Reviewerly/exHarmony huggingface dataset:
Easing Function as a Tool of Color Correction for Display Stitching in Virtual Reality

For many multimedia applications, the image stitching problem is very important. We analyzed this problem for the SEMI-CAVE virtual reality installation. In this study, we aim to analyze the manner in which color changes for correcting image stitching with regard to human perception (subjective evaluation of stitching quality). We propose to use Penner’s easing function for changing color of image stitching and obtain a proper perceptual transition of color. A series of experiments were conducted in the SEMI-CAVE environment. 27 participants assessed the quality of the black-to-white transition realized using 7 different Penner’s functions. The participants assessed the smoothness of the transition and the occurrence of perceptual artifacts. The analysis of the experimental results showed that the InOutSine function provides the best perceptual effects. Moreover, the obtained results (ranking of functions from the best to the worst) were statistically confirmed using Chi-square analysis.
Enhancing Personal Professional Development Through Technology Integration

In this chapter, personal professional development trainings, which need to include ubiquitous learning environments, are discussed. First of all, professional development is explained. Then, the authors discussed factors affecting the efficiency of professional development activities and how they can incorporate new technologies into professional development activities to meet the needs of adult learners. After that, based on the definition of ubiquitous learning, ways of using technology in terms of meeting adult needs with professional development are examined. Finally, the process that was evaluated within the framework of technology integration is presented to readers.
Improving the Classification of Q&amp;A Content for Android Fragmentation Using Named Entity Recognition

Despite the huge amount of high quality information available in socio-technical sites, it is still challenging to filter out relevant piece of information to a specific task in hand. Textual content classification has been used to retrieve only relevant information to solve specific problems. However, those classifiers tend to present poor performance when the target classes have similar content. We aim at developing a Named Entity Recognizer (NER) model to recognize entities related to technical elements, and to improve textual classifiers for Android fragmentation posts from Stack Overflow using the obtained NER model. The proposed NER model was trained for the entities API version, device, hardware, API element, technology and feature. The proposed classifiers were trained using the recognized entities as attributes. To evaluate the performances of these classifiers, we compared them with other three textual classifiers. The obtained results show that the constructed NER model can recognize entities efficiently, as well as discover new entities that were not present in the training data. The classifiers constructed using the NER model produced better results than the other baseline classifiers. We suggest that NER-based classifiers should be considered as a better alternative to classify technical textual context compared to generic textual classifiers.
Improved TF-IDF for We Media Article Keywords Extraction

Abstract Keyword extraction is one of the work of computer text topic mining, and it is also the basis of text analysis and public opinion analysis. The keywords extracted by the traditional TF-IDF algorithm are mainly calculated based on the word frequency. The importance of other feature words with fewer occurrences and the comments of readers below the article are not considered. Aiming at the above problems, this paper improves the traditional TF-IDF algorithm, adds the part of speech and the reader’s comment as the impact factor, and recalculates the weight of TF-IDF, so that the accuracy of the algorithm is improved. This paper uses the Python language programming to crawl from the media article and implement the improvement of the algorithm. Experiments show that the improved TF-IDF algorithm has significantly improved compared with the traditional TF-IDF, in terms of accuracy, recall rate, F1, MacAvg_P, MacAvg_R and MacAvg_F1.
Identifying User Preferences Through an Application for Autistic Children Using Inclusive Design Models

Due to a deficit on cognitive ability and language skills, children with intellectual disabilities, especially with autism, do not engage in participatory design activities. Using an inclusive design approach, children with autism are able to have more effective participation during the design, however for this it is necessary to adapt participatory design methods, making them more contextualized with children's daily activities. Participatory methods use games and light activities for people to bring out their design ideas, considering their needs and preferences. Children with autism need a more structure-activity with a very well-defined goal for them to feel comfortable. In this context, this paper, describe the implementation of a ludic application in line with the precepts of inclusive design to identify children with intellectual disabilities ways of thinking aiming at finding possibilities for adaptation of tools using participatory design methods.
A New Approach Based on the Bee Optimization Algorithm for Ontology Alignment

The ontology alignment process aims at generating a set of correspondences between entities of two ontologies. It is an important task, notably in the semantic web research, because it allows the joint consideration of resources defined in different ontologies. In this article, the authors developed an ontology alignment system called ABCMap+. It uses an optimization method based on artificial bee colonies (ABC) to solve the problem of optimizing the aggregation of three similarity measures of different matchers (syntactic, linguistic and structural) to obtain a single similarity measure. To evaluate the ABCMap+ ontology alignment system, authors considered the OAEI 2012 alignment system evaluation campaign. Experiments have been carried out to get the best ABCMap+'s alignment. Then, a comparative study showed that the ABCMap+ system is better than participants in the OAEI 2012 in terms of Recall and Precision.
Resilient Collaborative Intelligence for Adversarial IoT Environments

