maturity were formulated from the point of view of the continuous-synergetic approach. The findings can be used to develop pedagogical technologies of its formation. Besides, process peculiarities of the formation of university undergraduates’ social maturity were revealed.
Curating geosciences data in the Earth, Space and Environmental Sciences &amp;#8211; new developments of GFZ Data Services

&amp;lt;p&amp;gt;GFZ Data Services is a domain repository for geosciences data that assigns digital object identifier (DOI) to data and scientific software since 2004. Hosted at the GFZ German Research Centre for Geosciences (GFZ), the repository has a focus on the curation of long-tail data on one hand, but also provides DOI minting services for several global monitoring networks/observatories in geodesy and geophysics (e.g. INTERMAGNET; IAG Services ICGEM, IGETS, IGS; GEOFON) and collaborative projects (TERENO, EnMAP, GRACE, CHAMP). Furthermore, as Allocating Agent for IGSN, the globally unique persistent identifier for physical samples, GFZ is providing IGSN minting services for physical samples.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;GFZ Data Services increases the interoperability of long-tail data through (1) the provision of comprehensive domain-specific data description via standardised and machine-readable metadata with controlled domain vocabularies; (2) complementing the metadata with comprehensive and standardised technical data descriptions or reports; and (3) by embedding the research data in wider context by providing cross-references through Persistent Identifiers (DOI, IGSN, ORCID, Fundref) to related research products (text, data, software) and people or institutions involved.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Visibility of the data is established through registration of the metadata at DataCite and the dissemination of metadata in standard protocols. The DOI Landing Pages embed metadata in Schema.org to facilitate discovery through internet search engines like the Google Dataset Search. In addition, we feed links of data and related research products into Scholix, which allows to link data publications and scholarly literature, even when the data are published years after the article.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The new Website of GFZ Data Services has further developed from a searchable data portal (only) to an information point for data publications and data management. This includes information on metadata, data formats, the data publication workflow, FAQ, links to different versions of our metadata editor and downloadable data description templates. Specific data publication guidance is complemented by more general information on data management, like a data management roadmap for PhD students, and links to the data catalogue of GFZ Data Services, the IGSN catalogue of GFZ and RI@GFZ &amp;amp;#8211; the data and research infrastructure search portal of GFZ.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Since October 2020, GFZ is a DataCite member. This membership will enable and promote active participation in the current and future venues of technological and service-oriented developments related to the persistent identification of research outputs.&amp;lt;/p&amp;gt;
Correlation Between Organizational Learning and Employee Productivity in the Gulf Cooperation Council (Correlación entre el aprendizaje organizacional y la productividad de los empleados en el consejo de cooperación del golfo)

This article attempts to examine the relationship between organizational learning and organizational learning in the Gulf Cooperation Council. The study was conducted through an empirical research design; a survey method was employed and the study population comprised 15 banks in Oman. The research believes that the result of this study may be inferred to all GCC member countries. The researchers find that there is a strong, statistically significant positive relationship between organizational learning and organizational performance. In conclusion, organizations that invest in organizational learning reported improved employee productivity in Omani Banking Industry.
An Efficient Method for Text Detection and Recognition in Still Images

Text Detection and recognition in general have quite a lot of relevant application milestones in various fields such as unmanned drone, defence vehicle, sign board detection, security surveillance, and even for unmanned driving. Text detection from blurred images due to environment weather is very challenging. The main aim of this paper is to identify and recognize the text in still images. Results demonstrated that the new adaptive algorithm could efficiently recognize the text even if the image is corrupted by high noise density. Also implementation of the proposed method is easy and less complex when compared to other methods. This paper shows how to split regions containing text in an image and how to detect the text. The automated text detection algorithm in this paper uses MSER regions and optical character recognition (OCR) is used to recognize the text. Here system detects the text and finds the connected regions, chain them together in their relative position. The result of multiple segmentation hypotheses are post-processed by a connected component analysis algorithm. This algorithm is applied to several sample images and proved that this method is more efficient.
Calculated Columns Using R and Python

