Reviewerly/exHarmony huggingface dataset:
Path-Based Reasoning over Heterogeneous Networks for Recommendation via Bidirectional Modeling

Heterogeneous Information Network (HIN) is a natural and general representation of data in recommender systems. Combining HIN and recommender systems can not only help model user behaviors but also make the recommendation results explainable by aligning the users/items with various types of entities in the network. Over the past few years, path-based reasoning models have shown great capacity in HIN-based recommendation. The basic idea of these models is to explore HIN with predefined path schemes. Despite their effectiveness, these models are often confronted with the following limitations: (1) Most prior path-based reasoning models only consider the influence of the predecessors on the subsequent nodes when modeling the sequences, and ignore the reciprocity between the nodes in a path; (2) The weights of nodes in the same path instance are usually assumed to be constant, whereas varied weights of nodes can bring more flexibility and lead to expressive modeling; (3) User-item interactions are noisy, but they are often indiscriminately exploited. To overcome the aforementioned issues, in this paper, we propose a novel path-based reasoning approach for recommendation over HIN. Concretely, we use a bidirectional LSTM to enable the two-way modeling of paths and capture the reciprocity between nodes. Then an attention mechanism is employed to learn the dynamical influence of nodes in different contexts. Finally, the adversarial regularization terms are imposed on the loss function of the model to mitigate the effects of noise and enhance HIN-based recommendation. Extensive experiments conducted on three public datasets show that our model outperforms the state-of-the-art baselines. The case study further demonstrates the feasibility of our model on the explainable recommendation task.
A Study on Visual Perception of Light Field Content

The effective design of visual computing systems depends heavily on the anticipation of visual attention, or saliency. While visual attention is well investigated for conventional 2D images and video, it is nevertheless a very active research area for emerging immersive media. In particular, visual attention of light fields (light rays of a scene captured by a grid of cameras or micro lenses) has only recently become a focus of research. As they may be rendered and consumed in various ways, a primary challenge that arises is the definition of what visual perception of light field content should be. In this work, we present a visual attention study on light field content. We conducted perception experiments displaying them to users in various ways and collected corresponding visual attention data. Our analysis highlights characteristics of user behaviour in light field imaging applications. The light field data set and attention data are provided with this paper.
Revisiting Mid-Level Patterns for Distant-Domain Few-Shot Recognition.

Existing few-shot learning (FSL) methods usually assume known classes and novel classes are from the same domain (in-domain setting). However in practice, it may be infeasible to collect sufficient training samples for some special domains to construct known classes. To solve this problem, cross-domain FSL (CDFSL) is proposed very recently to transfer knowledge from general-domain known classes to special-domain novel classes. Existing CDFSL works mostly focus on transferring between close domains, while rarely consider transferring between distant domains, which is even more challenging. In this paper, we study distant-domain FSL, a challenging subset of CDFSL, by revisiting the mid-level features, which are more transferable yet under-explored in main stream FSL work. To boost the discriminability of mid-level features, we propose a residual-prediction task to encourage mid-level features to learn discriminative information of each sample. Notably, such mechanism also benefits the in-domain FSL. Therefore, we provide two types of features for both distant- and in-domain FSL respectively, under the same training framework. Experiments under both settings on six public datasets, including two challenging medical datasets, validate the rationale of the proposed method and demonstrate state-of-the-art performance.
COVID19 Tracking: An Interactive Tracking, Visualizing and Analyzing Platform

The Coronavirus Disease 2019 (COVID-19) has now become a pandemic, inflicting millions of people and causing tens of thousands of deaths. To better understand the dynamics of COVID-19, we present a comprehensive COVID-19 tracking and visualization platform that pinpoints the dynamics of the COVID-19 worldwide. Four essential components are implemented: 1) presenting the visualization map of COVID-19 confirmed cases and total counts all over the world; 2) showing the worldwide trends of COVID-19 at multi-grained levels; 3) provide multi-view comparisons, including confirmed cases per million people, mortality rate and accumulative cure rate; 4) integrating a multi-grained view of the disease spreading dynamics in China and showing how the epidemic is taken under control in China.
Library Research Guides: Informatics, Computing, & Engineering: Home

Informatics encompasses subjects including library and information science and computer science.
Prototipe Sistem Informasi Manajemen Kepegawaian di Dinas Kesehatan Kabupaten Kolaka

