Reviewerly/exHarmony huggingface dataset:
Deductive Querying of Natural Logic Bases

We introduce a dedicated form of natural logic intended for representation of sentences in a knowledge base. Natural logic is a version of formal logic whose sentences cover a stylized fragment of natural language. Thus, the sentences in the knowledge base can be read and understood directly by a domain expert, unlike, say, predicate logic and description logic. The paper describes the inference rules enabling deductive querying of the knowledge base. The natural logic sentences and the inference rules are represented in Datalog providing a convenient graph form. As such, the natural logic knowledge base may be viewed as an enriched formal ontology structure. We describe various query facilities including pathway finding accommodated by this setup.
Mobile AR Solution for Deaf People

In the last two years, the authors’ research has been focused on designing a smart solution to compensate for hearing or visual deficiencies using the Google Glass hardware device and its own software architecture. This paper presents a solution aimed on deaf people or people with hearing impairment. At the beginning of this paper there is a brief explanation of the architecture of the designed solution, a description of the user interface through Google Glass. Related work to face detection, visual activity detection and speech recognition is presented with many possible approaches to these research areas. The principle of the solution lies in the combination of face detection and subsequent assignment of the recognized speech to the mouth of the correct face in the image. The aim of the solution is to digitally capture the ambient sound and based on its evaluation using neural networks, to present detected speech in a text form assigned to detected face from camera stream. The testing has shown that the solution is beneficial, and it is working as expected. Machine Learning Kit provides good results in face detection and communication with Google Cloud Speech API is fast enough for smooth user experience.
The Human Factor in Managing the Security of Information

The article discusses the findings of analyses of information security levels in Polish universities and presents the results of comparative analyses performed currently and those of security level studies conducted in 2008. The re-examination has demonstrated that there has been no significant improvement in the level of security. Despite the increase in public awareness of threats on the Internet and the increase in general public’s ability to protect their own information resources, the analogous trend in universities has not occurred. Resources are still not adequately protected. The authors present the results of the comparative analysis and try to explain this paradox in conclusion.
Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks

In structured output prediction tasks, labeling ground-truth training output is often expensive. However, for many tasks, even when the true output is unknown, we can evaluate predictions using a scalar reward function, which may be easily assembled from human knowledge or non-differentiable pipelines. But searching through the entire output space to find the best output with respect to this reward function is typically intractable. In this paper, we instead use efficient truncated randomized search in this reward function to train structured prediction energy networks (SPENs), which provide efficient test-time inference using gradient-based search on a smooth, learned representation of the score landscape, and have previously yielded state-of-the-art results in structured prediction. In particular, this truncated randomized search in the reward function yields previously unknown local improvements, providing effective supervision to SPENs, avoiding their traditional need for labeled training data.
A Preliminary Study on the Curriculum Review of the English Language Courses at Akademi Pengajian Bahasa, UiTM

Curriculum is defined as an articulation of knowledge, skills and attitudes in the context of intentional and organized programmes of study. The content of curriculum may be organised through learning areas and subjects, as well as through activities or tasks. This study focuses on the needs analysis of a curriculum review of English language courses offered by Akademi Pengajian Bahasa, UiTM, with consideration to Education 5.0, Fourth Industrial Revolution (4IR), and Sustainable Development Goals (SDGs). The objectives of the curriculum review and the needs assessment are to validate the curriculum with the contemporary developments in the world. Twenty-four stakeholders from various faculties and industries, as well as representatives of UiTM alumni were invited to a two-day pre-workshop on how the future of language curriculum should be. Their opinions and feedback on the current language skills and courses were recorded and analysed. Thus, common themes were identified. Amongst the suggestions given were to increase opportunities to speak, to build character and image, and to bridge courses based on new media needs. This also includes the need to focus on the ability to discuss and express ideas clearly in group discussions. The implications of this exercise serve as the guideline of a framework for relevant and future language skills and courses, which will fulfil the needs of the 21st century communication skillsets.
Electromagnetic-wave propagation through an array of superconducting qubits: Manifestations of nonequilibrium steady states of qubits