Many IoT networks, including for battlefield deployments, involve the deployment of resource-constrained sensors with varying degrees of redundancy/overlap (i.e., their data streams possess significant spatiotemporal correlation). Collaborative intelligence, whereby individual nodes adjust their inferencing pipelines to incorporate such correlated observations from other nodes, can improve both inferencing accuracy and performance metrics (such as latency and energy overheads). Using realworld data from a multicamera deployment, we first demonstrate the significant performance gains (up to 14&#x0025; increase in accuracy) from such collaborative intelligence, achieved through two different approaches: (a) one involving statistical fusion of outputs from different nodes, and (b) another involving the development of new collaborative deep neural networks (DNNs). We then show that these collaboration-driven performance gains are susceptible to adversarial behaviour by one or more nodes, and thus need resilient mechanisms to provide robustness against such malicious behaviour. We also introduce an under-development testbed at Singapore Management University (SMU), specifically designed to enable real-world experimentation with such collaborative IoT intelligence techniques.
Enhancing story generation with the semantic web

In story or character driven games, in-game stories are usually manually authored in advance. As the complexity of interactions in games increases, the quantity of hand-crafted text typically follows. Designing stories and composing content by hand is a laborious and time consuming process that if automated, would speed up game production and lower development costs. In this paper, we present a mixed initiative tool to help generalize and enhance context free grammars (CFGs) for story generation. The tool is designed to take as input a story generating grammar in addition to generic keywords for people, places and other various metrics in order to control the output text. The tool is knowledgeable about a wide array of topics because it leverages the Semantic Web in order to extrapolate more details and related information from the user supplied content. As a result, generated text will contain genuinely new information, descriptions of characters and locations that were never written by the author. Although the general structure of a story or dialogue is somewhat fixed by the nature of grammar rules, the resulting text can be geared towards a variety of user inputs and can include details that may surprise designers. The tool is evaluated by a group of 15 individuals in a user study to gauge the practicality of using Semantic Web technologies for procedural text generation. The study concludes that using the Semantic Web is an effective aid for grammar based text generation. We discuss our system, the user study and share thoughts on future work.
Information Systems Architecture and Technology Security Aspects Relating to the Usability Attributes and Evaluation Methods of Mobile Commerce Websites

It was demonstrated that many mobile commerce (m-commerce) websites failed to attract customers, due to not being user-friendly and a lack of security relating to user interfaces. Among research accessed, none conducted usability evaluations where security as attribute was evaluated on m-commerce applications. Therefore, a new usability model for m-commerce applications is proposed, including security as usability attribute having direct effects on the market behavior and efficiency of users’ experiences with m-commerce applications. The research addressed the imbalance in literature by conducting a usability evaluation incorporating security, aiding validation of the proposed usability model. The study also addressed the lack of security attribute as instance of existing usability models and proposed a domain-specific evaluation method for usability evaluation of m-commerce websites. The outcomes showed that users consider security to be an important parameter when navigating m-commerce websites. Therefore, mobile application design and web design should look at optimizing the performance of security attributes for m-commerce websites, boosting customers’ shopping online quality of service.
Label Propagation Guided by Hierarchy of Partitions for Superpixel Computation

Superpixel computation can be seen as a process of grouping similar pixels trying to preserve image boundaries. In this work, we propose a label propagation method guided by hierarchy of partitions in the context of the marked (supervised) segmentation problem. The main idea of the proposed method is to propagate labels on a tree modelling a hierarchical representation of the image. We propose several criteria to decide, in the case of a conflict, which of the competing labels must be propagated into a neighbor region of the tree. According to our experiments, the proposed method outperforms the baseline provided by the SLIC method.
SimON-Feedback: An Iterative Algorithm for Performance Tuning in Online Social Simulation

Simulation of human behaviour being an intrinsically difficult problem, no single algorithm or model can accurately simulate online social networks. One can obtain an optimal and reliable simulation only after combining several models focusing on diverse social aspects. Since all independent models focus on different social aspects, it is inherently difficult to combine and optimize their performance. Moreover blackbox nature of these predictive algorithm makes it difficult to integrate human-guided intelligence. Here we are presenting SimON-Feedback, an iterative ensemble algorithm to combine the prediction of several independent models into a significantly improved simulation of an online social network. To this end, we explore user posting and commenting behavior on Reddit, a large social networking platform comprised of many communities called as subreddits.
Anarchy