Background: Human resource data and information management are required to be more effective and efficient to improve organization performance as a whole.The era of technological breakthrough which facilitates people to become more familiar with information technology can be used to initiate an innovation in developing a reliable human resource information system in supporting human resource management of Kolaka Health Office.Objective: This research is designed to develop a reliable human resource information system which meets the requirement of Kolaka Health Office.Methods: This research applies action research method.This method was choosen as it suits system development by prototyping.The research involves 8 respondents taken based on their qualification to answer research questions.Data collection was carried out by in-depth interview, focus group discussion and observation.The result of the research reveals that the resulting prototype has met the requirements of Kolaka Health Office and is considered to be of helpful for the human resource personnels in delivering services through a more efficient data management.
The Library: Choosing your device for University: Choosing a computer for university

A guide for Leeds Beckett University students and prospective students who are thinking about what device they should be buying to study here.
Textbook Design on Temperature and Thermodynamic Based on Problem Solving Blended Learning Model

Abstract Research has been conducted to determine the validity of the development of textbook based on problem solving-blended learning model. The development method used in this research is refer to the 4D development step of Tiagarajan modified. Validation is conducted by 5 people, they are through the validation expert and appropriate field of study. Validation data was obtained by using a sheet validation then analysed by descriptive qualitative method. There are six components of validated used to validate the textbook, including: 1) design; 2) format; 3) materials (content); 4) language; 5) presentation; and 6) the innovation and quality of learning. The result of validity of textbook based on problem solving-blended learning model is 3.3 with a valid criteria. Therefore, the textbook developed are valid and appropriate to use.
Pengujian Aplikasi Pemesanan Tiket Kereta berbasis Website Menggunakan Metode Black Box dengan Teknik Equivalence Partitioning

The train ticket booking application is an important application because it involves financial transactions. If something goes wrong can be detrimental to the parties involved. The developer of the train ticket booking application must be able to provide a guarantee that the application has been made according to the requirements and has good quality. To provide a guarantee can be done by testing the application. Testing on a product intends to check if a program has been running as per its capacities or still have blunders that should be adjusted so as to have a decent quality program. A famous testing strategy and broadly utilized by analyzers to investigate the program works out in a good way or not is Black Box Testing and White Box Testing. In this examination, the product that will be surveyed utilizing Black Box Testing is a train ticket booking framework that has two structures: the login structure and the booking type of the train pass to be filled by the administrator. The application will test utilizing Black Box Testing in which the test is just planned to see whether the program is as per the capacity that the program needs without realizing the program code utilized. The sort of testing of the Black Box Testing technique shifts one of which is Equivalence Partitions utilized by the creators in this investigation. Comparability Partitions procedure is a test dependent on entering information on each structure on the framework, each info menu will be tried and assembled by work either legitimate or invalid. Incorrect test results can be found and corrected immediately. So after testing, all requirements have been met and can be guaranteed that the train ticket booking application that has been made is error free and meets all the requirements specified.
A Theory of Hypergames on Graphs for Synthesizing Dynamic Cyber Defense with Deception

In this chapter, we present an approach using formal methods to synthesize reactive defense strategy in a cyber network, equipped with a set of decoy systems. We first generalize formal graphical security models--attack graphs--to incorporate defender's countermeasures in a game-theoretic model, called an attack-defend game on graph. This game captures the dynamic interactions between the defender and the attacker and their defense/attack objectives in formal logic. Then, we introduce a class of hypergames to model asymmetric information created by decoys in the attacker-defender interactions. Given qualitative security specifications in formal logic, we show that the solution concepts from hypergames and reactive synthesis in formal methods can be extended to synthesize effective dynamic defense strategy using cyber deception. The strategy takes the advantages of the misperception of the attacker to ensure security specification is satisfied, which may not be satisfiable when the information is symmetric.
E-162 Optimal projection angle planning tool for C-arm in augmented reality

