Reviewerly/exHarmony huggingface dataset:
Knowledge and competence for a networked world

KEYNOTE SPEECH.&#x0D; The world of today may be viewed as networked, both socially and technologically, with characteristics such as globalization, mobility of people across contexts, bottom-up user involvement, interweaving of physical and virtual contexts, and general pervasiveness of ICT. &#x0D; In her talk, Nina analyzes the competence demands which are posed on citizens in a networked world. She argues for a view of knowledge as a unity of experiential, practical, and propositional aspects, realized concretely in relation to the demands of the situation, yet points out that in a networked world, people are continuously required to use knowledge, learned in one setting, in new contexts. This raises the question of how people transform and resituate knowledge across contexts.&#x0D; Finally, Nina discusses implications of her talk for design for learning the knowledge and competence required. Throughout the talk, she will engage in discussion with participants about the way her heoretical points plays out in library practice and which roles libraries and librarians can have as facilitators of others’ development of knowledge and competence for a networked world.
Excitation-by-SampleRNN Model for Text-to-Speech

In this paper, we propose a neural vocoder-based text-to-speech (TTS) system that effectively utilizes a source-filter modeling framework. Although neural vocoder algorithms such as SampleRNN and WaveNet are well-known to generate high-quality speech, its generation speed is too slow to be used for real-world applications. By decomposing a speech signal into spectral and excitation components based on a source-filter framework, we train those two components separately, i.e. training the spectrum or acoustic parameters with a long short-term memory model and the excitation component with a SampleRNN-based generative model. Unlike the conventional generative model that needs to represent the complicated probabilistic distribution of speech waveform, the proposed approach needs to generate only the glottal movement of human production mechanism. Therefore, it is possible to obtain high-quality speech signals using a small-size of the pitch interval-oriented SampleRNN network. The objective and subjective test results confirm the superiority of the proposed system over a glottal modeling-based parametric and original SampleRNN-based speech synthesis systems.
The Satisfaction Degree of Occupational Tasks among the Faculty Members in the Hashemite University

This study aimed at identifying the satisfaction degree of the faculty members on their occupational tasks in the Hashemite University, and its relationship with their gender, academic rank and college variables. The study sample consisted of (185) faculty members, forming (32%) of the total study population. The researchers constructed a 31-item questionnaire distributed over three dimensions: teaching, scientific research, and community service. The study results showed that the satisfaction degree of the faculty members on their occupational tasks in the Hashemite University was high. The order of the dimensions was: teaching, scientific research and community service, respectively. The results further showed an apparent statistically significant difference in the satisfaction degree of the faculty members on their occupational tasks, attributed to their gender in all the dimensions in favor of the females. However, it was in favor of the professor rank according to the academic rank variable, and in favor of the scientific colleges faculty members according to the college variable. In the light of the study results, the researchers recommend enhancing the functionality of the faculty members, and maintaining the high level the faculty members achieved through the results of this study.
『蜻蛉日記』下巻の『霜枯れの』歌の成立事情

In this article, we pay a special attention to the documents relating to Hujiwarano Kanemichi and Hujiwarano Tōnori, who are the brothers of...
A study of smart Healthcare service Model based on Cloud Platform: Focus on small and Medium sized Hospitals

The objective is to propose a cloud hospital information system (cHIS) to allow small and medium sized hospitals to provide smart healthcare services and gain improved competitiveness. The research was conducted on cloud platform-based HIS service, mobile electronic medical record (EMR) service, personal biological record (PBR) service and healthcare big data service. Cloud computing technology was used for the HIS service to minimize the operating cost, IoT was applied to the mobile EMR and PBR services, and big data technology was used for the healthcare big data service to raise the efficiency in the clinical setting. This study examined the measures for promoting the use of cloud computing technology in the healthcare sector. If service providers can provide affordable, high-quality cloud healthcare services, such services will become high in demand despite hindrances. Thus, the architecture and service model of the cHIS were designed to minimize the operating costs through resource pooling achieved by virtualizing the hardware and application programs to promote affordability. Also, CloudSim was used to assess the stability and efficiency in relation to the data access time, service processing time and service wait time. First, the results of the experiment showed that an increase in the cloud storage disk and network bandwidths allows more users to be serviced. Second, it was found that the packet size had little to no impact on the system performance. Third, it was found that cloud-based distributed storage and processing was more efficient than using a web-based database in case of processing large amounts of data. The system presents economic advantages including maximized sharing of resources and minimized costs, enables real-time exchange of healthcare data, and promotes the use of collective intelligence for better healthcare services.
Synthesis Score Level Fusion Based Multifarious Classifier for Multi-Biometrics Applications

