Reviewerly/exHarmony huggingface dataset:
AN ANALYSIS OF THE STUDENTS’ SKILL IN WRITING NARRATIVE AT MTS AL AMIN BRANTA PASISIR

This research was intended to to find out the students’ skill in writing narrative at MTS Al Amin Branta Pasisir. In order to solve the problem, the researcher uses descriptive qualitative The number of sample in this research was 35 students which was taken from the eighth grade students. In this research, the researcher used writing test as the instrumentation of the research where the students were asked to write a narrative text based on the topics given to them. In this research, the researcher focus on five components of narrative text written by the students such as content, organization, vocabulary, language use and mechanic. To measure students’ skill, the researcher was helped by 3 raters where the result of the analysis showed that in the content of writing, students’ average score was 52,72 and it can be classified into the poor level. In the organization of writing, students’ average score was 50,47 and it can be classified into the poor level. In the vocabulary of writing, students’ average score was 51,31 and it can be classified into the poor level. In the language use, students’ average score was 52,80 and it can be classified into the poor level. In the mechanics, students’ average score was 52,70 and it can be classified into the poor level. From those results, the researcher found that the students’ average score in writing narrative text was 52 and it means their writing skill in narrative text can be categorized in the poor level.
Tokyo Metropolitan University: Community-centric System Research Center

The Community-centric System (CcS) research center was established in 2015 to address social problems such as elderly care, social rehabilitation, and information support in the event of a disaster. This research center combines various perspectives including sensing technology, robotics, information and communication, health and welfare, urban environments, and so on. This paper provides a brief preface on the history and activities of the research center.
Tools in Term Rewriting for Education

Term rewriting is a Turing complete model of computation. When taught to students of computer science, key properties of computation as well as techniques to analyze programs on an abstract level are conveyed. This paper gives a swift introduction to term rewriting and presents several automatic tools to analyze term rewrite systems which were developed by the Computational Logic Group at the University of Innsbruck. These include the termination tool TTT2, the confluence prover CSI, the completion tools mkbTT and KBCV, the complexity tool TcT, the strategy tool AutoStrat, as well as FORT, an implementation of the decision procedure for the first-order theory for a decidable class of rewrite systems. Besides its applications in research, this software pool has also proved invaluable for teaching, e.g., in multiple editions of the International Summer School on Rewriting.
Precise cable contour extraction method based on candidate point merge search

Aiming at the problem that the existing image contour extraction algorithm can't be accurate to the pixel level, this paper proposes a cable contour extraction method based on candidate point merge search. The algorithm is divided into three steps: Firstly, the rough position of the target area is extracted by color, and the contour candidate points with larger gradients near the boundary are obtained; Then the adjacent candidate contour points are uniformly connected into several line segments and the angle of each line segment and the gradient sum through the pixel points are calculated; Finally define the target of the line segment merge and the principle of distance attenuation and angle attenuation and perform a merge search, by iterating until it merges into a complete contour. For contour sections where the correct candidate point cannot be found, it can be skipped by adding flag bit. The experimental results show that this algorithm can extract the cable contour at pixel level without manual parameter setting, which is of great significance for cable quality detection.
Information Assurance and Security Education on Undergraduate Computing Degree Programs

A set of Information Assurance and Security hands-on learning modules is developed and open to the public. Topics include networking security, database security, defensive programming, web security, system fundamentals, mobile security, malware detection using Machine learning, and big data analytics on network intrusion detection. The design follows hands-on case- based pedagogical model, which yields a satisfaction rate up to 92.5% for self-learners.
Enhancing the Ensemble-Based Scene Character Recognition by Using Classification Likelihood

Research on scene character recognition has been popular for its potential in many applications including automatic translator, signboard recognition, and reading assistant for the visually-impaired. The scene character recognition is challenging and difficult owing to various environmental factors at image capturing and complex design of characters. Current OCR systems have not gained practical accuracy for arbitrary scene characters, although some effective methods were proposed in the past. In order to enhance existing recognition systems, we propose a hierarchical recognition method utilizing the classification likelihood and image pre-processing methods. It is shown that the accuracy of our latest ensemble system has been improved from 80.7% to 82.3% by adopting the proposed methods.
LibGuides: New Technology on the Horizon: Home

A look at the technology and electronic resource advances coming to the Xavier University of Louisiana Library.
Ensemble kriging for environmental spatial processes

