Reviewerly/exHarmony huggingface dataset:
MEMPERKUAT PERAN PUSTAKAWAN DALAM MEWUJUDKAN LAYANAN PERPUSTAKAAN PERGURUAN TINGGI YANG PRIMA DAN UNGGUL

&lt;p&gt;The establishment of the college library aims to support the achievement of the vision of the mission of higher education in implementing the Tri Dharma College, namely education, research, and community service. The role of the library in this regard include satisfying the information needs of academicians, providing library materials, provide study rooms, providing lending services and providing information services. Library is the heart of the college. Library as a source of information must be managed properly and professionally. To realize the excellent service and superior, then the college library services should beroreintasi on satisfaction and customer focus. For strengthening the role of the librarian, then the librarian skills and knowledge on the basics of the service must be improved through education, training, workshops, workshops and seminars, in order to achieve service excellence and superior library.&lt;br /&gt;There is also the strategy of librarians in strengthening its role in the realization&lt;br /&gt;of library services college superior and primed to consider several things, among&lt;br /&gt;others: (1) improving the competence of librarianship, (2) maintain the appearance, (3) confident, smiling, being friendly, and friends, (4) listen to each conversation and received no complaints with either, (5) speak the language properly and clearly, (6) enthusiastic in providing services and show the ability, (7) if it can not resolve the existing problems, can work together with other librarians.&lt;/p&gt;&lt;p&gt;Keywords: the role of librarians, college libraries, excellent service and superior&lt;/p&gt;
IDENTIFICATION THEORY AND ITS ROLE IN COPYCAT CRIMES

The reasons for the copycat crimes at the moment are a “white spot” in criminology. Theories explaining the origins of human behaviour can help in filling it out. Skinner’s and Bandura’s behavioristic theories explain the copycat process with the action of operant conditioning and the learning of aggression, respectively. Confronting the escape process from freedom is one of the reasons why a person can go against social norms and laws. These theories conclude in the cognitive theory of identification, which currently most extensively explains the mechanism of imitation, as well as is taking into concideration the influence of the media, an important actor in the mechanism of copycat crimes, on a person and vice versa.
Psychological features of communicative personality behavior in the Internet space

The article determines that belonging to one type or another of a person’s communicative behavior in the Internet space is determined by a specific ratio of psychological factors namely: a combination of cognitive, motivational, affective components of a person’s communicative behavior in the Internet space and the level of constructive-destructive behavior. The author proposes a typology of communicative behavior of a person depending on the type of cognitive distortion: destructive types of communicative behavior of a person in the Internet are based on cognitive distortions such as depreciation of the positive, mental filter, overgeneralization, dichotomous thinking, and catastrophization. The psychological characteristics of users conducting provocative activities on the network are investigated; prone to provocative online activities; ascribing to themselves the conduct of provocative activities in the network; not leading provocative online activities.
Stochastic Variational Inference via Upper Bound

Stochastic variational inference (SVI) plays a key role in Bayesian deep learning. Recently various divergences have been proposed to design the surrogate loss for variational inference. We present a simple upper bound of the evidence as the surrogate loss. This evidence upper bound (EUBO) equals to the log marginal likelihood plus the KL-divergence between the posterior and the proposal. We show that the proposed EUBO is tighter than previous upper bounds introduced by $\chi$-divergence or $\alpha$-divergence. To facilitate scalable inference, we present the numerical approximation of the gradient of the EUBO and apply the SGD algorithm to optimize the variational parameters iteratively. Simulation study with Bayesian logistic regression shows that the upper and lower bounds well sandwich the evidence and the proposed upper bound is favorably tight. For Bayesian neural network, the proposed EUBO-VI algorithm outperforms state-of-the-art results for various examples.
Dynamic Security Assessment of Small-Signal Stability for Power Systems using Windowed Online Gaussian Process

Due to the evolving nature of power grids and model uncertainty, the online stability assessment of electrical power systems is always a challenging problem. This paper aims to provide a theoretical framework for estimating the region of attraction for power systems in real time. By analyzing and learning the measurement data in a given time duration, a windowed online Gaussian process (GP) approach is developed to provide the real-time security assessment and quantify the uncertainty caused by measurement errors and dynamic evolution of power systems. In addition, the theoretical analysis is conducted to ensure the conference level of the estimated region of attraction. Finally, numerical simulations are implemented on a microgrid model with $9$ buses and $3$ generators to validate the proposed approach. The proposed online assessment approach contributes to improving the situational awareness of human operators, thereby taking remedial actions before the emergency.
AN ANALISYS OF STUDENTS’ COMPETENCE IN WRITING DESCRIPTIVE PARAGRAPH: A CASE STUDY AT THE SECOND YEAR STUDENTS OF SMA 1 PUJUT IN ACADEMIC YEAR 2018/2019

