Reviewerly/exHarmony huggingface dataset:
Impact of Severity of Failure and Rating on Online Distributer Brand Credibility

This thesis talks about the credibility of online distributer, if it’s affected by theseverity of failure of product purchased from it; also if it varies with rating. However, forthe current study only two levels of severity of failure, i.e. no failure or high failure isconsidered; also, only two levels of rating viz. highly rated or non-rated conditions ofproduct is discussed.While previous studies have mentioned about the impact of severity of failure ofproduct on the product itself and the brand that produced it, there hasn’t been much focusgiven to the distributor which acts as mediator between the consumer and the productproducer. Earlier studies have mentioned that with increase in severity of failure thecredibility of the brand that produced the product or service decreases. This occurred as aresult of building up of negative attitude towards brand whose product fails. However thecredibility tends to be high in condition when there is no failure.In the current research the experiment involves presenting participants with scenariosinvolving high fail / no fail conditions as well as high rated (4.3 star/5 star) / non-rated (norating available for the product) conditions for the product; the rating for the product beingavailable on online distributor platform. Thus a 2x2 model of experimentation is generated.The study has been carried out specifically on people of Indian nationality and the productthat will act as stimulus is a shampoo (category-beauty). A pretest is carried out to screenthe questionnaire items to be presented in the final experiment; the questions being filterediiiafter analyzing the coefficient of alpha. After collection of data of all participants in theexperiment phase the ANOVA test is carried out to verify the hypothesis. The analysis ofall the pretest and experiment phase data has been done on SPSS 22.The results show that Online Distributor Brand Credibility is indeed affected byhigh fail/no fail as well as highly rated/ non-rated condition. The individual effect ofseverity of failure and rating is shown by the main effects of the ANOVA result. It showsthat for high fail condition the credibility is low while for no fail condition the credibilityis high. On the other hand for a highly rated product the credibility is slightly higher thanof the product that had no rating. The interaction effect result shows that when the productundergoes high fail and had high rating then the credibility is relatively low as comparedto the same situation (high fail) but the product had been non-rated. On the other hand ifthe product underwent no fail and had high rating then the credibility is relatively high ascompared to the situation when the product was non-rated.
Extending Simple Online and Realtime Tracking with Sparse Optical Flow

Detection and tracking of objects in video data is a common topic in computer vision and widely used for traffic surveillance. Simple Online and Realtime Tracking (SORT) is a Multi-Object Tracking (MOT) algorithm which performs in realtime by using efficient algorithms. SORT’s tracking performance is based on detection quality and may suffer due to detection failures. This work proposes an extension to SORT’s Kalman filter measurement model with Robust Local Optical Flow to add a velocity component to the filter’s update vector and improve robustness against detection failures and decrease track id switches. The elaborated extension, termed SORT_OF, is tested and benchmarked on parts of the MOT15 tracking benchmark as well as on a self created benchmark representing a DLR real world scenario. The proposed tracking method still works in realtime.
Peak density algorithm based on KD-tree optimization

Abstract In view of the high time complexity of the density peak algorithm, it is necessary to manually confirm the clustering center according to the decision graph. A density peaking algorithm KT-DPC based on kd-tree optimization is proposed. The algorithm defines the local density p through K-nearest neighbor and uses kd-tree to accelerate the local density p and distance 8. In addition, in the confirmation stage of clustering center, a clustering center confirmation strategy (C2BD, clustering center confirmation based on difference) is proposed. The difference between adjacent y is calculated by arranging y=p*S in ascending order, and the boundary between clustering center and non-clustering center is found according to the change of difference. This method automatically confirms the clustering center of the algorithm, avoiding the problems of strong subjectivity and insufficient clustering accuracy caused by manually confirming the clustering center. Experiments on multiple UCI public data sets show that the running time and clustering accuracy of the KT-DPC algorithm under low-dimensional data are better than traditional DPC algorithms, KNN-DPC and other improved algorithms.
LibGuides: Cataloging Work Group: Work Group Members and Charge

LSP Cataloging Work Group Main Lib Guide- information on events, documentation, and resources Overview Summary for Acquisitions and ERM
A Breast Cancer Classification Technique Based On Histological Images Using Convolutional Neural Networks

Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. The diagnosis is based on the qualification of histopathologist, who will look for abnormal cells. However, if the histopathologist is not well-trained, this may lead to wrong diagnosis. Computer-aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification. Hematoxylin and eosin stained breast histology microscopy image dataset is provided as a part of the ICIAR 2018 Grand Challenge on Breast Cancer Histology Images. Our approach utilizes several deep neural network architectures.Convolutional Neural Networks for Binary class classification and multiclass classification. The Binary class classification is used to classify the cancer cells to malignant and benign. And the Multiclass classification these classes into different subclasses like adenosis, fibroadenoma, phyllodes tumour, tabular adenoma for benign class and ductal carcinoma, lobular carcinoma, mucinous carcinoma, papillary carcinoma for malignant class. The result will show Convolutional Neural Networks outperformed the handcrafted feature based classification with high accuracy in both binary and multiclass classification.
LibGuides: Student Showcase Competition: Research Tip 4 - Write and Cite

Research examples and tips Guide providing useful links for citation and project formatting
Policy on Strengthening the Role of Libraries in Supporting Scholarly Communication at IAIN Curup

Background of the study: Libraries occupy a very strategic position in supporting scientific communication in universities. Purpose: This study aims to analyze the policy of strengthening the role of libraries in supporting scientific communication at IAIN Curup. Method: This type of research is descriptive qualitative. Data collection was carried out by means of interviews and documentation. Findings: The results of this study indicate that there are several policies that have been and will be carried out by the IAIN Curup and the IAIN Curup Library in supporting scientific communication at IAIN Curup, namely 1) regulations and development strategies in the institutional strategic plan; 2) carry out routine user education activities; 3) online research skills training for academicians; 4) providing e-resources; 5) information literacy class program for students and lecturers; and 6) book review activities. The lecturers hope that the means of scientific communication can be improved so that the role of libraries can be maximized in scientific communication activities. The concept that can be offered in order to strengthen the role and function of libraries in the development of scientific communication at IAIN Curup is the revitalization of user education by adding facilities and facilities for user education activities. Then the increase in the promotion of services and facilities at the IAIN Curup Library. Conclusion: The position of libraries in supporting scientific communication in tertiary institutions must be strengthened through policies in favor of libraries.
Structural Equation Modeling with Latent Variables

Author(s): Karimi Bidhendi, Saeed | Advisor(s): Jafarkhani, Hamid | Abstract: Discovering causal relationships between variables is a difficult unsupervised learning task, which becomes more challenging if there are unobserved common causes between pairs of variables. Often it is not feasible to uniquely recover causal relations when only observational data is available. When experimental data is obtainable through interventions, we present a method for guaranteed identification under mild assumptions. We consider a linear structural equation model where there are independent unobserved common causes between pairs of observed variables. The generative process of latent effects is given by the mixing method of blind source separation problem. Our objective is to disentangle the observed causal effects from latent confounders and learn the model parameters that are consistent with observational and experimental data. By exploiting the invariance of latent factors across various interventions, we present matching methods as a way to combine the information across various interventions. Finally, we propose an identification algorithm that uses efficient tensor decomposition for a unique recovery of model parameters and disentangling the latent confounders from observed causal effects.
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection

Real-life applications, heavily relying on machine learning, such as dialog systems, demand for out-of-domain detection methods. Intent classification models should be equipped with a mechanism to distinguish seen intents from unseen ones so that the dialog agent is capable of rejecting the latter and avoiding undesired behavior. However, despite increasing attention paid to the task, the best practices for out-of-domain intent detection have not yet been fully established. This paper conducts a thorough comparison of out-of-domain intent detection methods. We prioritize the methods, not requiring access to out-of-domain data during training, gathering of which is extremely time- and labor-consuming due to lexical and stylistic variation of user utterances. We evaluate multiple contextual encoders and methods, proven to be efficient, on three common datasets for intent classification, expanded with out-of-domain utterances. Our main findings show that fine-tuning Transformer-based encoders on in-domain data leads to superior results. Mahalanobis distance, together with utterance representations, derived from Transformer-based encoders, outperform other methods by a wide margin(1-5% interms of AUROC) and establish new state-of-the-art results for all datasets. The broader analysis shows that the reason for success lies in the fact that the fine-tuned Transformer is capable of constructing homogeneous representations of in-domain utterances, revealing geometrical disparity to out of domain utterances. In turn, the Mahalanobis distance captures this disparity easily.
An Update on GPM and TRMM Data Services at NASA GES DISC

The Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to data archives of the NASA-JAXA Global Precipitation Measurement (GPM), the Tropical Rainfall Measuring Mission (TRMM), and other NASA missions and projects. To maximize the use of NASA data products in scientific research and applications as well as for societal benefits, we provide data and information services that make datasets easy to find and use through simplification of data access for users at all levels around the world. Over the years, user-friendly data services have been developed at GES DISC, including data subsetting, format conversion, online visualization and analysis (i.e. Giovanni), user support system, etc. We routinely analyze questions, feedback, and use cases from users and algorithm developers around the world as well as best practices and new technology to improve existing services and formulate new data services. Interaction between users and algorithm developers is an important process for identifying issues in products, collecting user requirements, and improving product quality and usability. Staff members regularly communicate with algorithm developers with user questions and concerns through conferences and workshops. We publish peer-reviewed papers and articles in major Earth science journals and book chapters to describe NASA global and regional precipitation datasets and services with examples. News articles about GPM and TRMM datasets associated with significant events are regularly posted in the GES DISC Web portal and social media. We also actively participate in training activities. In this presentation, we present our latest activities about GPM and TRMM data services, data/service metrics, and future plans at GES DISC.
EstBERT: A Pretrained Language-Specific BERT for Estonian.

This paper presents EstBERT, a large pretrained transformer-based language-specific BERT model for Estonian. Recent work has evaluated multilingual BERT models on Estonian tasks and found them to outperform the baselines. Still, based on existing studies on other languages, a language-specific BERT model is expected to improve over the multilingual ones. We first describe the EstBERT pretraining process and then present the results of the models based on finetuned EstBERT for multiple NLP tasks, including POS and morphological tagging, named entity recognition and text classification. The evaluation results show that the models based on EstBERT outperform multilingual BERT models on five tasks out of six, providing further evidence towards a view that training language-specific BERT models are still useful, even when multilingual models are available.
Factors of Adolescent Girls' Knowledge in the Prevention of Iron Deficiency Anemia in Banjarbaru, Indonesia

Women, including young women, have a higher level of susceptibility to anemia, especially iron deficiency anemia. The aim of the study was to determine the inhibiting factors for young women, especially in the consumption program of iron tablets to prevent anemia. The research respondents were high school teenage girls (n = 275) in Banjarbaru, South Kalimantan. The results of the analysis show that most of the young women already have a high level of knowledge (54.2%), with the results of the interval estimation it can be concluded that the 95% confidence level that the total knowledge average value is in the range of 10.09-10.64. The answer with the highest level of incorrect occurred for items related to drinks that inhibit iron absorption. Most of the adolescent girls (50.27%) saw milk as the best drink that could be consumed along with iron tablet consumption. It is known that knowledge of young women about anemia is still not optimal. The knowledge of young women about drinks that can be taken together with iron tablets is known to be weak.
ANCAMAN TERHADAP KEAMANAN INFORMASI OLEH SERANGAN CROSS-SITE SCRIPTING (XSS) DAN METODE PENCEGAHANNYA

Information stored on websites or the internet makes it easier for users to exchange information. Of course, only authorized users have access to this information. The amount of information that is spread and stored on the internet invites people who are not entitled to get that information. Various methods are used to obtain access rights and information. One of them is to carry out an attack called Cross Site Scripting Attack. Websites become the target of this type of attack. In this paper, an explanation of what is meant by a Cross Site Scripting attack, how this attack is carried out, and ways to prevent it. Knowledge of this type of attack is indispensable for developers of Web-based information systems. Because this attack works by exploiting programming errors or writing program code in an information system.
Guides: Faculty and Staff Library Resources and Services: Open Educational Resources (OER)

This guide gathers resources to assist faculty and staff in using Western's library tools, resources, and services.
ECOLOGICAL EDUCATION OF STUDENTS AS A VALUE COMPONENT OF MODERN EDUCATION

The article substantiates the necessity of organizing ecological education of students at the first stage of school education. The analysis of the state educational standard of primary general education in order to identify the ecological component in its content. Indicators of the formation of a child's ecological culture are named, which are a guideline for a primary school teacher in the planning and implementation of ecological education. The conditions and mechanisms of upbringing the foundations of the ecological culture of the individual in younger schoolchildren are revealed. The ecological situation that has developed over the past decades on the planet has put before humanity the problem of achieving sustainable development of society. Such development presupposes not only the rational exploitation of natural resources, but also the formation of an appropriate consciousness in relation to environmental problems, the upbringing of a person capable of living in harmony with the surrounding world.
Peer Review_2 Artikel Determination of Geochemical Correlation of Cu, Pb, Zn in Stream Sediment Samples in Barru Area, South Sulawesi