In this paper, we are presenting a face and signature recognition method from a large dataset with the different pose and multiple features. Initially, Face and corresponding signature are detected from devices for further pre-processing. Face recognition is the first stage of a system then the signature verification will be done. The proposed Legion feature based verification method will be developed using four important steps like, (i) feature extraction from face and data glove signals using feature Extraction. The various Features like Local binary pattern, shape and geometrical features of face, then the global and local features of the signatures were extracted. (ii) Score match normalization is used to enhance the recognition accuracy using min–max and median estimations. (iii) Then the match scores are evaluated using synthesis score level fusion based feature matching through Euclidean distance, (iv) Recognition based on the final score. Finally based on the feature library the face image and signature can be recognized. The similarity measurement is done by using Synthesis score level fusion (SSF) based multifarious Neural network (MNN) Classifier with weighted summation formulae where two weights will be optimally found out using Adapted motion search optimization algorithm. Finally SSF-MNN based matching score fusion based decision classifier to determine recognized and non-recognized biometrics. Moreover, in comparative analysis, a proposed technique is compared with the existing method by several performance metrics and the proposed SSF-MNN technique efficiently recognize the face images and corresponding signature from the input databases than the existing technique.
Cognitive workload management on globally interoperable network of clouds

A new computing paradigm using Distributed Intelligent Managed Elements (DIME) and DIME Network Architecture (DNA) is used to demonstrate globally interoperable public and private cloud network deploying cloud agnostic workloads. The workloads are cognitive and able to adjust autonomously their structure and maintain desired quality-of-service (QoS). DNA is designed to provide a control architecture for workload self-management of non-functional requirements to address rapid fluctuations either in workload demand or fluctuations in available resources. Using DNA, a transaction intensive three-tier workload is migrated from a physical server to a virtual machine hosted in a public cloud without interrupting the service transactions. After migration, cloud agnostic inter-cloud and intra-cloud auto-scaling, auto- failover and live migration are demonstrated again, without disrupting the user experience or losing transactions.
The Effect Of Students Motivation Toward Students Achievement Grade V At Elementary School Kecamatan Rambah Hilir Kabupaten Rokan Hulu Riau

ABSTRACT &#x0D; This study aims to reveal the effect of learning motivation on learning outcomes in grade V elementary school District of Rambah Hilir District, Rokan Hulu Riau Regency. The hypothesis in this study, learning motivation has an effect on learning outcomes. This type of research is correlation and regression. The research method used is correlational quantitative methods. The study population was all fifth grade students of State Elementary Schools in Cluster IV in Rambah Hilir Subdistrict, Rokan Hulu Regency, totaling 207 people. 67 results were determined using thetechnique Stratified Proportional Random Sampling. The data was collected with a Likert scale model questionnaire that had been tested for validity and reliability. The results of the questionnaire trial obtained by the variable X 0.859&gt; 0.396 by comparing r count greater than r table, the variable is said to be reliable / valid. Data were analyzed by correlation and regression techniques. The results of the analysis showed that the magnitude of the influence of motivation on learning outcomes was 11.7%.
Smart Contracts: Reducing Risks in Economic Exchange with No-Party Trust?

Our study on smart contracts, self-executing agreements based on blockchain technology, can be placed in the field of inquiry within law and economics of contracts which explores new modes of contract enforcement as sources of market creation. We lay the foundations by characterising contract enforcement and trust mechanisms underlying contracts. Considering that trust reduces risks in economic exchange, we explain how the particular trust mechanism underlying smart contracts’ enforcement (no-party trust) provides opportunities for creating new markets and changing existing ones. We explore, among other things, whether using smart contracts could be a path to increasing the autonomy of consumers and offering a solution for democratising trade.
Collaborative Citation Management

When it comes to citation management, identifying the right tool for the job has become an everevolving task.As an instruction librarian in the sciences, I have spent many a futile lesson teaching how to use a citation management tool only to find that the students quickly abandoned it if it did not readily address their specific needs.My institution is a mid-sized PhD granting university where research regularly occurs, but the primary focus is on undergraduate student education.Our students and researchers have expressed their desire for citation management software that is free, intuitive, and has their preferred citation styles.They also desire a tool that can go beyond formatting a bibliography to format citations directly from their word processorsthis function often serves as the deciding factor among potential managers.Though many citation managers allow users to cite sources while writing their papers, not all managers work with all word processors.With the growing popularity of Google Docs as a collaborative tool among college students, the ability of a citation manager to integrate specifically with Docs has become a desired and necessary function.However, only a few tools are actually equipped for the job.Among them, Paperpile rises to the top with Zotero following closely behind.
Places for News: A Situated Study of Context in News Consumption