Pseudo-random number generators are ubiquitous components of content generation systems, because their outputs are difficult to predict but also repeatable given an initial seed. These properties make them especially useful as the basis for "random" decisions during a generative process, as they allow the process to be chaotic but also repeatable. This paper describes an open-source family of pseudo-random algorithms which allow for shuffling and distributing items in a reversible and incremental manner. To demonstrate the applicability of these algorithms, I show how they have been used in the creation of a word-search game which includes strong guarantees about the distribution of words that can be discovered.
Eliminating Trust Issues in Islamic Interbank Monetary System by Blockchain Technology

In the literature, it is argued that there is an agency or incentive problem in the Mudarabah Interbank Instrument (MII), an instrument where the depositor is the rabbul-mal (capital provider or investor) while the counterparty is the mudarib or entrepreneur. It is to the receiving bank's advantage to ‘declare' a lower profit rate. To solve this problem, the Malaysian Central Bank revised the rules by setting a minimum benchmark rate for the MII. This practice is quite similar to the fixed interest rate in conventional financial system which may trigger several Shariah issues. In this chapter, the authors argue that the blockchain technology is a better way to address the issue and propose and how it overcomes the issue in the Islamic interbank money market. As implication of the study, Islamic banks can start using it as a testing process for the future businesses, and in accordance with the analyzing test results, they can implement the system for every occasion.
Analysis of Possibility of the Combination of Affine Cipher Algorithm with One Time Pad Cipher Using the Three-Pass Protocol Method in Text Security

Abstract The use of the Three-Pass Protocol method in exchanging secret text messages is one effective method because the two interested parties do not need to use a single key to open the message sent. But there is a possibility that the message cannot be described because the cipher used is not suitable. The purpose of this study is to show whether the Affine Cipher Algorithm with One Time Pad Cipher using the Three-Pass Protocol method can be used to encrypt and decryption the text message.
A Kind of Static Software Birthmark Based on Control Flow

Abstract In traditional static k-gram birthmark algorithm, the result of plagiarism detection is inaccurate. It is a new method for plagiarism detection that using the software birthmark based on program control flow in this paper. First, it is used to the result of static that analysis of the Java program as meta information, analyze meta information to get byte stream instruction in method. Then, a byte instruction stream in the method to get the control flow structure of the program has been analyzed, and replaced the external references with external control flow structures, using this control flow structure as a software birthmark. Finally, it is calculated that the similarity between two birthmarks by VF2 algorithm, thus determining whether there is plagiarism between the two programs. It is shows that birthmark which presented in this paper are more credible than traditional SKB birthmarks in experimental results.
Approach to Forecasting Behaviour of Dynamic System Beyond Borders of Education

The problem of forecasting behavior of a complex dynamic system is considered. The analysis of the approaches allowing in the conditions of limitation of information and parametric uncertainty on behavior character to predict with high accuracy behavior of systems for situations at which value of control parameters go beyond the limits of the used training set is carried out. The estimation of forecasting results is executed, the corresponding graphs are presented, conclusions are drawn.
Formalization of Asymptotic Notations in HOL4

Asymptotic notations characterize the limiting behavior of a function. They are extensively used in many branches of mathematics and computer science particularly in analytical number theory, combinatorics and computational complexity while analyzing algorithms. Traditionally, the mathematical analysis involving these notations has been done by paper-and-pencil proof methods or simulation. In order to introduce formal verification in this domain, this paper provides the higher-order-logic formalizations of O, Θ, Ω, o and w notations and the formal verification of most of their classical properties of interest. The formalization is based on the theory of sets, real and natural numbers and has been done using the HOL4 theorem prover.
Classification Betters Regression in Query-Based Multi-document Summarisation Techniques for Question Answering

Task B Phase B of the 2019 BioASQ challenge focuses on biomedical question answering. Macquarie University's participation applies query-based multi-document extractive summarisation techniques to generate a multi-sentence answer given the question and the set of relevant snippets. In past participation we explored the use of regression approaches using deep learning architectures and a simple policy gradient architecture. For the 2019 challenge we experiment with the use of classification approaches with and without reinforcement learning. In addition, we conduct a correlation analysis between various ROUGE metrics and the BioASQ human evaluation scores.
Shortest Path Search Simulation on Busway Line using Ant Algorithm

