Reviewerly/exHarmony huggingface dataset:
Penyajian Informasi Sarana dan Prasarana Berbasis Sistem Informasi Geografis di Kecamatan Tanete Raittang Kabupaten Bone

The aim of research to determine: 1) methods of presenting information based GIS infrastructure, 2) distribution facilities and infrastructure, and 3) The condition of facilities and infrastructure. This research was conducted by survey method. The study population includes building government infrastructure, economy, education, and worship kesehatanm with purposive sampling technique. Qualitative descriptive analysis based geographic information system. The results showed: 1) Presentation of information facilities and infrastructures based GIS is done by describing the results of the survey in the field with the attribute data (tables of research) and spatial data in the form of a map that details of each infrastructure that includes government, the economy, education, health, and worship that is able to answer all of the existing problems. 2) Distribution of facilities and infrastructure tend to converge on the village as well as for economic infrastructure centered in the Village Watampone, facilities and infrastructure pendidikakan centered in the Village Blue. 3) The condition of facilities and infrastructure are categorized in very good condition with aspects of SSR assessment in the form of the building functioned as the function of the establishment, fitness for use, facilities support adequate and good maintenance .
Domain Adaptation with Nonparametric Projections

Domain adaptation algorithms focus on a setting where the training and test data are sampled from related but different distributions. Various domain adaptation methods aim to align the source and target domains in a new common domain by learning a transformation or projection. In this work, we learn a nonlinear and nonparametric projection of the source and target domains into a common domain along with a linear classifier in the new domain. Experiments on image data sets show that the proposed nonlinear approach outperforms baseline domain adaptation methods based on linear transformations
Intermediate-Advanced Level

The chapter provides several exercises that aim to refine left-hand technique in the intermediate-advanced levels of string playing. These techniques include building better pitch accuracy, tuning double stops, executing trills, producing both natural and false harmonics, shifting, perfecting vibrato, and performing glissando. Right-hand bowing techniques that develop phrasing as well as various sound colors and advanced bowing styles are discussed. The author explains how incorporating western music history and theory concepts in rehearsals help students gain a deeper understanding about a piece’s purpose, musical form, harmonic structure, and rhythmic principles so that students can convey a powerful and emotional performance.
LibGuides: Media Services and Resources: Services

The Library provides access to audiovisual equipment and services to support the academic programs of the University of Lethbridge. The Library provides access to audiovisual equipment and services to support the academic programs of the University of Lethbridge
Sport News Classification with Convolutional Neural Network and Long-Short Term Memory

In this work, a system has been designed and implemented to classify the sports types found in sports news videos with Long-Short Term Memory Network (LSTM) method and to automatically segment the sport news program. Sports news we encounter in daily life contains anchor part who present news. There is no need to classify these parts. Thus, anchor faces was detected with using Local Binary Pattern Histogram method and removed from sport news in preprocessing step. In order to increase the processing speed instead of performing face recognition to the entire video, scene transitions were determined by using 64-bin histogram method and k-means algorithm and face recognition was performed only at this scene transitions. After the anchors are removed from videos, CNNs were used for feature extraction and LSTM was used for classification of videos by sport. In order to train and test the system, UCF-101 sport dataset, Unsegmented Sport News data set and YouTube sport videos dataset which is created from sport videos from Youtube by us were used. Classification was performed for 9 sport types including swimming, American football, football, tennis, basketball, wrestling, baseball, volleyball, and golf.
Germany, Shame on You and Your anti-BDS Resolution

By Gideon Levy. Published on May 19, 2019 on Haaretz website. Germany has just criminalized justice. A blend of warranted guilt feelings, orchestrated and taken to sickening extremes by cynical and manipulative Israeli extortion, caused the federal parliament on Friday to pass one of the most outrageous and bizarre resolutions since the end of World War II. The Bundestag has defined the boycott, divestment and sanctions movement against Israel as anti-Semitic. Benjamin Netanyahu and Gilad (...)
Practical Scheme for Secure Outsourcing of Coppersmith’s Algorithm