The Barru area is known as the rock basement location in Sulawesi Island. The disclosure of ultramafic rock, metamorphic rock, and various sedimentary rock formations in the field and outcrops of unmapping intrusive rocks on a regional scale are certainly very interesting to be used as a media experiment in statistical methods in exploration of mineral resources. This is quite reasonable because among these rock formations are revealed intrusion of dacite and diorite rocks which are alterated and deposited as sulfides. The research gradually combines the pearson hybrid correlation geochemical stream sediment data and intrusive rocks on the relationship between SiO2, TiO2, Al2O3, Fe2O3, MnO, MgO, CaO, Na2O, K2O, P2O5, and Cr2O3 variables which are illustrated by multidimensional spatial correspondence analysis and anomalous sources based on Cr, Cu, Fe, Mn, Ni, Zn, As, Mo, Co, Sb, Cd, and Pb variables. The results showed that the application of the hybrid statistical analysis method was effective enough to identify elemental variables in identifying sulfide deposits and the characteristics of anomalies were quite different from diorite and dacite due to magmatic hydrothermal and tectonic activity.
A study on the growth of elementary pre-service teachers’ teaching skills through online English microteaching

This study aims to investigate how elementary pre-service teachers develop their teaching skills through online English microteaching. In particular, it aims to explore what pre-service teachers learned while preparing, demonstrating, and reflecting on their online microteaching. For the analysis, 30 pre-service teachers’ reflection journals were qualitatively analyzed and the instructor’s note and video-recorded microteaching were analyzed as needed. Pre-service teachers began to understand how to utilize the new teaching platform and find ways to conduct online classes by observing each others’ microteaching and discussing the merits and problems of online classes. In online classes, as teachers’ gestures were less effective, much attention began to be paid to producing effective PowerPoint slides. In order to check students’ responses and to encourage students’ participation, they started using features such as whiteboards, annotations, and private chat. Also the breakout rooms were properly used after several attempts. Prior to their online microteaching, pre-service teachers held several video conferences with group members to practice on a new teaching platform, which could enhance their professionalism as elementary school teachers. Based on the results of the study, several implications for pre-service teacher education are suggested.
BALANCED LINKED LIST: BaLL

In this paper, a modified version of linked list, called balanced linked list (BaLL), has been proposed. It performs better than standard sorted linked list (SoLL) both theoretically and experimentally for maintaining a sorted sequence of data. The modification in BaLL than SoLL is to maintain a special middle node instead of head, and to maintain the remaining nodes in two sorted lists of almost equal size. Three most basic operations, search, insert and delete, have been considered in BaLL and have been compared with the same set of operations in SoLL. For these three operations, BaLL performs theoretically 50% better and experimentally around 50% better than SoLL.
Lightweight Authentication Protocol for NFC based Anti-Counterfeiting System in IoT Infrastructure

Counterfeit medications are known as the medications that were manufactured for the purpose of deceptively representing as authentic, effective and original in the market. Such medications cause severe health issues for patients. Counterfeited drugs have an inimical effect on the human health. The legal manufacturing companies also face threats to their revenue loss due to these counterfeited medicines. In this paper, we introduce a novel authentication protocol for anti-counterfeited drugs systems based on Internet of Things (IoT) to help checking the validity of drugs ‘‘unit dosage’’. Our protocol uses the near-field communication (NFC) as it is convenient for mobile environment. The protocol also offers reliable update phase for NFC. Furthermore, our scheme is complemented with performance evaluation along with the use of random oracle model for formal security analysis.
Efektivitas Mendeley sebagai Software Bantu untuk Manajemen Referensi

The purpose of this research is to be able to determine the effectiveness of Mendeley software that can be used as an aid software for reference management. The research method used is quantitative descriptive. The unit of analysis in this study is Mendeley. Data collection techniques used are exploration (browsing), searching (searching) on the software website under study and making a checklist of characteristics of software quality based on its function as a reference management software and with relevant library studies. The results showed that Mendeley’s software was stated to be very effective because of the 8 (eight) feature indicators stated 98.75% of the checklist indicators were available. Thus the quality of Mendeley’s software is very effective to be implemented, so that this software can be used to facilitate or integrate with other software in writing scientific papers in search of the scientific references they need.