Reviewerly/exHarmony huggingface dataset:
Predictive approaches to cloud computing costs reduction

Cloud Computing has become more and more affordable, it has seen an important growth in terms of adoption among all the IT companies in the last few years, overtaking the previously used on-premise solutions. Indeed, Cloud Computing is generally cheaper and easier to set-up with respect to on-premise solutions, requiring no maintenance and coming with more service stability, generally higher up-time and dedicated support from experienced companies like Google or Amazon in case of problems. The easiness of Cloud Computing, however, may lead developers to misuse computational resources mainly because it is very easy to add more memory or more processing units to any application. Moreover, developers never know the precise amount of resources their applications will need, thus exceeding with resources allocation just to be ready to handle all possible worst cases. In this work we will address the misuse of cluster resources from two perspectives, focusing our attention on batch jobs. Firstly, we will address the problem of scheduling several jobs into the same clusters, thus implementing resources sharing among jobs. Then, we will focus on automatically resizing cluster's resources (expressed in terms of computational machines) in order to always provide the best fit between cluster's resources and user's jobs. Moreover, we will prove that better scheduling decisions can be taken by exploiting the prior knowledge we have on our jobs in order to build Machine Learning models. In conclusion, we will show how we managed to obtain a 65% saving in costs of cloud computing in our team by adopting our system as an intermediate layer between the developers and the Cloud Computing platform.
Inference for continuous-time long memory randomly sampled processes

From a continuous-time long memory stochastic process, a discrete-time randomly sampled one is drawn using a renewal sampling process. We establish the existence of the spectral density of the sampled process, and we give its expression in terms of that of the initial process. We also investigate different aspects of the statistical inference on the sampled process. In particular, we obtain asymptotic results for the periodogram, the local Whittle estimator of the memory parameter and the long run variance of partial sums. We mainly focus on Gaussian continuous-time process. The challenge being that the randomly sampled process will no longer be jointly Gaussian.
Knowledge Management Process as a Predictor on Organizational Performance in Dubai Government Departments

In recent years, the concept of Knowledge Management has expanded widely in government and private sectors. The last five years have witnessed intensive discussions on Knowledge Management and its importance. The aim of this study is to examine the relationship between Knowledge Management and its aspects and its impact on the performance of the governmental institutions in the Emirate of Dubai from the point of view of the managers of these institutions. This study attempts to use the analytical descriptive method to address the subject of the research. In this light, the analytical framework drawn integrates these approaches and can be applied in empirical studies. The study uses the questionnaire in data collection, which is valid and reliable according to the Cronbach’s Alpha value. A Multiple linear regression analysis has been used to predict the OP based on KG, KSR and KST. The findings showed that KG, KSR and KST were the key predictors of OP as these explained 49.6% of the total variance in Model.
Research on Hot Topics Discovery Based on Short Texts of Online Reviews

Abstract The two crucial issues for hot topics discovery based on online reviews are that the sparsity of short text features and the “long tail” phenomenon of hot topics. This paper focuses on these two key issues, and proposes an improved similarity calculation method to calculate the similarity of short texts, and a novel clustering algorithm based on the time factor and dynamic adjustment of comparison times to automatically discard a large number of outliers. Moreover, the validity and advancement of the new method are presented by comparative experiments using real data sets.
PERBANDINGAN HASIL BELAJAR IPS TERPADU MENGGUNAKAN PICTURE AND PICTURE DAN COURSE REVIEW HORAYDENGAN MEMPERTIMBANGKAN MINAT BELAJAR SISWA