Coppersmith’s Algorithm was proposed by Coppersmith to find all small roots of a univariate polynomial congruence in polynomial time. In practical applications, we are facing a bottleneck of computation with high-dimensional matrix and extra large coefficients. In this case, cloud computing can provide the capability to utilize almost unlimited computational power and storage on cloud servers. In this paper, we investigate secure outsourcing for Coppersmith’s Algorithm for the first time. We design a outsource-secure scheme for Coppersmith’s Algorithm with extremely high speedup on the client side. The most time-consuming part of algorithm, which is the lattice reduction process, can be outsourced to a malicious cloud. We show that our scheme are correct, secure and have high-efficiency as well as immediate practicability.
Side Channel Analysis of Raspberry Pi with AES Algorithm and Measurement Improvement

In this paper, DEMA (Differential Electromagnetic Analysis) attack, which is one of the differential side channel analysis methods, is applied to the AES algorithm running on the Raspberry Pi. Raspberry Pi's operating system is not a simple operating system. Due to the fact that it is a mini computer, while Raspberry Pi is doing an operation, operating system are being performed simultaneously. The noise of the routine system of the operating system was observed, and the variance of the process time was observed when encryption or decryption was performed with AES. The encryption time is unpredictable and the routine operating system process has made it difficult to analyze measurements. In this study, it was investigated whether using Raspberry Pi platform is a measure against direct side channel analysis. At the end of the analysis, the algorithm is seen no to withstand the side channel attack because of secret key obtained. It is proposed to implement a software-based measure in the AES algorithm or a software / hardware measure to be added to Raspberry Pi.
COMPARING THREE INPUT DEVICES FOR SKETCHING ASSIGNMENTS IN E-EXAMS IN COMPUTER SCIENCE

E-exams used in higher education can accommodate a range of assignment types that have traditionally been conductedwith pen-and-paper. However, one issue that remains a challenge is proper support of sketching in larger, generic e-examssystems.
Improved biometric identification system using a new scheme of 3D local binary pattern

In any computer vision application, integration of relevant feature extraction module is vital to help in making accurate decision of the classification. In the literature, several methods that have achieved promising results and high accuracies are based on texture analysis. Thus, there exist various feature extraction techniques to describe the texture information, among them; the local binary pattern (LBP) is widely used to characterise the image sufficiently. Generally, LBP descriptor and their variants are applied on greyscale images. Thus, in this paper, we propose a new method that can be applied to any type of image either in greyscale, colour, multispectral or hyperspectral. It is a new scheme of 3D local binary pattern. We have developed biometric system for person identification and an edge detection technique to evaluate it. The obtained results have showed that it has higher performances compared to other methods developed in the literature in terms of identification rates.
The role of CRM and e – CRM in the Hospitality and Tourism Industry and the reasons why they fail

