Reviewerly/exHarmony huggingface dataset:
CLaRO: A Controlled Language for Authoring Competency Questions

Competency Questions (CQs) assist in the development and maintenance of ontologies and similar knowledge organisation systems. The absence of tools to support the authoring of CQs has hampered their effective use. The few existing question templates have limited coverage of sentence constructions and are restricted to OWL. We aim to address this by proposing the CLaRO template-based CNL to author CQs. For its design, we exploited a new dataset of 234 CQs that had been processed automatically into 106 patterns, which we analysed and used to design a template-based CNL, with an additional CNL model and XML serialisation. The CNL was evaluated, showing coverage of about 90% with the 93 templates and their 41 variants. CLaRO has the potential to facilitate streamlining formalising ontology content requirements and, given that about one third of the CQs in the test sets turned out to be invalid questions, assist in writing good questions.
Fuzzy Inference Systems

The previous two chapters explained the core concepts related to Fuzzy Logic. They discussed Fuzzy Sets and how they are different from the classical/crisp sets. You also learned about various operations that can be done on them and their properties. Then you learned about membership functions, which define the membership values of each element present in a Fuzzy Set. You learned about the different types of membership functions. Later, you learned about the Fuzzy Rules and reasoning approaches that utilize the concepts of membership functions to give various Fuzzy Solutions.
Examining the Effects of Perceived Organizational Support, a Fair Rewards System, Training and Development and Information Sharing on Employees Engagement in Saudi Arabia Telecom Sector

Due to multiple outcomes of employee engagement, organizations have been emphasizing different techniques to enhance employee engagement in order to gain a competitive edge in the market. Therefore, purpose of this study is to investigate and empirically validate the relationship between employee engagement and other constructs, such as perceived organizational support, a fair rewards system, training and development, and information sharing. SPSS 18 was used to analyze the data and the findings of this study suggest that a fair rewards system is the most important construct to enhance employee engagement in Saudi Arabia’s telecom sector. Findings of this study will help professionals working in the sector to appreciate these factors when formulating programs to boost employee engagement. They will also be helpful in understanding the effects of these factors on organizations going through a major reform process at both macro and micro level.
Research on Equipment Defect Management System Based on QR Code

Abstract With the rapid development of information technology, bar code technology is widely used in information collection, logistics and warehousing, power management, and automatic identification technology, which brings huge economic benefits. The two-dimensional bar code has been widely used in various industries and departments because of its large information capacity, high security and high anti-counterfeiting, low cost and easy manufacture, high decoding reliability, and strong anti-loss and error correction capabilities. In the power equipment defect management system, the defect means that it will not cause trouble to the safe and stable operation of the power grid in a short period of time, but it may pose a safety hazard. Therefore, this paper mainly focuses on the research of equipment defect management system based on two-dimensional code. In order to improve the power system equipment, the operation and maintenance personnel can grasp the defect processing situation in time, and timely eliminate and repair the work, which can ensure that the equipment defect problem is tracked. Management without loss, continuous management of defects in poultry equipment, and promoted equipment in a safe, stable, economic operation.
Modification Tolerant Signature Schemes: Location and Correction

This paper considers malleable digital signatures, for situations where data is modified after it is signed. They can be used in applications where either the data can be modified (collaborative work), or the data must be modified (redactable and content extraction signatures) or we need to know which parts of the data have been modified (data forensics). A classical digital signature is valid for a message only if the signature is authentic and not even one bit of the message has been modified. We propose a general framework of modification tolerant signature schemes (MTSS), which can provide either location only or both location and correction, for modifications in a signed message divided into n blocks. This general scheme uses a set of allowed modifications that must be specified. We present an instantiation of MTSS with a tolerance level of d, indicating modifications can appear in any set of up to d message blocks. This tolerance level d is needed in practice for parametrizing and controlling the growth of the signature size with respect to the number n of blocks; using combinatorial group testing (CGT) the signature has size $$O(d^2 \log n)$$ which is close to the best known lower bound of $$\varOmega (\frac{d^2}{\log d} (\log n))$$ . There has been work in this very same direction using CGT by Goodrich et al. (ACNS 2005) and Idalino et al. (IPL 2015). Our work differs from theirs in that in one scheme we extend these ideas to include corrections of modification with provable security, and in another variation of the scheme we go in the opposite direction and guarantee privacy for redactable signatures, in this case preventing any leakage of redacted information.
Bayesian Meta Sampling for Fast Uncertainty Adaptation