This research aims to know the An Analysis of Students’ competence in writing descriptive paragraph. The subject of this research has been 36 students of class at SMA 1 Pujut in academic year 2018/2019. The research design on one test of SMA 1 Pujut used the one sheet method. In this test the students had to write a descriptive paragraph. The author used the descriptive method for data interpretation. The research revealed a mean score of 53.47 at the test. In detail: the students’ competence in writing descriptive paragraph was fairly good (38.8%), good (13.8%), excellent (5.5%), poor (36.1%) and very poor (5.5%). In general, based on the result, the author concludes that the students’ competence in writing descriptive paragraphs was classified fairly good. It demonstrated that most of the students (80%) of class at SMA 1 Pujut were able to write descriptive paragraph using their own words as good possible.
Facial Expression Detection using Deep Neural Networks

Facial Expression conveys non-verbal communication, which plays an important role in acquaintance among people. The Facial Expression Detection system is an activity to identify the emotional state of a person. In this system, a captured frame is compared with trained dataset that is available in database and then state of the captured frame will be defined. This system is based on Image Processing and Machine Learning. For designing a robust facial feature descriptor, we apply the Xception Modelling Algorithm. Xception is a convolutional neural network that is trained on more than a million images from the ImageNet database. The network is 71 layers deep and can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many animals. As a result, the network has learned rich feature representations for a wide range of images. The detection performance of the proposed method will be evaluated by loading the data-set and pre-processing the images for feeding it to CNN model. Experimental results with prototypic expressions show the superiority of the Xception-Model descriptor against some well- known appearance-based feature representation methods. Experimental results demonstrate the competitive classification accuracy of our proposed method.
Felician University Libraries: Doctor of Business Administration: Seminal Works

This guide provides online tools and resources for students in the Doctor of Business Administration program.
PELAKSANAAN DAN FUNGSI PEMELIHARAAN ARSIP PADA DINAS KEARSIPAN DAN PERPUSTAKAAN DAERAH KABUPATEN MAMASA

This study aims to determine the implementation and maintenance functions of archives in the Regional Archives and Library Office of Mamasa Regency, as well as the factors that influence them. This study the author uses a descriptive qualitative approach that describes the reality of the events under study. The data used in this study are primary data and secondary data. The results showed that the implementation of records management policies in the Office of Archives and Library of Mamasa Regency had not been fully implemented. The factors that support the implementation of records management policies are strong commitment from the Regional Government, availability of equipment, Archival Guidelines, archival training, and provision of incentive officers. While the inhibiting factor is the procedure is too complicated, the lack of awareness and understanding of employees about the importance of the archive, the number of archival officers is still lacking, and the archive is still seen as a less attractive field. The archive management strategy that can be applied is the procurement of archives in the processing unit, the addition of archival officers in the archival unit, changes in the incoming mail control lines, the creation of archival storage schedules and the development of archive functional organizations.
Towards Good Practices for Multi-Person Pose Estimation

Multi-Person Pose Estimation is an interesting yet challenging task in computer vision. In this paper, we conduct a series of refinements with the MSPN and PoseFix Networks, and empirically evaluate their impact on the final model performance through ablation studies. By taking all the refinements, we achieve 78.7 on the COCO test-dev dataset and 76.3 on the COCO test-challenge dataset.
Irsyadul Murid Hisab Of The Beginning Islamic Lunar Month On Digital Falak Web-Based

Abstract:The development of astronomy in determining the beginning of the Islamic lunar month has occurred so rapidly, along with the sophistication of technology that makes it easy for users to get information. The digital falak web-based application was made by Ahmad TholhahMa'ruf an astronomy scholar from Islamic boarding school who presented the astronomy books. This web- based application displayed data and calculations in several books of astronomy inclusion including IrsyadulMuridbook. The research method used was qualitative with descriptive approach. The type of data used was library research. The results showed that the algorithm used in the early reckoning of Islamic lunar inIrsyadulMuridbook based on the digital falak web was different toIrsyadulMuridbook. The results of calculating the book IrsyadulMuridwith the digital falak web of celibacy were inappropriate which was done manually within the last 3 years making the results different. So, it could be concluded that the digital Falak web was inaccurate if it was used for rukyat data. Evaluation was necessarily needed, thus hisab(astronomical calculation) result in digital falak web-based would be equivalent to hisab in IrsyadulMuridbook. Keywords:digital falak web,Islamic lunar month,IrsyadulMurid.
Jeff Scovil's Selection of World-Class Mineral Specimens