&lt;p&gt;&lt;b&gt;Purpose: &lt;/b&gt;This article is an overview of the existing literature review in the aspect of CRM and e – CRM concluding opinions and theories of academic writers. The purpose of this article is to review the existing literature of CRM, the connection of e-CRM in the technological advantage and investigate more and in depth all the connection between CRM and e – CRM with customer retention and customer satisfaction with a focus in the rate of failure and the reason why CRM project fail and investigate research gaps. &lt;/p&gt;&lt;p&gt;&lt;b&gt;Methodology: &lt;/b&gt;Secondary research has been conducted by using Oxford Brookes library databases such as business source complete, Emerald and hospitality and tourism complete, EBSCO host, Elsevier, on – line books, Journal of travel research and numerous academic journal articles.&lt;/p&gt;&lt;p&gt;&lt;b&gt; &lt;/b&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;Findings: &lt;/b&gt;There are findings which explain some of the reasons why CRM has a 55% to 77% failure rate and e – CRM a 65% of failure. This is due to insufficient training from employers or even motivation from employees in order to learn the CRM systems. Moreover, it was found that sometimes, e -CRM programs due to the high cost of programs are not preferred by SME companies and they prefer to keep the traditional marketing approaches which can lead to low customer retention. &lt;/p&gt;&lt;p&gt;&lt;b&gt; &lt;/b&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;Research limitations: &lt;/b&gt;All findings are based in secondary research in English articles without conducting a primary research. Approximately, in all academic journal articles, books and on line resources it was mentioned that there is a limitation in the literature review of e – CRM in the hospitality industry due to the lack of journal article resources and the small sample size researches &lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;b&gt;Practical implications: &lt;/b&gt;Due to the fact that antagonism between hospitality industries grows, top managers should train fully the employees of lower hierarchical levels as it has a further influence in customers’ satisfaction and customers retention and SME’s have start and adopt CRM strategies according to their financial data. &lt;/p&gt;&lt;p&gt;&lt;b&gt; &lt;/b&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;Originality/value: &lt;/b&gt;This article helps a lot of people on how e – CRM was born and what are the main principles of the CRM before the emerge of WEB 2.0 era as there is a little difference between them. Moreover there is gap in the literature regarding hospitality industry as the articles do not offer an expanded knowledge due to small size samples and also due the fact that there are no articles that describe the steps that managers and companies have to do in order to overcome the lack of CRM in almost all SMEs. &lt;/p&gt;
Graph Structured Prediction Energy Networks

For joint inference over multiple variables, a variety of structured prediction techniques have been developed to model correlations among variables and thereby improve predictions. However, many classical approaches suffer from one of two primary drawbacks: they either lack the ability to model high-order correlations among variables while maintaining computationally tractable inference, or they do not allow to explicitly model known correlations. To address this shortcoming, we introduce ‘Graph Structured Prediction Energy Networks,’ for which we develop inference techniques that allow to both model explicit local and implicit higher-order correlations while maintaining tractability of inference. We apply the proposed method to tasks from the natural language processing and computer vision domain and demonstrate its general utility.
Sobolev Independence Criterion

We propose the Sobolev Independence Criterion (SIC), an interpretable dependency measure between a high dimensional random variable X and a response variable Y. SIC decomposes to the sum of feature importance scores and hence can be used for nonlinear feature selection. SIC can be seen as a gradient regularized Integral Probability Metric (IPM) between the joint distribution of the two random variables and the product of their marginals. We use sparsity inducing gradient penalties to promote input sparsity of the critic of the IPM. In the kernel version we show that SIC can be cast as a convex optimization problem by introducing auxiliary variables that play an important role in feature selection as they are normalized feature importance scores. We then present a neural version of SIC where the critic is parameterized as a homogeneous neural network, improving its representation power as well as its interpretability. We conduct experiments validating SIC for feature selection in synthetic and real-world experiments. We show that SIC enables reliable and interpretable discoveries, when used in conjunction with the holdout randomization test and knockoffs to control the False Discovery Rate. Code is available at http://github.com/ibm/sic.
The Relationship between Proactive Personality and Creativity: The Moderating Role of Task Autonomy and Task Feedback