Remote-sensed and reanalysis databases are valuable sources of environmental data that support a wide range of engineering applications. However, the sizes of such databases are often measured in terabytes (TB). Whereas these datasets with high spatial resolution are usually stored on the servers of national laboratories, the large data volume can be inconvenient for individuals who wish to work with the data. To that end, it is important to investigate how much redundant information the dataset contains, e.g., are the time series from two adjacent pixels statistically different? We use kriging, a spatial interpolation technique, to quantify such redundancy. More specifically, if the kriged environmental processes are sufficiently accurate, one can circumvent the need to work with the original high-spatial-resolution data, and use only a dimension-reduced version of the data. The empirical part of the paper considers the National Solar Radiation Data Base (NSRDB), which provides half-hourly, gridded, satellite-derived solar irradiance data, with a spatial resolution of 4 km by 4 km, spanning 1998-2017, with a total size over 40 TB. NSRDB is a valuable dataset for solar resource assessment applications. The beam normal irradiance (BNI) process is reconstructed using data on various dimension-reduced lattices. The trade-off between spatial resolution and data accuracy is studied.
LibGuides: Learning Express Library: Home

Interactive platform that contains practice tests for standardized and placement tests at every grade level. Also contains tutorials to help improve basic math, reading, writing, and computer skills for every age. Assessment tests and career placement hel
Evaluation of Data Efficacy in Privacy-aware Computing

The Digital era marked by the unparalleled growth of Internet and its services with day-to-day technological advancements has paved way for a data driven society. This digital explosion offers huge market value to organizations and business processes who gain valuable information from the collected data to promote futuristic decision making. The aftermath of this large scale analytics is the privacy breach of sensitive information of individuals. The confidential information of people is at a risk of disclosure when it is used for a purpose not intended. Not only should privacy techniques guard classified data, but also ensure that it does not weaken data value when considered for analytical purposes. The proposed work focuses on assessing the expediency of sanitized data for analytics, using a threshold based optimal strategy for improving anonymization with large data. Classification models are trained on the anonymized data using benchmark algorithms and its accuracy is determined. The work is extended to evaluate the performance aspects of the proposed technique on diverse parallel execution environments, Hadoop and Spark.
What Are the Chances?—Hidden Markov Models

Hidden Markov Models (HMMs) can be used to solve a variety of problems from facial recognition and language translation to animal movement characterization and gene discovery. With such problems, we have a sequence of observations that we are not certain is correct—we are not sure our observations accurately reveal the corresponding sequence of actual states, which are hidden—but we do know some important probabilities that will help us. In this chapter, we will develop the probability theory and algorithms for two types of problems that HMMs can solve—calculate the probability that a particular sequence of observations occurs and determine the most likely corresponding sequence of hidden states. The chapter will end with a collection of research projects appropriate for undergraduates.
Active pulse underwater vision system

Underwater vision among existing surveillance systems plays an important role. With it, you can solve many problems in places such as emergency rescue operations, work at great depths, the study of the seabed and minerals. The development of such systems and methods of their use should be based on a fairly universal theory of visual and instrumental vision, which allows predicting the potential capabilities of optical systems of various types depending on the characteristics of the object of observation, the location of the vision system (underwater, surface), the nature of lighting (natural, artificial), optical parameters of water and atmosphere, severity of excitement, etc. The development of this theory was initiated by research on the problem of visual visibility in water under natural light. Subsequently, the issues of instrumental observation came to the fore. Their solution required, on the one hand, the development of a rather complicated section of the theory of radiation transfer), and on the other hand, the development of a qualitatively new approach to the analysis of the image formation process (based on the results of the theory of signals and noise). The usual method used to detect an underwater target is to send and receive some form of acoustic energy. But speakers have limitations in resolution and range accuracy; while the potential benefits of laser detection of underwater targets include high directivity, high sensitivity and high range accuracy. Lasers operating in the blue-green region of the light spectrum (420: 570 nm) have several applications in the field of detection and determination of the range of immersed targets due to the minimum attenuation in water (less than 0.1 m-1) and the maximum laser reflection from the calculated targets (e.g. mines or submarines) to provide early warning. The laser response from various targets (metal, plastic, wood and rubber) is detected using a high resolution CCD camera. The position of the detection camera is adjusted to provide laser radiation with high reflection from the target and noise with low backscattering from the aquatic environment, digital image processing methods are also used to detect and distinguish echo signals from a metal target and subtract echo signals from other objects. The image of the target is extracted from the scattering noise using the methods of background subtraction and edge detection. Thus, it is possible to obtain high image quality and distinguish objects in troubled waters, which systems using acoustic waves cannot allow.
LibGuides: RDA 3R and RDA Toolkit: RDA 2021