All photographs by Jeff Scovil ALL OF THE SPECIMENS IN THIS PICTORIAL WERE SELECTED BECAUSE I CONSIDER THEM TO BE WORLD-CLASS. What makes a specimen world-class? There are a number of factors, not ...
An End-to-end Framework for Unconstrained Monocular 3D Hand Pose Estimation

This work addresses the challenging problem of unconstrained 3D hand pose estimation using monocular RGB images. Most of the existing approaches assume some prior knowledge of hand (such as hand locations and side information) is available for 3D hand pose estimation. This restricts their use in unconstrained environments. We, therefore, present an end-to-end framework that robustly predicts hand prior information and accurately infers 3D hand pose by learning ConvNet models while only using keypoint annotations. To achieve robustness, the proposed framework uses a novel keypoint-based method to simultaneously predict hand regions and side labels, unlike existing methods that suffer from background color confusion caused by using segmentation or detection-based technology. Moreover, inspired by the biological structure of the human hand, we introduce two geometric constraints directly into the 3D coordinates prediction that further improves its performance in a weakly-supervised training. Experimental results show that our proposed framework not only performs robustly on unconstrained setting, but also outperforms the state-of-art methods on standard benchmark datasets.
Enculturation of the Russian Youth in the Modern Digital Educational Environment

On the cusp of the 20 th and 21 st centuries, during the period of progressing globalization processes, all social institutions, including science and education, saw major changes. On the one hand, the transitivity of the modern society has influenced the changes in the system of social values and attitude to the information, a priori knowledge and university as the place of tits production and accumulation. On the other hand, the penetration of digital culture, containing new values and meaning of education has had a massive effect on the formation of certain patterns of subject-subject relations in the educational process. The purpose of this study was to explore the opportunities and risks associated with education of Russian students and to analyze social and axiological aspects of this process. In the course of our study we analyzed the differences between generations that are subjects of the educational process and presented key sociocultural characteristics of the student youth determining their approach to studies. The conducted analysis shows that as digital culture bearers Russian students adapt quickly to ongoing social and technological transformations/ as well as perceive and share the values of the academic community and future profession.
Digital Copies of Bibliographic Publications in the Structure of Information Resources of Federal National Libraries

Modern libraries have considerable information resources. Digital copies of publications, including bibliographic ones, are an integral part of information resources. The author studies the activity of the Russian libraries of Federal level on creation of digital copies of bibliographic editions, basing on the own library holdings. There are three national libraries — the Russian State Library, the National Library of Russia and the Presidential Library named after B. Yeltsin. The purpose of the study is to analyse the array of digitized bibliographic publications and to identify the place of digital copies of bibliographic publications in the information resources of the national libraries. The author considers the content of the electronic catalogues of these libraries by entering the same type of request. The article presents the results of study of the volume and content of electronic catalogues, obtained by the method of bibliographic keyword search. The author analysed the array of digital copies of bibliographic publications on various parameters — chronological coverage of digitized documents; language features; terms of access to electronic documents. The author notes that the priority is now given to the digitization of publications in the national language. The article presents the types of access to digital copies of bibliographic publications from the user’s point of view. The author considers the statistical data on the availability of digital copies of bibliographic publications in the collections of electronic documents and the presence of special electronic collections. The emphasis is made on the study of open access to digitized documents. The study revealed that the volume of digital copies of bibliographic publications in the national libraries is very small for the implementation of their inherent scientific and educational function; the access to bibliographic information resources is mostly limited. The author concludes that the level of availability does not meet expectations of the user; and Russian libraries should develop their activities to expand open access to bibliographic information resources.
Zero knowledge proofs for cloud storage integrity checking

With the wide application of cloud storage, cloud security has become a crucial concern. Related works have addressed security issues such as data confidentiality and integrity, which ensure that the remotely stored data are well maintained by the cloud. However, how to define zero-knowledge proof algorithms for stored data integrity check has not been formally defined and investigated. We believe that it is important that the cloud server is unable to reveal any useful information about the stored data. In this paper, we introduce a novel definition of data privacy for integrity checks, which describes very high security of a zero-knowledge proof. We found that all other existing remote integrity proofs do not capture this feature. We provide a comprehensive study of data privacy and an integrity check algorithm that captures data integrity, confidentiality, privacy, and soundness.
The expression of air quality in urban areas: going further on a Compositional Data Analysis approach