창의성은 변화가 빠르게 진행되는 오늘날의 경영 환경에서 기업들에게 지속적인 성장과 경쟁우위 달성을 가능하게 하는 중요한 요소로 여겨지고 있다. 본 연구는 창의성에 영향을 미치는 개인의 능동적인 특성에 집중하였다. 즉, 변화 주도 성향과 자기 향상 동기를 기반으로 개인의 주도적 성격이 창의성에 미치는 영향을 검토하였다. 또한 개인의 성격 특질 변수를 활성화 시켜주는 상황 요인으로 직무 특성을 고려하였다. 구체적으로, 특성 활성화 이론을 적용하여 본 논문에서는 자율성과 피드백이 주도적 성격이 창의성에 미치는 정(+)의 효과를 강화 할 것이라고 예측하였다. 더 나아가 주도적 성격과 자율성, 피드백의 삼원 상호작용 효과를 살펴보았다. 이러한 가설들을 검증하기 위해서 국내기업들을 대상으로 상사-부하 설문을 실시하여 총 158쌍의 응답을 실증 분석하였다. 동일 방법 편의를 제거하기 위해 조직 구성원들에게 주도적 성격, 자율성, 피드백을 측정하였고, 조직 구성원들의 창의성은 그들의 직속상사에 의해 측정하였다. 위계적 회귀 분석 결과 주도적 성격을 가진 구성원일수록 창의적인 행동을 많이 보이는 것으로 나타났다. 조절효과 중 자율성은 주도적 성격과 창의성의 관계를 정(+)적으로 조절하였다. 반면, 피드백은 가설에서 예측 했던 것과는 달리 주도적 성격과 창의성의 관계를 부(-)적으로 조절하였다. 보다 자세히 세 변수들의 삼원 상호작용 효과를 살펴본 결과, 자율성이 높고 피드백이 낮을 때 주도적 성격과 창의성의 정(+)적 관계가 가장 강화되었다. 본 연구는 창의성 창출을 위한 능동적인 개인의 특성이 무엇이며, 이를 활성화시키는 경계 조건이 무엇인지를 밝힘으로써 창의성과 관련된 분야에 이론적·실무적 함의를 제공한다고 할 수 있다.Creativity is critical for organizational survival and growth in the contemporary business environment, in which organizations must adapt to fast-changing markets. This study focused on the importance of proactive individual dispositions. Particularly drawing on personal initiative tendency and self-enhancement motive, this study investigated the relationship between proactive personality and individual creativity. This study also considered job characteristics as trait-relevant factors to activate personality expression. Specifically, based on trait-activation theory, the study predicts that autonomy and feedback strengthen the positive effects of proactive personality and creativity, also examining the three-way interaction between proactive personality, autonomy, and feedback on creativity. To prove these hypotheses, empirical analyses were conducted on 158 employee-supervisor dyad samples collected from Korean companies. To avoid common method bias, employees were asked to rate their proactive personality, autonomy, and feedback, whereas their immediate supervisors were asked to rate the employees’ creativity. As predicted, individuals with high proactive personality were more likely to be involved in creative behaviors. In the opposite direction from what was expected, autonomy positively moderated the relationship between proactive personality and creativity, while feedback negatively moderated the relationship between proactive personality and creativity. The results of specific three-way interaction effects show that the positive effects between proactive personality and creativity are strongest when autonomy is high and feedback is low. These theoretical backgrounds and results reveal proactive individual traits in promoting creativity and the boundary condition necessary to increase such behaviors. The study’s findings have important theoretical and practical implications in creativity literature.
Domain Intersection and Domain Difference

We present a method for recovering the shared content between two visual domains as well as the content that is unique to each domain. This allows us to map from one domain to the other, in a way in which the content that is specific for the first domain is removed and the content that is specific for the second is imported from any image in the second domain. In addition, our method enables generation of images from the intersection of the two domains as well as their union, despite having no such samples during training. The method is shown analytically to contain all the sufficient and necessary constraints. It also outperforms the literature methods in an extensive set of experiments. Our code is available at this https URL.
PIE - Proving, Interpolating and Eliminating on the Basis of First-Order Logic.

PIE is a Prolog-embedded environment for automated reasoning on the basis of first-order logic. It includes a versatile formula macro system and supports the creation of documents that intersperse macro definitions, reasoner invocations and LaTeX-formatted natural language text. Invocation of various reasoners is supported: External provers as well as sub-systems of PIE, which include preprocessors, a Prolog-based first-order prover, methods for Craig interpolation and methods for second-order quantifier elimination.
Multiple Task-driven Face Detection Based on Super-resolution Pyramid Network