This paper presents a qualitative study of contextual factors that affect news consumption on mobile devices. Participants reported their daily news consumption activities over a period of two weeks through a snippet-based diary and experience sampling study, followed by semi-structured exit interviews. Wunderlist, a commercially available task management application and note-taking software, was appropriated for data collection. Findings highlighted a range of contextual factors that are not accounted for in current ‘contextually-aware’ news delivery technologies, and could be developed to better adapt such technologies in the future. These contextual factors were segmented to four areas: triggers, positive/conducive factors, negative/distracting factors and barriers to use.
Enhancing Blood Cell Images using Denoising Filters for the Detection of Hematological Disorders

Hematological disorders refer to the diseases caused with the changes in blood cells or blood system such as Leukemia, Anemia, Malaria and Azotemia. Preprocessing of blood cell images is very important step in the detection of these disorders. Hence after image acquis ion from hematologists and oncologists denoising and edge detection are to be done to enhance the image for segmentation of blood cell images and leukocytes, erythrocytes and thrombocytes. Because leukemia can be detected from leukocytes and malarial parasites can be detected from erythrocytes. In this paper we have applied few techniques such as Gabor filter, Gaussian filter, Prewitt filter, Sobel and Canny edge operators for the preprocessing purpose. We have compared the performance of these techniques based on their accuracy and resolution
Human and Object Detection and Interaction Analysis in Video ImageProcessing

Interaction analysis between human and objects are a part of video image processing. Human and object interactions contain an important data that can be extracted and analyzed. In order to understand the motive and purpose of object motion and the reason they occur, interaction analysis between human and objects should be carried out. This will give us an understanding of human behavior. From a video sequence, the human and objects and their motions are detected through an algorithm process. These motions are then analyzed as interactions when the human and objects overlaps each other. From this research, the interactions of the human and objects and its surrounding will result in having either interaction or no interaction at all. Accuracy of the human and object detection is critical to this analysis. It may be used in various scenes especially surveillance camera system, for eliminating threatening conditions such as robbery or theft in a shop
AN IMPACT ASSESSMENT OF HIGHER CAPITAL ADEQUACY REQUIREMENTS: EVIDENCE FROM INDIA

Regulatory norms aim to ensure stability and resilience in the banking sector as episodes of crises may have a spill-over effect in the real economy.Literature based on studies of developed economies, suggests that higher capital norms improve the resilience of the banking sector, which in turn, reduces the probability of a financial crisis.An important benefit of which is on the size of the economic loss if the crisis does occur.On the other hand, higher capital requirements pose significant costs to banks, which are, in turn, passed on to the rest of society through reductions in lending volumes, credit rationing and increase in prices of credit that culminates into decreasing the output of the economy.This study aims to find the net impact of implementing Basel norms in a fast-growing economy, (yet under-researched) of Asia, i.e, India.The results prove that the implementation of Basel norms has significant benefits (using a step wise approach, multivariate logistic regression), along with costs (using vector auto regression).In sum, there are positive net benefits in terms of output saved.
Density Matrices for Derivational Ambiguity.

Recent work on vector-based compositional natural language semantics has proposed the use of density matrices to model lexical ambiguity and (graded) entailment (e.g. Piedeleu et al 2015, Bankova et al 2019, Sadrzadeh et al 2018). Ambiguous word meanings, in this work, are represented as mixed states, and the compositional interpretation of phrases out of their constituent parts takes the form of a strongly monoidal functor sending the derivational morphisms of a pregroup syntax to linear maps in FdHilb. Our aims in this paper are threefold. Firstly, we replace the pregroup front end by a Lambek categorial grammar with directional implications expressing a word's selectional requirements. By the Curry-Howard correspondence, the derivations of the grammar's type logic are associated with terms of the (ordered) linear lambda calculus; these terms can be read as programs for compositional meaning assembly with density matrices as the target semantic spaces. Secondly, we extend on the existing literature and introduce a symmetric, nondegenerate bilinear form called a that defines a canonical isomorphism between a vector space and its dual, allowing us to keep a distinction between left and right implication. Thirdly, we use this metric to define density matrix spaces in a directional form, modeling the ubiquitous derivational ambiguity of natural language syntax, and show how this alows an integrated treatment of lexical and derivational forms of ambiguity controlled at the level of the interpretation.
Factors Affecting Soldiers’ Perception of Sexual Harassment Criminal Psychology