Meta learning has been making impressive progress for fast model adaptation. However, limited work has been done on learning fast uncertainty adaption for Bayesian modeling. In this paper, we propose to achieve the goal by placing meta learning on the space of probability measures, inducing the concept of meta sampling for fast uncertainty adaption. Specifically, we propose a Bayesian meta sampling framework consisting of two main components: a meta sampler and a sample adapter. The meta sampler is constructed by adopting a neural-inverse-autoregressive-flow (NIAF) structure, a variant of the recently proposed neural autoregressive flows, to efficiently generate meta samples to be adapted. The sample adapter moves meta samples to task-specific samples, based on a newly proposed and general Bayesian sampling technique, called optimal-transport Bayesian sampling. The combination of the two components allows a simple learning procedure for the meta sampler to be developed, which can be efficiently optimized via standard back-propagation. Extensive experimental results demonstrate the efficiency and effectiveness of the proposed framework, obtaining better sample quality and faster uncertainty adaption compared to related methods.
Blockchain Technology in Maritime Transportation and Management

This chapter discusses using blockchain technology in maritime transportation and management. Blockchain technology is less than 10 years old. With a lot of its features, the new technology has the potential to solve many problems in many sectors. Nowadays, this potential attracts many companies and organizations to try the blockchain technology in their sector to find the solution to their problems, to increase their profit, and to decrease the time spent for doing their jobs. Like other sectors, there are many works in maritime transportation and management for using blockchain technology. This chapter introduces blockchain technology and examines current and future uses and applications of it in maritime transportation and management.
Bilayer synchronous measuring method of curved screen based on a line-structured light-scanning sensor

Curved screens are widely used in smart wearables, optics, aerospace, and other display fields. To overcome the difficulty of overall quality evaluation of large-area curved screens, this paper proposes a novel measuring method to realize the bilayer synchronous measurement based on line-structured light scanning. The integrated shape information of the large bilayer curved screen can be obtained by only a single probe in one scanning step. The two-step image processing in the image and three-dimensional data space is proposed to reduce the noise due to the weak reflection from the bilayer screen. To realize the large-area curved screen measurement, a splicing algorithm based on the optimization principle is also proposed to rectify the position deviation of each splicing step. A curved mobile phone screen was measured, and the experimental results effectively proved the validity of the proposed method. A camera lens was also measured to prove its potential for other multilayer parts.
EasyPZ.js: Interaction Binding for Pan and Zoom Visualizations

The creation of data visualizations has become easier as the skillbarrier to our tools has decreased. However, adding interactivity, such as gestures for pan and zoom, still requires significant coding expertise. We introduce an open-source library-EasyPZ.js-for the creation of multi-scale (pan and zoom) visualizations across desktop and mobile devices. EasyPZ is fully customizable and extendable with flexible options for interaction design. For example, it is easy to choose gestures which are compatible with selection interactions such as clicking. EasyPZ can be enabled on any SVG-based visualization on the web with one line of code, or by simply clicking a bookmark without requiring commitment to code changes. With this library, we contribute ways for the visualization community to more easily author interactive multi-scale visualizations.
Libraries of noble estates in the cultural environment of the Tambov Governorate in the late 18th – 19th centuries

The authors analyze the concept of «cultural environment», highlight its components on the example of the Tambov Governorate, show its progress. The libraries of the noble estates played an important role in the development of cultural life in province, performed memorial, in-formational and socializing functions. We reveal the trends in the development of personal collec-tions, the core of the library fund, which allowed to determine the structure of the cultural heritage – publications distributed over the 19th–21th centuries. We make the conclusion about most popular authors, books and reading fashion. The authors reconstructed an objective picture of establishing and functioning of estate libraries in this period as an element of the cultural environment. A number of technologies for creating personal libraries can be used at present. Family reading techniques are applicable in promoting reading, books and book culture.
An Effort in Teaching Invertebrates and Training Digital Literacy to the Students

Abstract Digital literacy is an ability to understand and use information in multiple formats and sources while presented through computers. The research purposes have analysed the influence of the electronic Invertebrate book on students’ digital literacy and learning outcomes, as well as describe student responses upon learning process using electronic Invertebrate book. This research used mixed-method. The research samples selected using purposive sampling. Student’s digital literacy and learning outcomes, in the form of pre-test and post-test, were analysed quantitively using normalised gain scores (g). The difference between pre-test and post-test in treatment or control class calculated using Wilcoxon test. Meanwhile, the post-test score and normalised gain score between treatment and control class calculated using Mann-Whitney test. The student’s responses through the learning process were analysed descriptive-quantitatively using questionnaire. The result revealed that about 57% of students completed the digital literacy test and 100% of them enhanced in the category of medium to high on digital literacy skills.
Educational innovation project: songs for life