Tujuan penelitian ini untuk mengetahui perbandingan hasil belajar IPS Terpadu menggunakan model Picture and Picture dan Course Review Horay dengan mempertimbangkan minat belajar siswa. Metode yang digunakan adalah komparatif dengan pendekatan eksperimen. Populasi pada penelitian ini adalah seluruh siswa kelas VIII SMP Negeri 1 Gunung Pelindung. Penentuan sampel menggunakan metode sampling jenuh, yaitu sebanyak 45 siswa. Pengumpulan data menggunakan observasi, angket, dan tes. Berdasarkan analisis data disimpulkan sebagai berikut: (1) Terdapat perbedaan hasil belajar antara siswa yang pembelajarannya menggunakan model PnP dibandingkan dengan model CRH, (2) Rata-rata hasil belajar siswa dengan model PnP lebih tinggi dibandingkan CRH pada minat belajar tinggi, (3) Rata-rata hasil belajar siswa dengan model PnP lebih rendah dibandingkan CRH pada minat belajar rendah, (4) Terdapat interaksi antara model pembelajaran dengan minat belajar.Kata kunci: Course Review Horay, Hasil Belajar, Minat Belajar Siswa, Picture and PictureThe aim of this study was to determine the comparison of students’ achievementof social studies using Picture and Picture and Course Review Horay modelconsider to the students’ learning interest. This study used comparative methodwith experimental approach. The population of this study was all the eighth gradestudents at SMP Negeri 1 Gunung Pelindung. The researcher used saturationsampling in determining the sample, the total number of students was 45 students.The data collection used are observation, questionnaire, and test. Based on theresults of the research obtained as follows: (1) There is difference of students’achievement between students who have taught by using PnP model and thestudents who have taught by using CRH model. (2) The mean score of students’achievement using PnP model was higher than CRH model in students who havehigh learning interest. (3) The mean score of students’ achievement using PnPmodel was lower than CRH model in students who have low learning interest. (4)There is an interaction between PnP and CR with students’ learning interest.Keyword: Course Review Horay, Picture and Picture, Students’ Achievement,Students’ Learning Interest
Validation of the Atomic Absorption Spectroscopy (AAS) for Heavy Metal Analysis and Geochemical Exploration of Sediment Samples from the Sebangan River

This study was to validate the Atomic Absorption Spectroscopy (AAS) in the determination of heavy metals using surface sediments from the Sebangan (estuary of Sadong River), Sarawak State, Malaysia as a case study. Aqua regia procedure was used to extract the trace elements from the sediments. The Scanning Electron Microscope was used to analyse and investigate the microstructure morphology and chemical composition characterizations of the sediments. The results of the examination confirmed to the fact that the technique validated was appropriate and less laborious for the determination of the 12 metals of interest (Al, Mn, Ca, Cd, Cu, Fe, Cr, Ni, Co, Zn and Pb) in the sediment. Massive deposits of sharp teeth granite and quartz particles of distinct tetrahedral conformation with plus size were observed in the samples investigated.
Transfer Learning in Autonomous Vehicles using Convolutional Networks

This thesis has investigated the potential benefits of using transfer learning when training convolu- tional neural networks for the task of autonomously driving a car. Three transfer learning networks were trained and compared with a conventionally trained convolutional neural network. The first conclusion is that training, as expected, is considerably quicker when using transfer learning. More specifically, transfer learning utilizes pretrained networks and does not require the entire network to be trained, rather just parts of it. This results in faster training since less weights have to be updated per epoch of training. Here, training was approximately twice as fast per epoch compared to training a non-transfer learning network. The pretrained network used in this thesis was in fact also trained, something that in a practical transfer learning setting would already have been done. The data used to train the so called pretrained network originates from a different, although similar, domain. By keeping a varying number of convolutional layers from the pretrained network fixed, three networks were trained using transfer learning. This way, knowledge is said to be transferred from a previously solved problem to the current problem. The network called fine-tuning network 2 performed better than the two other transfer learning networks when tested in the simulator. After only 7 epochs of training, this network could drive around the entire track without going off-road, even at higher speeds. This is to be compared with the so called conventional network, trained under a classic machine learning setting. Not until having been trained for 18 epochs did the performance of the conventional network match the performance of the fine-tuning network 2, trained for merely 7 epochs. In other words, in less than half the number of epochs, and with each epoch training twice as fast, a network using transfer learning performed as well as a non-transfer learning network. (Less)
LibGuides: Art: Essential Resources

A research guide to introduce you to the field of art. You'll find the materials, search tools, and other resources you need to start your research. If you need any assistance, please contact your librarian.
Developing An Extendable Web-Based Architecture For Honey Bee Data Visualization

Over the past 10 years, a paradigm shift has occurred in the field of web development as websites became web applications. Although hard to define, web applications usually refer to sites with a focus on providing responsive experiences that incorporate complex and dynamic functionality. This shift in complexity is accompanied by a shift in web technologies, as traditional LAMP stack (Linux, Apache, MySQL, and PHP) websites are replaced by JavaScript-based web applications built upon new technologies such as the MEAN stack (MongoDB, ExpressJS, Angular, and Node.js). As these new technologies become widely accepted, the need for a general and adaptable architecture for web-based dynamic data visualization using JavaScript has grown. This thesis details such an architecture. Our architecture seeks to be extendable, flexible, and largely platform agnostic, however, it is specifically designed to leverage new web paradigms such as WebSockets and full stack JavaScript web application frameworks. As a proof of concept, we have applied this architecture in a web application for the visualization of automatically analyzed honey bee hive data from the BeeMon project. This web application presents our framework in a practical scenario and provides a basic implementation for others to extend and adapt to their specific needs.
THE DEVELOPMENT OF EDUCATION IN BULGARIA