Although research in face detection and recognition has achieved tremendous progress through the various frameworks that are being put forward every year, face detection under complex circumstances is still a challenging issue. Multiple task-driven face detection has wide applications, such as crowd number estimation, face recognition attendance and so on. In this paper, we propose a multiple task-driven cascade detection networks based on super-resolution Pyramid, to effectively tackle the following challenges in face detection: low-resolution faces under the lens; faces from blur, illumination, scale, pose, expression and occlusion. Our method integrates the advantages of the super-resolution technology and an efficient image pyramid structure. The design of this structure not only recover high frequency information lost in the sampling process, but also can handle multi-scale invariants. Also, facial landmarks play non-negligible roles during detection. Our method achieves state-of-the-art results over prior arts on both the WIDER FACE dataset and the Face Detection Dataset and Benchmark (FDDB), and our results show a higher average detection precision of 90%. Notably, we demonstrate superior performance and robustness in a challenging environment.
Aprendizaje orientado a Proyectos en Arte y Trabajo

The purpose of this essay is to reflect on the value of learning in a context of uncertainty such as the university classroom, where students are presented with a real approach to the subject and others without sufficient motivation to take a subject, linked to the art and creative work. More than making a detailed approach to the situation, we are interested in an existential proposal, based on active methodologies and the stages of reality through the crossing of three styles of knowledge (critical, creative, meta-cognitive) deep learning through short artistic projects. And so, transform the teaching-learning process by leaving the teacher to have the leading role and the students assume the leadership of the process, to have a holistic and comprehensive learning result with meaning from the results achieved, which covered the expectations raised, even so they will analyze the situations and implications to encourage other experiences.
Do We Preach What We Practice? Investigating the Practical Relevance of Requirements Engineering Syllabi - The IREB Case.

Nowadays, there exist a plethora of different educational syllabi for Requirements Engineering (RE), all aiming at incorporating practically relevant educational units (EUs). Many of these syllabi are based, in one way or the other, on the syllabi provided by the International Requirements Engineering Board (IREB), a non-profit organisation devoted to standardised certification programs for RE. IREB syllabi are developed by RE experts and are, thus, based on the assumption that they address topics of practical relevance. However, little is known about to what extent practitioners actually perceive those contents as useful. We have started a study to investigate the relevance of the EUs included in the IREB Foundation Level certification programme. In the first phase reported in this paper, we have surveyed practitioners mainly from DACH countries (Germany, Austria and Switzerland) who participated in the IREB certification. Later phases will widen the scope both by including other countries and by not requiring IREB-certified participants. The results shall foster a critical reflection on the practical relevance of EUs built upon the de-facto standard syllabus of IREB.
Cultural Scaffolding and Technological Change: A Preliminary Framework

Technology helps us to do new things, or to do old things in new ways. This, at least, is our common understanding and continual hope. Technologies, however, only become useful when guided by human means to human ends and they therefore do not add to our arsenal of abilities in an unproblematic, straightforward manner. Rather they must confront a complex and preexisting set of biological traits and cultural practices before their potentialities and consequences are clear. My goal here is to sketch an account of how technologies interact with the innate and socially supported human capacities to learn and develop, using cultural scaffolding as an interpretive tool.
An Empirical Study into the Success of Listed Smart Contracts in Ethereum

Since it takes time and effort to put a new product or service on the market, one would like to predict whether it will be a success. In general this is not possible, but it is possible to follow best practices in order to maximise the chance of success. A smart contract is intended to encode business logic and is therefore at the heart of every new business on the Ethereum blockchain. We have investigated how to measure the success of smart contracts, and whether successful smart contracts have characteristics that less successful smart contracts lack. The appearance of a smart contract on a listing website such as Etherscan or StateoftheDapps is such a characteristic. In this paper, we present a three-pronged analysis of the relative success of listed smart contracts. First, we have used statistical analysis on the publicly visible transaction history of the Ethereum blockchain to determine that listed contracts are significantly more successful than their unlisted counterparts. Next, we have conducted a survey among more than 200 developers via an anonymous online survey about their experience with the listing process. A significant majority of respondents do not believe that listing a contract itself contributes to its success, but they believe that the extra attention that is typically paid in tandem with the listing process does contribute. Finally, based on the respondents' answers, we have drafted 10 recommendations for developers and validated them by submitting them to an international panel of experts.