Abstract Busway lane must be planned carefully, so that it can reach a number of points in an area efficiently. Problem that occurs is how to find the shortest route in a busway lane, this problem can be solved by using Ant algorithm. Naturally, ant colony will be able to find the shortest path on their way from nest to food sources by using pheromone. The Ant algorithm procedure to find shortest path in this research is using 100 ants to track all the path in a busway lane, drop pheromone on each path, the shorter a path is, the more pheromone gets accumulated on the path, and pheromone evaporates in each iteration. After going through a number of iterations, the pheromone will accumulate on the shortest path and all ants will follow the shortest path. Application can be used to find the shortest path from a busway lane planning in Medan using Ant algorithm. For a maximum of 30 terminals, ant algorithm requires only about 28 seconds to find the shortest route.
Discover MyPlate: Nutrition Education for Kindergarten

Childhood obesity prevention remains a significant public health initiative. Educating children about nutrition from an early age is 1 strategy used to encourage the development of habits for a lifelong healthy eating pattern. Discover MyPlate: Nutrition Education for Kindergarten is a resource that provides lessons teachers can integrate into math, science, language arts, and health. These lessons are intended to meet core education standards, so while children are practicing counting, reading, and writing, they are learning skills to build a healthy lifestyle.
Discriminating aggregate sources with <i>in situ</i> mineral chemistry: an Irish example

The need to characterize and distinguish geographically adjacent aggregate quarry sources prompted the SEM-EDS analysis of pyrite (FeS2) within fill material taken from eight different quarry sources. This experiment was undertaken to investigate the possibility of geochemically separating these quarry sources based on the major element concentration of their pyrite. The results show that median values for Fe and S vary by up to 7.6 and 8.55 wt% respectively. By implementing statistical methods, including k-means clustering and principal component analysis, it is possible to geochemically discriminate three of the eight sources.
The Potential of Lacquer Peel Profiles and Hyperspectral Analysis for Exploration of Tailings Deposits

Lacquer peel profiles are a valuable technique to preserve and study sedimentary structures and depositional features outside the field. The use of the lacquer fluid Mowiol® has shown to work well as a simple and rapid preparation technique for tailings material from a tailings heap in Copiapó, Chile. The combination of lacquer peels with 2D mapping techniques such as Hyperspectral Imaging (HSI) can provide important sedimentary information such as particle size distribution on a large scale with little effort, which becomes quantifiable due to continuous 2D information and modern image analysis. The presented relationship of element or mineral distribution with particle size can serve as a tool for targeted and more focused sampling for mineral exploration in tailings and tailings analysis in general, considering future selective mining for economic or environmental reasons.
Ore Mineralogy of High Sulfidation Çorak-Taç Epimesothermal Gold Deposit (Yusufeli-Artvin-Turkey)

Çorak and Taç, two nearby mineralizations, are located in the eastern black sea region, which is one of the most productive metallogenic belts of Turkey. It is characterized by a great number of Kuroko-type volcanogenic massive sulfide deposits as well as vein-type polymetallic deposits, porphyry and epithermal precious metal deposits. Subject neighboring deposits are hosted within the voluminous Cretaceous-Eocene granitoids and interbedded volcanic rocks and carbonates. Mineralogy of altered host rocks include quartz veins, carbonates, sericite, chlorite, chalcedony, and disseminated sulfides - mainly pyrite, sphalerite, galena, and chalcopyrite. The main texture encountered in the host rocks is hyalo-porphyry. Due to hydrothermal alterations primary minerals are mostly altered in which the ferromagnesian minerals are chloritized and calcified, while feldspars are altered into sericite, calcite, and albite. Silicification and argillic alteration (medium, moderate, high) are widely spread however; XRD analysis carried on 33 core samples from Çorak has also revealed local propylitic alteration, limonitization and hematitization as well. The minerals assemblages that accompanied the different alterations include jarosite and alunite suggesting high sulfidation hydrothermal mineralization. Through the ore microscopic studies, pyrite, chalcopyrite galena, sphalerite, and a lesser amount of sulfosalts (tennantite-tetrahedrite and pyrargyrite) were determined. Quartz and calcite account for the main gangue minerals. While the Taç mineralization is pyrite, chalcopyrite and sphalerite dominating, the Çorak mineralization contains relatively less chalcopyrite and galena becomes prevalent with sphalerite. Gold in both sites may reach up to 10 ppm, on average 3 ppm. Silver occurrence is insignificant.