A task that is difficult to do in Power Query is adding calculated columns that are based on complex mathematical formulas. That problem does not exist in R or Python. R was built by statisticians, so it was designed to perform complex statistical and mathematical calculations. The same holds true with Python. Python is not only used in data science but also in other computation-intensive fields such as engineering and physics. Like R, Python is optimized to be able to perform calculations that are not possible using M in Power Query. So, in situations where you need to add a calculated column based on a complicated computation in Power BI, you should consider leveraging R or Python. You will not only benefit from the fact that R and Python handle complex computations better but, in many cases, you may find that R and/or Python may have a pre-built function that does the heavy lifting for you.
On the Scaled Inverse of $(x^i-x^j)$ modulo Cyclotomic Polynomial of the form $\Phi_{p^s}(x)$ or $\Phi_{p^s q^t}(x)$

The scaled inverse of a nonzero element $a(x)\in \mathbb{Z}[x]/f(x)$, where $f(x)$ is an irreducible polynomial over $\mathbb{Z}$, is the element $b(x)\in \mathbb{Z}[x]/f(x)$ such that $a(x)b(x)=c \pmod{f(x)}$ for the smallest possible positive integer scale $c$. In this paper, we investigate the scaled inverse of $(x^i-x^j)$ modulo cyclotomic polynomial of the form $\Phi_{p^s}(x)$ or $\Phi_{p^s q^t}(x)$, where $p, q$ are primes with $p<q$ and $s, t$ are positive integers. Our main results are that the coefficient size of the scaled inverse of $(x^i-x^j)$ is bounded by $p-1$ with the scale $p$ modulo $\Phi_{p^s}(x)$, and is bounded by $q-1$ with the scale not greater than $q$ modulo $\Phi_{p^s q^t}(x)$. Previously, the analogous result on cyclotomic polynomials of the form $\Phi_{2^n}(x)$ gave rise to many lattice-based cryptosystems, especially, zero-knowledge proofs. Our result provides more flexible choice of cyclotomic polynomials in such cryptosystems. Along the way of proving the theorems, we also prove several properties of $\{x^k\}_{k\in\mathbb{Z}}$ in $\mathbb{Z}[x]/\Phi_{pq}(x)$ which might be of independent interest.
AN ANALYSIS OF TOEFL SCORE FOR ENGLISH DEPARTMENT STUDENTS OF STKIP YDB LUBUK ALUNG

The purposes of this research are (1) to know the relationship between the materials tested on TOEFL and those in syllabi of English department on related skill subject. (2) to show students TOEFL score, the last semester of English Department Student. The research used descriptive design by quantitative approach. The sample is 39 students of English department. Data are collected using various techniques (TOEFL test, documentation for syllabus). From the analysis, it is found that (1) there is a close relationship between the materials tested on TOEFL and those in English Department syllabi; (2) The student’s TOEFL score was proven by mean score 394-483, it was classified as moderate category
Organizational commitment as mediator of the relationship between job satisfaction and performance in the commercial banks in Sri Lanka-A study

The purpose of this study was to investigate the relationship among job satisfaction, organizational commitment and job performance of non-managerial employees in the commercial banks in Sri Lanka. The sample consisted of 400 non-managerial employees randomly selected from Systemically Important Banks. A questionnaire was administered among the non-managerial employees as the measuring instrument. The collected data were analyzed using correlation coefficient and simple regression. The results of the study indicated that there was a positive relationship between job satisfaction and job performance, job satisfaction and organizational commitment, organizational commitment and job performance. Organizational commitment was found to mediate the relationship between job satisfaction and job performance of non-managerial employees in the commercial banks in Sri Lanka.
숙달도를 고려한 한국어 교재의 주제별 어휘 목록 선정에 대한 연구