We report a theoretical study of the propagation of electromagnetic waves (EWs) through an array of superconducting qubits, i.e., coherent two-level systems, embedded in a low-dissipation transmission line. We focus on the near-resonant case as the frequency of EWs $\ensuremath{\omega}\ensuremath{\simeq}{\ensuremath{\omega}}_{q}$, where ${\ensuremath{\omega}}_{q}$ is the qubit frequency. In this limit we derive the effective dynamic nonlinear wave equation allowing one to obtain the frequency-dependent transmission coefficient of EWs, $D(\ensuremath{\omega})$. In the linear regime and a relatively wide frequency region we obtain a strong resonant suppression of $D(\ensuremath{\omega})$ in both cases of a single qubit and chains composed of a large number of densely arranged qubits. However, in narrow frequency regions a chain of qubits allows the resonant transmission of EWs with greatly enhanced $D(\ensuremath{\omega})$. In the nonlinear regime realized for a moderate power of applied microwave radiation, we predict and analyze various transitions between states characterized by high and low values of $D(\ensuremath{\omega})$. These transitions are manifestations of nonequilibrium steady states of an array of qubits achieved in this regime.
Automated Proofs of Unique Normal Forms w.r.t. Conversion for Term Rewriting Systems

The notion of normal forms is ubiquitous in various equivalent transformations. Confluence (CR), one of the central properties of term rewriting systems (TRSs), concerns uniqueness of normal forms. Yet another such property, which is weaker than confluence, is the property of unique normal forms w.r.t. conversion (UNC). Recently, automated confluence proof of TRSs has caught attentions; some powerful confluence tools integrating multiple methods for (dis)proving the CR property of TRSs have been developed. In contrast, there have been little efforts on (dis)proving the UNC property automatically yet. In this paper, we report on a UNC prover combining several methods for (dis)proving the UNC property. We present an equivalent transformation of TRSs preserving UNC, as well as some new criteria for (dis)proving UNC.
Analysis of SLA Compliance in the Cloud - An Automated, Model-based Approach

Service Level Agreements (SLA) are commonly used to specify the quality attributes between cloud service providers and the customers.A violation of SLAs can result in high penalties.To allow the analysis of SLA compliance before the services are deployed, we describe in this paper an approach for SLA-aware deployment of services on the cloud, and illustrate its workflow by means of a case study.The approach is based on formal models combined with static analysis tools and generated runtime monitors.As such, it fits well within a methodology combining software development with information technology operations (DevOps).
Steady state particle swarm

This paper investigates the performance and scalability of a new update strategy for the particle swarm optimization (PSO) algorithm. The strategy is inspired by the Bak–Sneppen model of co-evolution between interacting species, which is basically a network of fitness values (representing species) that change over time according to a simple rule: the least fit species and its neighbors are iteratively replaced with random values. Following these guidelines, a steady state and dynamic update strategy for PSO algorithms is proposed: only the least fit particle and its neighbors are updated and evaluated in each time-step; the remaining particles maintain the same position and fitness, unless they meet the update criterion. The steady state PSO was tested on a set of unimodal, multimodal, noisy and rotated benchmark functions, significantly improving the quality of results and convergence speed of the standard PSOs and more sophisticated PSOs with dynamic parameters and neighborhood. A sensitivity analysis of the parameters confirms the performance enhancement with different parameter settings and scalability tests show that the algorithm behavior is consistent throughout a substantial range of solution vector dimensions.
A Technique for Selection and Drawing of Scatterplots for Multi-Dimensional Data Visualization

Scatterplot matrix and parallel coordinate plots are well-used multi-dimensional data visualization techniques. These techniques have a problem that they need a very large screen space when an input dataset has an enormous number of dimensions. To solve this problem, we propose a method for selecting important scatterplots from all scatterplots generated from input datasets and for drawing the scatterplots as ”outliers” and ”regions enclosing non-outlier plots.” The technique is useful for users to determine whether to delete outliers from the datasets and form mathematical models of non-outlier plots. This paper introduces an example of visualization using this technique with a retail transaction dataset and climate values.
Generative Well-intentioned Networks

We propose Generative Well-intentioned Networks (GWINs), a novel framework for increasing the accuracy of certainty-based, closed-world classifiers. A conditional generative network recovers the distribution of observations that the classifier labels correctly with high certainty. We introduce a reject option to the classifier during inference, allowing the classifier to reject an observation instance rather than predict an uncertain label. These rejected observations are translated by the generative network to high-certainty representations, which are then relabeled by the classifier. This architecture allows for any certainty-based classifier or rejection function and is not limited to multilayer perceptrons. The capability of this framework is assessed using benchmark classification datasets and shows that GWINs significantly improve the accuracy of uncertain observations.
A Family of Robust Stochastic Operators for Reinforcement Learning