Information and links to information, web sites, webinars, etc. on RDA 3R and the RDA Toolkit
Developing Augmented Reality Application for All-in-one Interface Card

Technologies like Augmented Reality (AR) and Virtual Reality (VR) have been advanced quickly in recent years. Many hardware devices and special techniques have been developed. AR is a technology which integrates the virtual objects with the real time environment. But the critical breakthrough came, when AR spread to the smart phones, this enabled mass spread of AR applications in the field of Education, Manufacturing industries, Military, Medical etc. providing the information about the specified targets to the users. It is also one of the key technologies used in Industry 4.0. AR systems have already reached some level of maturity in educational field and the effectiveness have been widely proven. This paper proposes the development of Marker-based mobile Augmented Reality application, which demonstrates the working of RVCE All-in-one Interface Card.
Video marketing for libraries: A practical guide for librarians

"Video marketing for libraries: A practical guide for librarians." Journal of Web Librarianship, 14(1-2), p. 55
Recursion in language, theory-of-mind inference and arithmetic: aphasia and Alzheimer’s disease

We found a variety of dissociations among the linguistic and non-linguistic operations tested.In the case of Hungarian speaking patients with a medium-serious AD, syntactic recursion is relatively unimpaired, as opposed to their limited ability to tackle theory-of-mind and arithmetical recursion.Conversely, we found limited syntactic recursion but normal theory-of-mind inferences and recursive arithmetical operations in Hungarian speaking agrammatic aphasics.We argue for a model that posits a module of recursive operations in the human mind that is shared by linguistic, theory-of-mind, and arithmetical performance.
Uncertainty-Aware Authentication Model for IoT

Handling the process of authentication for the hundred million of computer embedded devices in Internet of Things (IoT) is not achievable without considering inherent IoT characteristics like scalability, heterogeneity, dependency and dynamism. In one hand, traditional and emerging access control models cannot handle indeterminate data access scenarios in IoT by applying deterministic access policies. On the other hand, moving towards resilient access control paradigms needs new attitudes and current manual risk analysis methods that rely on vulnerability calculations do not fit in IoT. This holds true as considering vulnerability as the key player in risk assessment is no longer efficient way to tackle with indeterminate access scenarios due to complicated dependency and scalability of IoT environment. Moreover, most of the IoT devices are not patchable so by discovering new vulnerabilities the vulnerable devices need to be replaced. Therefore, IoT needs agile, resilient and automatic authentication process. This work suggests a novel authentication method based on our previous work in which uncertainty was introduced as one of the neglected challenges in IoT. Uncertainty in authentication derived from incomplete information about incident happening upon authenticating an entity. Part of IoT characteristics makes such an uncertainty worse. Therefore, we have proposed an uncertainty-aware authentication model based on Attribute-Based Access Control (ABAC). Our prediction model is able to consider the uncertainty factor of mobile entities as well as fixed ones in authentication. In doing so, we have built our prediction model using boosting classifiers (AdaBoost and Gradient Boosting algorithms) besides voting classifier. We have compared the results with our previous work. Our designated model (AdaBoost) can achieve authentication performance with 86.54% accuracy.
The Mystery Game: Engaging families with children in the mysteries of the Mauritshuis

This projectThe aim of this graduation project was to find out how to make the Mauritshuis, an art gallery museum in the city centre of The Hague, relevant to visiting families with children. Thereby the focus was on how to engage the families as soon as they enter the permanent exhibition of the museum and make the museum more relevant to them accordingly. The Relevance by Play Framework (Vermeeren a Calvi, 2019) was taken as reference. To understand the message and experience that the Mauritshuis wants to provide to its visitors (and mainly families with children) with the help of the permanent exhibition, the content of the permanent exhibition, the management mission / vision and museum employees are consulted. Additionally the strengths and weaknesses of the current family product in use are reviewed as reference. The scope is broadened by looking at how other museums approach families with children. Parallel to getting to know the core of the Mauritshuis, research has been conducted with families, both parents and children, with the aim to understand their motivations, roles and interests before –and during a visit to museums in general, or the Mauritshuis specifically. This was achieved through a literature review, observations, questionnaires, interviews and generative sessions. The project visionThe research outcomes resulted in an interaction vision:I want that the Mauritshuis becomes like an exciting exploration of a goldmine. Corridor systems give confidence and guidance to curious families that decide to walk autonomously through the goldmine. When gold is discovered, it can be subtracted from the mine and taken home as a reminding reward to proudly share with others. The vision was used as base while generating product ideas. Through engaging employees of the Mauritshuis in the idea generation, a concept is developed that was assumed to be relevant to both the Mauritshuis and visiting families: the Mystery Game. The Mystery GameThe Mystery game is storytelling application on an iPad, which keeps the family together while travelling through the Mauritshuis. The family is helped to immerse in the stories behind the building: they can see a reconstruction of each room of the year 1704 when inside the rooms, with the use of animations, movies and augmented reality. The present is mixed with the past and the family is challenged to find the link between them through solving a mystery in each room. A prototype has been made of this concept as proof of concept and in order to test its relevance.
An Analysis on Consensus Protocols in Permissioned Blockchain