This study considered whether the vocabulary list of Korean level 3 textbooks is appropriate for the topics and mastery of the unit. The selected vocabulary list by topic possibly enhances the level of difficulty per unit. A list of vocabulary was chosen, based on the view of preceding studies that indicated that the words commonly included, may be essential to the topic. The study was limited to Korean level 3 textbooks published after 2010, and the vocabulary list for a total of nine types of textbooks was compiled. As a result, seven topics were commonly included in the third-level textbooks: Health, Weather, Love, Character, Travel, Job, and School Life. In this study, a vocabulary list was compiled of words that are contained in each topic. In addition, vocabulary and vocabulary lists were compared to the level of the International Standard Korean Language Curriculum that determines proficiency. As a result, select a list of vocabulary by subject , considering the requirements for mastery at level 3. The study revealed that although there are not many common vocabulary words for each topic that are suitable for Level 3 proficiency, a list of words with meaningful relevance can be selected through sub-topics. Further , it was suggested that a study of topic-specific lexemes was continuously needed to select a vocabulary that considered both proficiency and topic matter when selecting textbook vocabulary.
컨테인먼트형 데이터센터 최적 제어 알고리즘을 위한 열환경 예측모델 개발

Purpose: This study aimed at developing a temperature prediction model for a containment data center. The predictive model must be guaranteed with stability and accuracy in order to be used for real-time control. Therefore, statistical evaluation was conducted to verify the prediction performance of the proposed model. Method: The predictive models were developed using four representative machine learning algorithms. A thermodynamic based containment data center and cooling system were modeled by MATLAB & Simulink software. The initial and optimized models were evaluated by R2 and Cv(RMSE), and the model with the highest performance was applied to the simulation. Result: In the initial models, RF and ANN presented highest accuracy on R2 (0.89) and Cv(RMSE) (17.85%), respectively. After the optimization, ANN presented the best prediction performance on both R2 (0.99) and Cv(RMSE) (0.94%). The result supports the accuracy and stability of the ANN model to be used for real-time control, and based on which the optimal control algorithm will be developed on further study.
Comparison Analysis of Hand Gesture Recognition using Different Prediction Based Algorithm

In previous years, the issue of sign motion acknowledgment is happen on the grounds that it is hard to perceive the human hand motion by utilizing diverse calculation and by using device .So in this paper we explained different algorithm to explain gesture recognition algorithm because it has been gaining lots of attention. We can interact with computer without touch the computer screen using our hand gesture we can give instruction to computer so in this paper we explain about the detection of hands signed gesture using Kinect. We are using dynamic time warping method of gesture recognition. We explain an efficient method for gesture recognition. We also used easy K-NN classifier. In this method we used DTW (Dynamic Time wrapping) alignment. Using different algorithms and methods we are explain about the sign hand gesture recognition results. We used MPLCS algorithm to recognize hand gesture in free air and give good results after that we additionally utilized MCC calculation which have identify the beginning and end purpose of significant motion and overlook unused signals. So by using this algorithm we are giving our hand gesture reorganization results which are better than previous all results.
Joint-Conditional Entropy and Mutual Information Estimation Involving Three Random Variables and asymptotic Normality

A method of estimating the joint probability mass function of a triplet of discrete random variables is described. This estimator is used to construct the joint-conditional entropies and mutual information estimates involving three random variables. From there almost sure rates of convergence and asymptotic normality are established. The theorical results are validated by simulations.
E-FIR APP AND WEB PORTAL

The traditional ways of expressing oneself has changed a lot in recent times of pandemic. We are getting to observe an era that is transitioning to digitization. However, there are so many day to day events that still haven’t been revamped. They continue to be old fashioned. Thus we have made an attempt to digitize and automate one of the rights of citizen to speak up against wrong, that is, registration of FIRs. No matter how used to we are of this culture of reporting crimes and hideous actions, there are still some parts/people of our society that are restricted to do so. The primary motive of this application is to be able to reach common people just like technology and let them be able to stand up against such activities if they encounter any. This solution can help commoners report about illicit activities without needing to actually go to the police station.
Working with Files in Android

In this chapter, we will explore files in detail, including Android's methods for storing, retrieving, and managing data for your applications. In the following chapter, we will deal with the complementary tools around databases, which together with files represent a wealth of options for data management in your applications. We will also contrast these with Content Providers, Android's more sophisticated model for data access and management.