This project that starts in a small town of Castellón (L'Alcora, Spain), includes a sample of 30 seniors between 60-90 years of age, who meet once a week to sing together.The participants do not have musical knowledge, the psychomotor control is varied, because this is also the difference in age, counting on one participant in a wheelchair, another with an injury to the left arm, two more with habitual deconcentration or forgetfulness.However, our proposal is aimed at the prevention of dementias, such as Alzheimer's and provide a better quality of life, therefore, although the benefits of music are multiple and varied, we collect a small sample related to our interests
An efficient learning algorithm for periodic perceptron to test XOR function and parity problem

Artificial neural network (ANN) is an important tool, which is used in numerous fields, such as computer vision, pattern recognition, signal processing, solving optimization problems, and voice analysis and synthesis. Many real-life problems, where the future events play a vital role, are based on the past history. For example, predicting the behavior of stock market indices and electrical load forecasting. In this paper, we establish an efficient learning algorithm for periodic perceptron (PP) in order to test in realistic problems, such as the XOR function and the parity problem. Here, the periodic threshold output function guarantees the convergence of the learning algorithm for the multilayer perceptron. By using the binary Boolean function and the PP in single and multilayer perceptron, XOR problem is solved. The performance of PP is compared with multilayer perceptron and the result shows superiority of PP over the multilayer perceptron.
STUDENT MOBILITY: FACTORS FOR CHOOSING INDONESIA AS A STUDY ABROAD DESTINATION

The Indonesian government encourages the process of internationalization of higher education by increaseing the number of foreign students studying in Indonesia. However, based on UNESCO student flow data in 2018, it can be concluded that Indonesia is not yet a popular study destination for students even in the ASEAN. Therefore it is necessary to investigate the factors that drive foreign students to choose Indonesia as their education location. The factors examined are: Country Environment with sub variables perception about Indonesia, academic quality, environment (climate and weather), marketing programs, immigration process, opportunities to learn language and culture,&nbsp; Institutional characteristics with sub variable programs offered, significant others who influence country choice, creative capital, significant others who influence university selection, university academic quality, financial assistance/scholarships, interaction with lecturers and research topics, university location, City Location with sub variable diversity, level of tolerance and nondiscrimination factors. Data were collected through questionnaires to 106 foreign students studying in Indonesia. The data analysis technique used Principal Component Analysis (CPA). The results show that there are 2 new factors namely academic and scholarship factor and geographic and bilateral relationships factor that are considered by foreign students to choose Indonesia as their study destination.
Developing a system for detecting the same content within the UBT academic institution, including special characters

One of the most acute problems in the academic world is plagiarism (prevention and detection). Based on this fact, numerous software systems have been developed in line with the growing demand from educational institutions. In principle, systems use string sort algorithms (matching algorithms) to detect possible cases of plagiarism. Each of them, although the original solution is prone to being sensitive in terms of security. These software platforms have some problems mainly in terms of the incompatibility of the character with the control system. This allows two identical documents (plagiarism and original) even though the same content is not detected by the system since they are written in a different alphabet (for the same characters). Plagiarism detection system addresses this problem by "translating" all data into a format where all characters are readable, exposing any document that is plagiarized (data). This is achieved by giving each character a unique value, regardless of the alphabet in which it is written in the document. This is accomplished through the implementation of different algorithms for sorting. This enables the system to face eventual errors where the client "cheats" the system and forces the system to compare documents in the database, written in an unsupported alphabet.
Anti-Cheat Tool for Detecting Unauthorized User Interference in the Unity Engine Using Blockchain

The purpose of this paper was to analyse problem of cheating in online games and to design a comprehensive tool for the Unity engine that detects and protects the applications against unauthorized interference by the user. The basic functionality of the tool is detecting and blocking unauthorized interference in the device’s memory, detecting the modification of the speed of time flow in the game and detecting time changes in the operating system. The research also examined the current potential of blockchain technology as a secure database for the game. Proposed algorithms where implemented and tested for usability and speed of operation.
OGaze: Gaze Prediction in Egocentric Videos for Attentional Object Selection