<h3>Introduction</h3> Acquiring images at an optimal projection viewing angle during a neurointerventional procedure is important to get proper view of aneurysms, avoid vessel foreshortening, obtain accurate measurements, and perform proper vessel cannulations. In some cases, the interventionalist may look for the appropriate view under fluoroscopy by acquiring multiple projection images. This radiation exposure can be avoided by using an interactive planning software that allows manipulation of a volumetric image. This abstract describes a novel method in which the interventionalist uses wearable augmented reality (AR) device to manipulate the volumetric image and select the view that best suits the procedure stage. The AR software generates the appropriate c-arm angle and indicates whether the angle is achievable by the c-arm. <h3>Objective</h3> To provide the interventionalist a fast and intuitive way to manipulate volumetric images in order to select the best viewing angle while avoiding radiation exposure to scout for the best view. <h3>Method</h3> An AR platform was developed to render volumetric data on wearable AR headset (Hololens2 Microsoft, Redmond WA). Hand gestures, eye gaze and voice control were provided as means to interact with 3D-rendered volumetric acquisition. A digitally reconstructed radiograph (DRR) in the direction of the physicians eyes was displayed in the headset next to the volumetric rendering. The corresponding C-arm angle was displayed above the DRR. Knowing the forward kinematics of the C-arm gantry (ceiling mounted Allura FD-20, Philips, NL), the color of the text changes based on whether the angle is achievable. A pre-op cone beam computed tomography (CBCT) image was acquired during a preclinical study. The interventionalist was presented with the volumetric rendering and asked to rotate the image to find the desired view. They were able to select the best viewing angle which was achievable by the gantry. <h3>Results</h3> The interventionalist was able to achieve the desired angle without additional fluoroscopy and while remaining in the sterile field. The DRR provided a preview of what image to expect when the C-arm was moved to the calculated angle. <h3>Conclusion</h3> Augmented reality provides a new interaction paradigm in the interventional suite. Articulated hand tracking proves to be an intuitive way to rotate and move the virtual content while remaining in the sterile field. Providing the C-arm angle to achieve the desired x-ray view has a potential to reduce radiation exposure during a procedure. <h3>Disclosures</h3> <b>A. Panse:</b> 5; C; Philips Research. <b>M. Flexman:</b> 5; C; Philips Research. <b>B. Mory:</b> 5; C; Philips Research. <b>P. Webb:</b> 5; C; Philips Research. <b>P. Keenan:</b> 5; C; Philips Research.
Teknik Pengujian Equivalence Partions untuk Pengujian Aplikasi Sistem Penunjang Keputusan Pegawai Terbaik Menggunakan Black Box

The development of decision support system applications for the selection of the best employees is very important to support management in making decisions. This application must be free of errors because if there are errors can be detrimental to several parties, both the company and the employee. To guarantee that the floating application is error free, a test is needed. Testing on an application aims to check whether a program is running properly or there are still errors that must be corrected so that the program created will be a program that has good quality. The testing technique consists of White Box Testing and Black Box Testing which are widely used by testers to check the program is appropriate or not. The Best Employee Decision Support Application will be tested using Black Box Testing where the test only aims to see whether the program is in accordance with the function desired by the program without knowing the program code used. Types of testing of the various Black Box methods, one of which is the Equivalence Partitions used by the authors in this study. Equivalence Partitions Technique is a test based on data entry on each form in the Best Employee Decision Support System, each input menu will be tested and grouped according to function whether it is valid or invalid. With this test the quality of the software created can be expressed objectively very well and has fulfilled all the requirements set.
STAFF’S UNDERSTANDING OF ENGLISH LOAN WORD IN FINANCIAL TERMS (A STUDY AT PT. SARANA SULTENG VENTURA)

This research is descriptive qualitative research. It aims at finding out level of staff’s understanding of English loanword in financial terms incorporated borrowing. The objectives of this research are: to enlist the English financial loanterms commonly used by the staff of PT. Sarana Sulteng Ventura, to find out staff’s understanding on English loanfinancial terms by the staff of PT. Sarana Sulteng Ventura, and to find out the causes of difficulties encountered by thestaff of PT. Sarana Sulteng Ventura to comprehend English loan financial terms. In-depth interview, questionnaire, anddocument analysis data were collected and analyzed descriptively. There were 10 staffs that researcher took asrespondents at PT. Sarana Sulteng Ventura. Based on the result of data analysis, it was found that the staff’sunderstanding about English loan word in financial terms at PT. Sarana Sulteng Ventura was 80% categorized highlevel and 20% staffs categorized medium level.
PENGEMBANGAN BAHAN AJAR MEDIA PEMBELAJARAN MATEMATIKA BERBASIS LECTORA INSPIRE DI SEKOLAH DASAR

This research aims to develop teaching materials for mathematics learning media based on lectora inspire in elementary schools on the material of plane properties, to see the response and understanding of students. The subject of this study was the fifth grade students of SDN Pasir. Amounting to 30 students in the 2018/2019 academic year. Data collection is obtained by tests, questionnaires and documentation. The results of the study were (1) obtained an average score of expert validation of 84.15% with the category "feasible" (2) the average score of student responses with a percentage of 97.6% which was included in the "very good" category ( 3) post-test average score of 81,49% with the "very good" category so that it can be concluded that the teaching material of lectora inspire-based mathematics learning media is suitable to be used in fifth grade on plane properties and can provide understanding to studentsnin fifth grade plane properties.
Investigating Fine-Grained Usefulness Perception Process in Mobile Search