The quality of atmospheric air in large cities is a matter of great importance because of its impact on the environment and on the health of the population. Recently, measures restricting access of private vehicles to the centre of large cities and other measures to prevent atmospheric air pollution are currently topical (Hervada-Sala et al., 2018). The knowledge of air quality acquires special relevance to be able to evaluate the impact of those great social and economic measures. There are many indices to express air quality. In fact, quite every country has its own, depending on the main pollutants, they have as Plaia and Ruggeri (2011) pointed out. In general, all indices ignore the compositional nature of the concentrations of air pollutants and do not apply methods of Compositional Data Analysis; those indices also have some other weak points such as leak of standardized scale. A first approach applying Compositional Data Analysis methods has been developed in Jarauta-Bragulat et al., 2016. In the present work, we try to go some step further to improve the understanding and manageability of air quality. The air quality index proposed here takes into account the compositional nature of the data, it has an adequate correlation between input (concentrations) and output (air quality index), it distinguishes between air pollution and air quality and it has a 0-100 reference scale which makes easier interpretation and management of air quality expression. To illustrate the proposed method, an application is made to a series of air pollution data (Barcelona, 2001-2015).
CRIMINOLOGICAL TENDENCIES OF YOUTH CRIME IN LATVIA

In the age of risk society, the word “crime” is gaining more and more importance. Today’s rapid economic development, dynamic and rather controversial technological processes, which describe the current global environment, call for a more active response to crime as one of the top priorities. In recent years, criminal offences committed by young people, especially minors, are a priority issue for law enforcement authorities, society and the state. The term “youth crime” in criminology has been introduced relatively recently. This topic has been little studied in Latvia. The paper provides an insight into the criminological scope of youth crime. The author would like to launch a discussion on the criminological study prospect of youth crime in Latvia.The aim of the paper is to describe the phenomenon of youth crime by analysing the theoretical and practical aspects. The topicality of the study of the youth crimes’ criminological aspect is determined by the prevalence of this type of crime and the problems in identifying and prevention of it. Such tasks of the study are defined: to describe the criminological content of youth crime and to provide the criminological classification of a subject; to analyse its causes and circumstances contributing to it; to discover the content of criminological prevention. The study is based on the opinions and conclusions of scientists and different documents. Several methods of general scientific research and specific methods are used in the paper: monographic and constructive approaches, logical interpretation, statistical methods and the method of legal norms’ interpretation.The author concludes that youth crime is a complex, dynamic criminological phenomenon with certain regularities, which determine its formation and existence. The author acknowledges that criminological importance is got by early prevention measures, especially for young people whose behaviour manifests itself in a criminal inclination or takes place in a hostile or criminal environment.
Trend-responsive User Segmentation Enabling Traceable Publishing Insights. A Case Study of a Real-world Large-scale News Recommendation System

The traditional offline approaches are no longer sufficient for building modern recommender systems in domains such as online news services, mainly due to the high dynamics of environment changes and necessity to operate on a large scale with high data sparsity. The ability to balance exploration with exploitation makes the multi-armed bandits an efficient alternative to the conventional methods, and a robust user segmentation plays a crucial role in providing the context for such online recommendation algorithms. In this work, we present an unsupervised and trend-responsive method for segmenting users according to their semantic interests, which has been integrated with a real-world system for large-scale news recommendations. The results of an online A/B test show significant improvements compared to a global-optimization algorithm on several services with different characteristics. Based on the experimental results as well as the exploration of segments descriptions and trend dynamics, we propose extensions to this approach that address particular real-world challenges for different use-cases. Moreover, we describe a method of generating traceable publishing insights facilitating the creation of content that serves the diversity of all users needs.
Modal-aware Features for Multimodal Hashing

Many retrieval applications can benefit from multiple modalities, e.g., text that contains images on Wikipedia, for which how to represent multimodal data is the critical component. Most deep multimodal learning methods typically involve two steps to construct the joint representations: 1) learning of multiple intermediate features, with each intermediate feature corresponding to a modality, using separate and independent deep models; 2) merging the intermediate features into a joint representation using a fusion strategy. However, in the first step, these intermediate features do not have previous knowledge of each other and cannot fully exploit the information contained in the other modalities. In this paper, we present a modal-aware operation as a generic building block to capture the non-linear dependences among the heterogeneous intermediate features that can learn the underlying correlation structures in other multimodal data as soon as possible. The modal-aware operation consists of a kernel network and an attention network. The kernel network is utilized to learn the non-linear relationships with other modalities. Then, to learn better representations for binary hash codes, we present an attention network that finds the informative regions of these modal-aware features that are favorable for retrieval. Experiments conducted on three public benchmark datasets demonstrate significant improvements in the performance of our method relative to state-of-the-art methods.