This paper proposes a novel gaze-estimation model for attentional object selection tasks. The key features of our model are two-fold: (i) usage of the deformable convolutional layers to better incorporate spatial dependencies of different shapes of objects and background, (ii) formulation of the gaze-estimation problem in two different ways, i.e. as a classification as well as a regression problem. We combine the two different formulations using a joint loss that incorporates both the cross-entropy as well as the mean-squared error in order to train our model. The experimental results on two publicly available datasets indicates that our model not only achieved real-time performance (13–18 FPS), but also outperformed the state-of-the-art models on the OSdataset along with comparable performance on GTEA-plus dataset.
Using AR in Higher Education - suggested use in the Real Estate Agency Study Program

Games, e.g. like Pokémon Go, use Augmented Reality (AR). The functionality that allows one to “see” an object through an application on a mobile phone, can also be used to test out the visual portrayal of e.g. where to put a sauna on a property. It separates itself from Virtual Reality (VR) by being a representation on top of the real world picture. VR portrays a complete virtual reality where all you can see is programmed. Since AR allow the real world to be the basis of the visual image, it provides us with a tool for different uses. Currently one uses AR to organize training for rescue operations at the Inland Norway University of Applied Sciences. Up to four different people can work in the same “world” at the same time with different vehicles; one can drive the police car, one can fly the helicopter, one can drive the ambulance, etc. All of the participants can sit in their own room and watch what the other “players” are doing in the same visual area. This provide the students with unique insight and training regarding e.g. crisis management. However, how can we support the students attending the Real Estate Study Program by using AR? One option is to place a building in an environment in order to “see” it in a particular setting. Can we cater for other needs by utilizing AR? This paper present a pre-study regarding using AR and we will here investigate the different ways AR may support the students in the Real Estate Study Program. We have discussed the use of AR with students and Real Estate Agents that may be our students' future work places. We have investigated their needs, and have in the paper presented and proposed how AR can be a support in the education in order to support the worklife for our students. We also suggest how data can be collected from the different uses and support Knowledge Management processes in the Real Estate Agencies.
A Real Time Sign Language Interpretation of forearm based on Data Acquisition Method

The popularity of the field of electromyography has reached at a height in the past few years. There are several factors that contribute to the achievement of such a height like sensor technology advancement, exponential rise of computational abilities of computer, progress in understanding of human body and increasing awareness of benefits of interdisciplinary studies. The posture and orientation are the key for the identification of the EMG signal. Sign language is based on the use of specific sign or gesture. Individual sign has three components i.e. shape of hand, movement and location of hand. Multiple signs can be identified with different postures and orientation. This paper presents the fundamental concepts of analog to digital data acquisition with the goals of recording better quality of EMG signals generated by the posture and orientation of muscles of hands. In this paper, a wireless and wearable multi sensor EMG system is developed to translate sign language into spoken language for the dumb, so that they can convey their message through sign to the person who don't know sign language by converting it into spoken form. The paper gives the introduction of EMG, calculation of mean absolute value by short time analysis, knowledge of sensors method and experimental setup along with the scope of EMG and result of the experiment and the recordings obtained.
HEvAS: Headline Evaluation and Analysis System

Automatic headline generation is a subtask of one-line summarization with many reported applications.Evaluation of systems generating headlines is a very challenging and undeveloped area.We introduce the Headline Evaluation and Analysis System (HEvAS) that performs automatic evaluation of systems in terms of a quality of the generated headlines.HEvAS provides two types of metricsone which measures the informativeness of a headline, and another that measures its readability.The results of evaluation can be compared to the results of baseline methods which are implemented in HEvAS.The system also performs the statistical analysis of the evaluation results and provides different visualization charts.This paper describes all evaluation metrics, baselines, analysis, and architecture, utilized by our system.
Deciding the Loosely Guarded Fragment and Querying Its Horn Fragment Using Resolution

We consider the following query answering problem: Given a Boolean conjunctive query and a theory in the Horn loosely guarded fragment, the aim is to determine whether the query is entailed by the theory. In this paper, we present a resolution decision procedure for the loosely guarded fragment, and use such a procedure to answer Boolean conjunctive queries against the Horn loosely guarded fragment. The Horn loosely guarded fragment subsumes classes of rules that are prevalent in ontology-based query answering, such as Horn ALCHOI and guarded existential rules. Additionally, we identify star queries and cloud queries, which using our procedure, can be answered against the loosely guarded fragment.