Blockchain had attracted many organizations around the world because it is a newtechnology that act as a distributed ledger and can be used to recording transactions. The mostunique part of blockchain is it maintained by many nodes without central authority through adistributed cryptographic protocol. In blockchain technology, all the nodes will validate theinformation that to be appended to the blockchain. Then, blockchain will updated via theconsensus protocol which used to ensure an unequivocal, common ordering of transactionsand blocks. Besides, consensus protocol also guarantees the consistency and integrity of theblockchain across geographically distributed nodes.As Blockchain being more popular and useful nowadays, many developers try to figure outthe new consensus protocol to fit into the different types of blockchain. That is, it cause manypeople confused about the consensus protocols and have no idea which is the best or mostaccurate one that can be applied to the blockchain system especially permissioned blockchainsince it can provide integrity and confidentiality simultaneously. Furthermore, there will besome differences between the consensus protocol that apply to the public blockchain andpermissioned blockchain. Therefore, too many consensus protocols and it makes the user orscholar who want to learn more about consensus protocol perplexed.In order to solve those problems, several comparisons between the consensus protocols willbe provided along with detailed explanation. This paper aims to provide a comprehensivedescription on the underlying principle, nature, operations and algorithm of the consensusprotocols by reviewing the whitepaper of the consensus protocols, research papers fromprofessionals, journals, consensus protocols sharing platforms, etc. Lastly, the authorproposed some improvements/suggestions to solve the limitations in certain consensusprotocols.
Dynavision을 이용한 시지각 훈련이 ADHD 성향 대학생의 집중력과 시지각 향상에 미치는 효과

Objective : The purpose of this study was to enhance visual perception and concentration using Dynavision program in adults with ADHD. Methods : This study was used A-B single subject design. The independent variable was a Dynavision training program(visual tracking, self-paced, apparatus-paced, digital flash). Intervention was consisted of two adapted and training sessions. Subject A was trained ten sessions. Subjects B and C were trained each seven sessions. Dependent variables were visual perception(MVPT-3, TVMS) and concentration (Stroop test, 100 cell calculation problems). MVPT-3, TVMS, and Stroop test were conducted before and after the intervention and 100 cell calculation problems were measured every session. Results : The MVPT-3 and TVMS scores were improved and the reaction time of Stroop test was decreased after intervention. In addition, as the sessions progressed, the speed of solving the 100 cell calculation problems was increased and the number of wrong answers was decreased. Conclusion : The results revealed that Dynavision training program was effective for the enhancement of ADHD adults’ visual perception and concentration. Based on the result, provision of more extended research will be conduced in ADHD children or dementia elderly.
Spline Nonparametric Regression Approach For Modeling Factors Affecting Vocational National Exam Results in Surabaya

Government policy in the field of evaluation is the holding of the National Examination (UN). Therefore, various improvements in the quality or quality of education through national examinations need to be done so that the quality of human resources really materializes as expected. Identification of factors that influence the indicators is done by modeling, namely by nonparametric regression analysis because the pattern of relationships between the variables carried out does not follow a certain pattern. The choice of nonparametric regression used is Spline, with its advantages model. Based on the analysis and discussion of the best Spline nonparametric regression model is a linear Spline model with one vertex. The resulting GCV value is 0.044. The teacher-student ratio factor at the level of vocational education influences the achievement of national student exam results in the city of Surabaya in the 2018/2019 academic year. This study still uses a linear regression program with a combination of one, two, and three knots with an R square of 65.92%. Need help developing the program into a quadratic and cubic order using a combination of knots