With the development and popularization of smartphones, search on mobile devices has become more and more popular in recent years. Existing research found that users’ search interaction patterns in the mobile environment are different from those in the desktop environment. As we know, there are a number of vertical results and richly informative snippets in the ranked lists of mobile search engines. Users can perceive useful information from both the snippet and the landing page of a result. Therefore, we consider that it is necessary to investigate how users interact with mobile search engine result pages and their fine-grained usefulness perception processes. In this paper, we collected fine-grained usefulness annotations for mobile search results in a user study dataset. With the user behavior information in the dataset, we investigate the patterns of users’ examination and click behavior and propose a user model for the fine-grained usefulness perception process in mobile search. Our research sheds light on improving user models in mobile search evaluation metrics and other mobile search-related applications.
QUALITY AND FEATURE OF MULTIPLE-CHOICE QUESTIONS IN EDUCATION

The quality of multiple-choice questions (MCQs) as well as the student's solve behavior in MCQs are educational concerns. MCQs cover wide educational content and can be immediately and accurately scored. However, many studies have found some flawed items in this exam type, thereby possibly resulting in misleading insights into students’ performance and affecting important decisions. This research sought to determine the characteristics of MCQs and factors that may affect the quality of MCQs by using item response theory (IRT) to evaluate data. For this, four samples of different sizes from US and China in secondary and higher education were chosen. Item difficulty and discrimination were determined using item response theory statistical item analysis models. Results were as follows. First, only a few guessing behaviors are included in MCQ exams because all data fit the two-parameter logistic model better than the three-parameter logistic model. Second, the quality of MCQs depended more on the degree of training of examiners and less on middle or higher education levels. Lastly, MCQs must be evaluated to ensure that high-quality items can be used as bases of inference in middle and higher education. Keywords: higher education, item evaluation, item response theory, multiple-choice test, secondary education
New semantics for urn logics: taming the enduring scandal of deduction

&#x0D; &#x0D; &#x0D; The traditional theory of semantic information, originally proposed by [Bar-Hillel, Carnap, 1953], provides a versatile and pretty plausible conception of what kind of thing semantic information is. It embodies, however, the so-called “scandal of deduction”, a thesis according to which logical truths are informationally empty. The scandal of deduction is prob- lematic because it contradicts the fact that ordinary reasoners often do not know whether or not a given sentence is a logical truth. Hence, it is plausible to say, at least from the epistemological standpoint of those reasoners, that such logical sentences are really inform- ative. In order to improve over traditional theory, we can replace its classical metatheory by the so-called urn logics, non-standard systems of logic (described in detail below) that better describe the epistemological standpoint of ordinary reasoners. Notwithstanding, the applic- ation of such systems to the problem of semantic information faces some challenges: first, we must define truth-conditional semantics for these systems. Secondly, we need to precisely distinguish two systems of urn logic, namely, perfect and imperfect urn logics. Finally, we need to prove characterization theorems for both systems of urn logic. In this paper we offer original (and hopefully, elegant) solutions for all such problems.&#x0D; &#x0D; &#x0D;
Analysis of Partial Semantic Segmentation for Images of Four-Scene Comics

Ways of understanding human creations with the help of artificial intelligence (AI) have increased; however, those are still known as being one of the most difficult tasks. Our research challenge is to find ways to understand four-scene comics through AI. To achieve this aim, we used a novel dataset called “Four-scene Comics Story Dataset”, which is the first dataset made by researchers and comic artists to develop AI creations. In this paper, we focused on the partial semantic segmentation of features such as eyes, mouth, or speech balloons. The semantic segmentation task of comics has been difficult because of the lack of annotated comic dataset. To solve this problem, we utilized the features of our dataset and easily created annotated dataset. For the semantic segmentation method, we used a model called DeepLabv3+. The effectiveness of our experiment is confirmed by computer simulations showing the segmentation result of test images from four-scene comics.
IMPLEMENTATION OF KAHOOT APPLICATION AS A STRATEGY TO GROW THE SPIRIT OF COMPETITION FOR STUDENTS

STMIK STIKOM Indonesia students are millennials who are literate with technology. Kahoot is a game platform in Education that is based online is one way to increase student motivation in learning English. This popular learning media will be tested on students on the final agenda in each meeting session. This application can not only be done in classroom learning, but in the process of live sessions in online learning or e-learning. This study will use a qualitative descriptive analysis of the implementation of Kahoot at the end of the session, which aims to find out whether the Kahoot platform is able to increase the motivation of students to compete in learning English, and how the process of implementing the game in the classroom and in live sessions.