We consider a new family of stochastic operators for reinforcement learning with the goal of alleviating negative effects and becoming more robust to approximation or estimation errors. Various theoretical results are established, which include showing that our family of operators preserve optimality and increase the action gap in a stochastic sense. Our empirical results illustrate the strong benefits of our robust stochastic operators, significantly outperforming the classical Bellman operator and recently proposed operators.
CONCEPTUAL FRAMEWORK FOR LIGHTWEIGHT CIPHERTEXT POLICY-ATTRIBUTE BASED ENCRYPTION SCHEME FOR INTERNET OF THINGS DEVICES

The purpose of this paper is to propose a conceptual model for data security in the Internet of thing devices. Estimated by Jumoki in early 2018 to 2022, there will be about 18 billion connected IoT devices. Therefore many issue related to IoT devices were discussed especially data security. Cryptography with lightweight features is one of the focus area by researchers to develop a powerful cryptography scheme for IoT devices. Lightweight cryptography scheme has been discussed and proposed widely recently. There are AES, PRESENT, Hash algorithm declared as a lightweight algorithm under consideration in ISO/IEC 29192 “Lightweight Cryptography”. Unfortunately these lightweight algorithm is one-to-one communication cryptography technique. This algorithm is very practical to implement for individuals or for small group communication but unpractical when implemented in a big company where many users can become a bottleneck. Therefore we propose a lightweight Ciphertext Policy-Attribute Based Encryption (CP-ABE) algorithm to implement in IoT devices. CP-ABE algorithm is one-to-many technique suitable for secure grouping communication, but this algorithm is not a lightweight feature. Therefore this paper proposes a lightweight CP-ABE algorithm for IoT devices.
Educational Needs Analysis of the Career Specialist Teacher's Tasks in Elementary Schools

The purpose of this study was to analyze the educational needs of career specialist teacher’s tasks in elementary schools. The participants of this study were 583 career specialist teachers assigned to the elementary schools in Seoul Metropolitan City in 2018. The survey was developed based-on Jeong et al. (2017)’s research. The data were analyzed with the method of educational needs analysis. There were two major findings. First, the primary tasks that need to be dealt with in educational training for career specialist teachers were as follows: organization of career education classes and guidance of career education curriculum configuration; provision of career education material or information; interpretation of career psychological test results; student career counseling support; securing career experience budgets; community network management; selection of community career experience places; and method consultation for community career experience place programs. Second, the tasks to be dealt with in other ways and the tasks dealt with through training should be distinguished. The tasks to be dealt with in other ways require the support of the Ministry of Education, the District Office of Education, and the school. The implications of the research were also presented.
Penerapan Teknik Clustering Sebagai Strategi Pemasaran pada Penjualan Buku Di Tokopedia dan Shopee

Pustaka Aysha is one of the online bookstores in Shopee and Tokopedia. Shopee and Tokopedia are online shopping sites that are top ranked in Indonesia. The amount of competition that exists between stores so that requires a marketing strategy. This research uses clustering techniques in data mining marketing strategies. Clustereing is one technique in data mining to find data sets that have similarities with other data or data dissimilarity with others. The clustering process is carried out using k-means and k-medoids on the sales transaction data of the Pustaka Aysha bookstore in Shopee and Tokopedia on March 2019 and consists of each of the 488 data divided into 3 clusters namely the first cluster for the most product in demand, the second cluster for products that are quite popular and the third cluster for products that are of little interest. Both of these algorithms will be clustered evaluation to find out which algorithm has better performance in this research, the evaluation process is carried out using davies bouldin index to maximize inter cluster distance and minimize intra cluster distance, so the results obtained that the k-medoids algorithm have performance better than k-means.
Comparing Information Needs of Diabetes Patients in Chinese and American Health Communities of Questions and Answers.

This study selects the users generated content in diabetes groups of ManYouBang and DailyStrength which are two representative HCQA (Health Communities of Questions and Answers). Theme coding was applied to identify information needs while social network analysis was used to compare Chinese and American HCQA. In theory, we combine Social Network Analysis and content analysis to capture and contrast the pattern of Q&A in HCQA. On the one hand, the core needs of HCQA are "how to treat the disease" and the "diet" theme is closely related to other themes. On the other hand, the Chinese diabetes communities have "question and answer attributes" while the American diabetes communities have both "question and answer attributes" and "social support attributes." In practice, the founding provides enlightenment for the development of HCQA including improving content quality and strengthen emotional connection and disease treatment infrastructure.
An Improved Topsis Method Based on Cloud Model for Risk Assessment of Failure Modes of Metro Vehicle