The aim of this study is to gather sufficient evidence and arguments in order to prove to society that during the process of change in thinking and especially of effective practical implementation of educational models such, high levels of efficiency can be achieved on all hierarchical levels in systems key for the society and the state .
Discovery of user access pattern and loan transactions analysis of information resources using association rules technique in data mining (Case study: Libraries and Information Centers of Hamedan University of Medical Sciences)

Increasing massive amount of data and using them to improve the quality of management decisions are the problems of libraries and information centers. In the meantime, a powerful data mining tool can analyze data to predict and analyze user transactions and stop wasting time to use useful data from among massive data, identify valid patterns and unknown relationships, and help libraries in strategic decision-making and effective management assistance. This study using association rules technique, which is one of the data mining methods, seeks to analyze the transactions of user lending and discover their access pattern. In this cross-sectional descriptive study required data were collected from transactions of users of the libraries and information centers of Hamedan University of Medical Sciences and after preprocessing these data, the total number of 6636 user transactions was 132833 using a census method during a three-year period examined. The results of this study showed that most transactions and referrals with the score of 20.7±24.4 were related to the students and the highest delay and duration of loan respectively with the score of 884.3±1396.9 and 885.7±1765.3 related to the faculty members. Also, the rules derived from the Apriori algorithm showed by providing a users access pattern based on demographic information and determining subject dependence of information resources could be used as an appropriate pattern for analyzing and predicting user transactions. Using association rules technique and implementing the Apriori algorithm, the best rules governing the data set were extracted. Therefore, using association rules technique can be designed as a book advisory system in libraries and information centers. Managers and policy-makers can also use these patterns and rules to align their supply and information resources with the real needs of their members, and can benefit greatly from library procurement, collection, management and services. © 2019 Iranian Research Institute for Scientific Information and Documentation. All rights reserved.
Data Center Visitor Sign In/Out Policy

The purpose of this policy is to ensure that access to the University Data Centers is controlled to protect the physical resources and IT Resources from unauthorized use, accidental, malicious damage, and/or theft.
Astronomy laboratory for 13-to-15-year-old students

Abstract In this work, we suggest the use of astronomical laboratory topics in didactic activities. We present two educational experiences, which we offered to last year students of the junior high school and first-year students of the technical-economic high school (ITES). Astronomy attracts the majority of students. Our idea is to use this interest as leverage to show how concepts and tools of Mathematics and Physics are essential; therefore the study of Mathematics and Physics topics becomes more explained and fascinating. For every laboratory activity, we explicate some of the Math, Physics and Astronomical concepts that can be strengthened. Every step was enriched by a brief theoretical presentation of some current research in the astronomical field, to increase the interest of students. We propose to use simple and cheap materials for all the laboratory experiences, and we suggest also using smart-phone applications as physical tools. We present three laboratory activities for the younger students and two laboratory activities for the older ones. For every topic we proposed a pre-test, to check out previous knowledge, and a post-test, to reflect if students have achieved the goals. We report the teacher’s opinion to draw some conclusions about the work done. In the end, we underline some problems and difficulties encountered.
LibGuides: Services for Faculty: Reserves

The Dean B. Ellis Library is happy to offer A-State faculty a variety of services. Learn about placing articles, notes, and books on reserve for student use.
Workshop: Professional Communication in the Age of Immersive Technology

Immersive technologies are the emerging spaces in which technical communicators must engage and learn how to navigate. This workshop aims to be a beginning to that navigation.
Improving The Reading Comprehension Of The Second Year Students Of SMPN 1 Kemuning Indragiri Hilir By Using Think Pair Share Technique Through Recount Text

This classroom action research was aimed to know whether think pair share technique can improve the reading comprehension of the second year students of SMPN 1 Kemuning Indragiri Hilir through recount text. This research consisted of two cycle. There were thirty students participated in this study. The data were collected from the reading comprehension tests, observation sheets, and field notes. The results were that The average score of pre-test was 63 (Fail). Then, the average score of the students in the first cycle-test was 75 (Good) and the last, the average score of the students in the second cycle-test was 79 (Very Good). In addition, from the observation sheets result, there was an improving of students’ participation in every single activity and also in their cognitive, affective and the psychomotor . Based on the tests, it can be concluded that think pair share technique can improve the reading comprehension of the second year students of SMPN 1 Kemuning Indragiri Hilir through recount text. This research also recommended the students and other researchers to conduct similar research to get further information.Keywords : improving, reading comprehension , think pair share tecnique , recount text
Library Consortia as Cooperation and Collaboration Initiative for Libraries