군대는 위계질서가 강하고 폐쇄적인 특성으로 인해 성희롱이 빈번하게 발생하지만, 문제제기가 가장 어려운 집단이라고 할 수 있다. 이에 국방부는 다각도의 대응방안을 제시하지만 대부분이 성폭력에 중점을 두고 있으며, 국방부 차원에서의 실태조사는 이루어지지 않았다. 본 연구는 군 장병의 성희롱에 대한 인식에 영향을 주는 영향요인을 분석하여 군 장병의 성희롱 인식을 개선할 방안을 모색코자 하였다. 499명의 군장병이 참여한 설문조사 결과, 일상적 긴장이 높을수록, 음주/회식이 잦을수록 성희롱에 대한 인식은 낮았으며, 성평등 의식이 높을수록, 공감능력이 높을수록 성희롱에 대한 인식은 강한 것으로 분석되었다. 연구 결과를 토대로 군장병의 일상적 긴장을 낮추기 위한 건전한 여가활동 시행, 성평등 의식을 강화할 교육 프로그램 개발, 공감능력을 높이기 위한 음악/미술/스포츠를 활용한 프로그램의 도입과 시행, 군 장병들의 의견을 고려한 건전한 음주/회식문화 활성화 방안 수립 등이 제안되었다.The purpose of current study is to investigate soldiers’ perception of sexual harassment and factors affecting their perceptions. It has been considered that sexual harassment in the miliary is prevalent, while it is the most difficult place to report the incident. Based on previous research review, demographic factors (including age, gender, position, service period, marital status, having children, having daughter, having sisters, religion, religious faith, and economic status), military life satisfaction, drinking/congregate dining, empathy, self esteem, general strain, self control and gender equality were constructed as independent variables. Using self-administered survey method, 499 soldiers in the military were participated in survey. Research results indicated that average of respondents’ perceptions of sexual harassment 4.39 was higher than median value(3). Results of multiple regression revealed that a respondent with a higher empathy level and gender equality level is more likely to demonstrate higher perception of sexual harassment, while a respondent with higher level of general strain and frequent drinking/congregate dining is more likely to demonstrate lower level of perception of sexual harassment. Based on research results, implementing various leisure activities aiming at alleviating soldiers’ general strain, developing educational programs for enhancing gender equality level, introducing music, art and sports programs aimed at strengthening empathy level and developing strategic plans for establishing wholesome drinking/congregate dining cultures in the military were provided as policy implications.
ORGANISATION OF KNOWLEDGE FROM TRACES OF HUMAN LEARNING

Faced with the diversity and the large number of learning resources available on e-learning platforms, learners often face problems of inadequacy between the training path to choose and the skills sought.Indeed, many learning platforms with recommendation exist, but these do not often include information and different characteristics of learners.This problem can be mitigated by the semantisation of the content and the organization of the knowledge of the different actors involved on the learning platform.In this paper, we make a modeling of the knowledge representation (thesauri and concept maps) of learning resources, based on information from learner's written records on a learning platform and knowledge modeling from expert interactions on resource and learner assessments.These models make it possible to represent knowledge from written tracesthese written traces are metadata resulting from the interactions made on a learning platform by the learners and the experts (for example the expert in charge of the content of the trainings, the expert in charge of the evaluation of the trainings carried out).
NTNU Academic Writing - developed with UX

In spring 2017, the University Library of the Norwegian University of Science and Technology (NTNU) launched VIKO, the redesigned tool for fostering information literacy and academic writing skills.&#x0D; The digital and technological development as well as new requirements for information literacy and academic writing skills have made it necessary to revise this tool.&#x0D; A working group at NTNU University Library developed and carried out an electronic survey to map specific needs of students, teachers, and researchers. We involved our users in developing our information literacy tool in order to give them a more useful user experience. We asked the following questions: Is information about academic writing something you need? Where do you go to find information about this? What kind of content do you desire? The answers suggested that “Yes!” this was something both students and teachers wanted. They were eager to get all the information they needed in their studies in one place.&#x0D; Results of this survey and additional depth interviews with students and staff have been the starting point for both the updated content and the new graphical design of VIKO. To accommodate the wish of having all information in one place, all content is now placed on the University Intranet together with all other information relevant for the students. A page listing relevant topics helps students navigate in the content relating to academic writing.&#x0D; The content of the redesigned tool is structured into four topics: defining a research topic, finding sources, structuring your text, and using and citing sources. We know that people have different ways of learning, so offering content for different learning styles like visual learning, auditory learning, and read/write learning will contribute to improving the learning outcomes.
The Feasibility of Creating a Universal Digital Forensics Framework

The aim of this paper was to identify quality evidence that supports the feasibility that a standardized digital forensic methodology for all investigations of all digital artifacts in the global environment can be generated.