In order to improve the quality of the risk prioritization results of failure modes for metro vehicle, a new risk prioritization approach of failure modes is proposed based on the improved TOPSIS and cloud model. Firstly, three risk factors are considered, namely severity (S), occurrence (O), and detection (D). The risk factors and their importance weights of risk factors are assessed using linguistic information. Secondly, considering uncertainty and diversity of experts’ assessment information, linguistic assessment information is converted to corresponding clouds model. Then, the method of solving the weight of risk factors is proposed based on cloud model. Thirdly, an improved TOPSIS method is used to evaluate risk of the failure modes. Finally, a numerical example and a comparison analysis are provided to demonstrate the feasibility and effectiveness of this method.
PROVIDING EXPLICIT STRATEGY INSTRUCTION TO ENHANCE STUDENTS’ READING COMPREHENSION AT ENGLISH FOR ISLAMIC STUDIES CLASS

The aim of research is to identify the effects and advantages of providing explicit strategy instruction to enhance students’ reading comprehension at English for Islamic Studies class of IAIN Pontianak . Th is was a classroom action research, and its data were collected through reading comprehension test, observation, interview , and document review . Then, the data were analysed though interactive model data analysis. The results showed that, after providing explicit instruction of comprehension strategy, students’ reading comprehension improved for they became more strategic and more metacognitive when reading after being introduced with reading comprehension strategy explicitly.
Construction of A Nautical Knowledge Graph Based on Multiple Data Sources

Nie, Q.; Sheng, X.; Zhang, N.; Wang, J.-J.; Shang, Y.-G., and Hu, F.-H., 2019. Construction of a nautical knowledge graph based on multiple data sources. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 223–226. Coconut Creek (Florida), ISSN 0749-0208.To automatically recognize the nautical chart symbol is a difficult task; the first recognize step works well by the image recognition methods based on deep neural networks, however, these symbols usually have their own domain meanings which are different from their common meanings; a feasible method to improve the task is using domain knowledge to describe the domain meanings of these symbols. This paper proposes an automatic nautical knowledge graph construction method based on multiple data sources. The data sources adopted include structured data like data in relational databases, semi-structured data like data from web pages, and unstructured data like text. The author uses different methods to extract knowledge from these three types of data sources, including the rule-based method, wrapper method and machine learning method, etc. Then the author tests the proposed method by using it to establish a knowledge graph for the nautical industry. The established knowledge graph contains about 1,500 concepts and over 250 million hyponymy relations, about 80 million entities and about 30 million relations among the entities; and the average precision of these knowledge is above 0.9. The experimental result proves that the proposed method is precise and efficient.
Feature Extraction of Mild Cognitive Impairment Using a Dual-Task of Drawing and Counting Test

From the perspective of preventive care, a monitoring function that detects a decline in cognitive function would be useful as an information and communications technology (ICT) based service for watching over elderly people. We developed a system that evaluates cognitive functioning by simultaneously measuring dual tasks using a tablet computer. The tasks comprised a spiral drawing task and a color change counting task. The objective of this research is feature extraction of mild cognitive impairment (MCI) using this system. To do so, we compared the results of dual task tests for three participant groups: elderly people with suspected MCI, healthy elderly people, and healthy young people. The analyses were based on the amount of time required for drawing each section and the drawing velocity. The results indicate a significant difference between the MCI elders and the other two groups regarding the amount of time required for drawing the section close to the center of the spiral if the difficulty of the test’s sub-task is adjusted.
Color Refinement, Homomorphisms, and Hypergraphs

Recent results show that the structural similarity of graphs can be characterized by counting homomorphisms to them: the Tree Theorem states that the well-known color-refinement algorithm does not distinguish two graphs G and H if and only if, for every tree T, the number of homomorphisms $$\mathsf {Hom}(T, G)$$ from T to G is equal to the corresponding number $$\mathsf {Hom}(T, H)$$ from T to H (Dell, Grohe, Rattan 2018). We show how this approach transfers to hypergraphs by introducing a generalization of color refinement. We prove that it does not distinguish two hypergraphs G and H if and only if, for every connected Berge-acyclic hypergraph B, we have $$\mathsf {Hom}(B, G) = \mathsf {Hom}(B, H)$$ . To this end, we show how homomorphisms of hypergraphs and of a colored variant of their incidence graphs are related to each other. This reduces the above statement to one about vertex-colored graphs.
Astronomical apps for teaching astronomy

Mobile phones and tablet computers are ubiquitous, and the variety of apps (short for software applications, or programs) available for these platforms is daunting to wade through. In this month’s column, I will describe some traditional astronomical apps, and some that aren’t so traditional but may be helpful for teaching certain otherwise difficult astronomical concepts.