This chapter discusses the different aspects of cooperation and collaboration initiatives for libraries that includes associated opportunities, issues, and challenges. A proposed model for library consortia is depicted to illustrate the benefits that can help institutes to overcome these issues and challenges faced by the libraries for smooth functioning. The proposed cross-resource sharing model may provide an appropriate platform for both institutes and publishers that can enhance the library cooperation and collaboration in a much more effective way by overcoming the fund issues and to enable a suitable platform in improvising the library services. By achieving a successful and appropriate library consortia model, the cooperation and collaboration initiatives for the libraries gives an effective result and better services to its users.
An Efficient Digital Signature Connecting Conjugacy and DLP with Hash Function

In current paper, we plan an advanced algorithm of digital signature using conjugacy structure together with discrete logarithm inter linked non abelian group structure of field combining hash function. Here we construct a non abelian group of matrices with the elements of finite fields as F* (x) = GLn (Fq), so that conjugacy structure together with discrete logarithm can be executed effectively including hash function. Here we define and construct the signature algorithm by connecting conjugacy, discrete logarithm problem with hash function. In hash function the above combination reduces completely in to discrete logarithm problem. Here the protection of the signature scheme depending on hardness of the issues combined with discrete logarithm and conjugacy problem in matrix structure through hash function. The security check and rest of suggested procedure of digital signature is dispensed by aid of order and space complexity, time complexity, key only attack, existential forgery, signature repudiation, and selective forgery.
PROMOTING STUDENTS’S SCIENTIFIC RESEARCH ACTIVITIES: SOLUTIONS FOR IMPROVING EFFICIENCY AND APPROPRIATENESS OF INTEGRATING SOFT SKILLS FOR MODERN EDUCATION DEVELOPMENT

In the era of development, companies and businesses require graduates have to meet specialized skill as well as research skill, job adaptability and soft skills. However, most graduated students only meet specialized skill, while soft skills and research skills are slow to adapt, this leads to the re-training after the businesses recruitment. To overcome these difficulties, the article focused on analyzing the importance and reality of scientific research of Tra Vinh University students. On that basis, the author proposed solutions for improving scientific research in students in order to integrate soft skills training in a practical, effective and consistent with the educational development trend in the new age.
An Efficient Approach of GPU-accelerated Stochastic Gradient Descent Method for Matrix Factorization

Matrix Factorization (MF) is a very effective tool for Collaborative Filtering (CF) in recommender systems. As a popular solver, Stochastic Gradient Descent (SGD) is widely utilized to find MF solutions for CF. However, SGD solver often suffers from a very slow optimization process, due to its large computation burden. How to speed up it becomes a very important research topic. One of the main techniques to the problem is partitioning the matrix to factorize into blocks and calculate the factorization parallelly with these blocks. In this paper, we would like to use the most modern computation resource Graphics Processing Unit (GPU) to speed up the partition-based computation. Though there are some studies on partition-based SGD with GPUs, due to the sparsity of matrices in real-life scenarios, these methods produce too many blank blocks, which will waste the GPU computing resources. In this paper, we propose a new method, which can avoid the problem and make use of GPUs more efficiently to speed up the SGD based MF solver.
19. Computer misuse

This chapter examines computer misuse, a collective term for a number of criminal offences committed by means of a computer, often through access to the internet, including computer hacking (unauthorized access), denial-of-service attacks, and the creation and distribution of computer viruses and other malware. It first discusses hacking, focusing on employee hackers and external hackers, and then looks at the political debate surrounding the UK’s Computer Misuse Act 1990, and extradition centred on the cases of hackers Gary McKinnon and Laurie Love. The chapter also considers ‘digital criminal damage’ associated with the creation and distribution of computer viruses, along with cases of web defacement and mail-bombing.
Financial Development, Financial Structure and Economic Growth in Tanzania

This paper investigates the influence of financial structure and financial development on the performance of the economy during the period a 1990 to 2016. An econometric model is used to quantify the impact of the two variables and investment as a control variable, on economic growth. Financial structure is measured by structure-activity and structure-size while financial development is measured by finance size and finance –activity. Gross capital formation is used to measure investment. Economic growth is measured by annual change in GDP. The estimation results suggest that both financial structure and financial development were important in influencing economic growth in Tanzania during the period under study.
Applicant Information - Demonstration and Training Programs

Archived -- This page lists application kits, required forms, notices inviting applicants, schedules, and other information of interest to prospective applicants under the Demonstration and Training program (CFDA 84.235).
LibGuides: Library Services and Resources Available: Intro

Guide prepared to help faculty understand what is available via the library for them and their students