Reviewerly/exHarmony huggingface dataset:
LibGuides: Cataloging Toolbox for International Government Information: Home

Cataloging, classification and subject vocabularies used in creating metadata description for International Governmental Organizations.
Comparison of Heuristic Algorithms for Path Planning in 3D Printing with Multistage Experimentation System

The objective of this work is to present the implemented algorithms to solving path planning in 3D printing problem. The algorithms have been compared on the basis of the obtained results of simulation experiments. As the indices of algorithm’s performance the total distance, the energy cost, and the time cost are taken into account. The designed and implemented two-stage experimentation system is described. The simulation experiments have been carried on along with own experiment design. Short analysis of the obtained results allowed for recommendation of the most promising algorithms.
Simple and Robust Automatic Detection and Recognition of Human Movement Patterns in Tasks of Different Complexity

In many different research areas it is important to understand human behavior, e.g., in robotic learning or human-computer interaction. To learn new robotic behavior from human demonstrations, human movements need to be recognized to select which sequences should be transferred to a robotic system and which are already available to the system and therefore do not need to be learned. In interaction tasks, the current state of a human can be used by the system to react to the human in an appropriate way. Thus, the behavior of the human needs to be analyzed. To apply the identification and recognition of human behavior in different applications, it is of high interest that the used methods work autonomously with minimum user interference. This paper focuses on the analysis of human manipulation behavior in tasks of different complexity while keeping manual efforts low. By identifying characteristic movement patterns in the movement, human behaviors are decomposed into elementary building blocks using a fully automatic segmentation algorithm. With a simple k-Nearest Neighbor classification these identified movement sequences are assigned to known movement classes. To evaluate the presented approach, pick-and-place, ball-throwing, and lever-pulling movements were recorded with a motion tracking system. It is shown that the proposed method outperforms the widely used Hidden Markov Model-based classification. Especially in case of a small number of labeled training examples, which considerably minimizes manual efforts, our approach still has a high accuracy. For simple lever-pulling movements already one training example per class sufficed to achieve a classification accuracy of above $$95\%$$ .
An Enhanced Authentication Technique to Mitigate the Online Transaction Fraud

Online transactions provide benefits to the customer and financial organization in terms of reducing operating cost, time, efforts, papers, and increasing the comfort and ease. Beside these benefits online transaction has a side effect likeforged online transaction. This side effect results in loss of money. This forged online transaction is performed by fraudsters who are well equipped with the dynamic novel idea to steal an amount of money from the customer through online transaction. Although security measures are already implemented this forged online transactions are increasing every year. This is happening due to fraudsters creating novel ideas continuously to perform forged online transaction. Therefore, security measures need improvements continuously on a regular basis. The key aspiration of this paper is to create an improved authentication technique to prevent forged online transaction. This study produces an enhanced authentication using a mobile application to mitigate online transaction fraud.
Research on the Effects of Learning environment on Students' Academic Performance

This paper evaluated whether the learning environment can affect students' performance in reading, mathematics and science. Using the data from PISA, the paper analyzed the relationship between having classic literature, books of poetry, and works of art and students' scores in reading, mathematics and science using Hotelling's T-squared test and three-way between-subjects MANOVA.
Hear about Verbal Multiword Expressions in the Bulgarian and the Romanian Wordnets Straight from the Horse’s Mouth

In this paper we focus on verbal multiword expressions (VMWEs) in Bulgarian and Romanian as reflected in the wordnets of the two languages.The annotation of VMWEs relies on the classification defined within the PAR-SEME Cost Action.After outlining the properties of various types of VMWEs, a crosslanguage comparison is drawn, aimed to highlight the similarities and the differences between Bulgarian and Romanian with respect to the lexicalization and distribution of VMWEs.The contribution of this work is in outlining essential features of the description and classification of VMWEs and the cross-language comparison at the lexical level, which is essential for the understanding of the need for uniform annotation guidelines and a viable procedure for validation of the annotation.
A PROCEDURE FOR AUTOMATIC ADAPTATION TO THE USER IN INTELLIGENT VIRTUAL AGENTS

This paper describes procedures for improving the functionality of task-oriented intelligent virtual agents (IVAs) and carrying out adaptation to the user in such agents.The functionality improvement is based on automatic extension of input patterns (rules), using a database of interchangeable phrases.This extension results in greater flexibility both regarding the user's input and the agent's output.The adaptation to the user relies on a complexity measure, allowing the agent to assess the level of complexity of the user's input and thus to adapt the complexity level of its response.For the case of a simple travel information agent, the pattern extension procedure resulted in an increase in the number of available patterns of around a factor 20, greatly enhancing the agent's capacity of adapting its output to the user.
The Challenge of Imputation in Explainable Artificial Intelligence Models

Explainable models in Artificial Intelligence are often employed to ensure transparency and accountability of AI systems. The fidelity of the explanations are dependent upon the algorithms used as well as on the fidelity of the data. Many real world datasets have missing values that can greatly influence explanation fidelity. The standard way to deal with such scenarios is imputation. This can, however, lead to situations where the imputed values may correspond to a setting which refer to counterfactuals. Acting on explanations from AI models with imputed values may lead to unsafe outcomes. In this paper, we explore different settings where AI models with imputation can be problematic and describe ways to address such scenarios.
A novel architecture based on fuzzy cognitive maps and holonic systems for decision making in a cooperative context

Ensuring consistency and good decision making is one of the most topical problems in an information system; it becomes more difficult in a cooperative context. In this paper, we propose an architecture based on fuzzy cognitive maps (FCM) tool and holonic multi-agent paradigm that enhance the decision making process in cooperative information system (CIS). Furthermore, the concept of ontolgy is used for semantically enrich our architecture. We modelled each sub-CIS by a holonic agents where everyone used a FCM for a more precise analysis of complex dynamic system decisions. This group will try to make a collective decision to solve any given distributed problem. To put our approach into practice, we considered road safety field to see how to educate people in order to reduce the fatal accidents number. Finally, we validated our proposition through experiments to show how it improves the decision making process in a cooperative context.
Automatic Traveltime Picking Using Structure-Enhanced High-Dimensional Time-Frequency Transform

Summary Traveltime picking is an important step in seismic data processing, and it plays an important role in tomographic imaging. In this paper, we discuss a structure-enhanced high-dimensional time-frequency analysis algorithms for automatic traveltime picking based on instantaneous traveltime. By using a high-dimensional time-frequency transform operator that depends on prior structure information, the improved method introduces the lateral continuity of the recorded data and picks up the traveltime automatically. Testing this approach on field seismic data reveals its properties and shows it can accurately do the automatic seismic events picking.
A FOCUS-PLUS-CONTEXT VISUALIZATION FOR STRENGTH EXERCISE TRAINING

Regular strength exercise training is recommended by the WHO.Usersespecially novices or patientscall for intensive supervision to execute strength exercises correctlyeven if performed with a fitness device.Usually, a trainer or a physiotherapist provide guidance and assist the user.However, increasing costs and missing experts call for new solutions that support the user to perform strength exercises correctly and without supervision of an expert.This paper describes the fitness system SMART-FIT.The system comprises a cable machine, a notebook, and a tablet PC providing visual feedback during strength exercise training.36 participants volunteered in our user study, designed as within-subject experiment.Performing a shoulder exercise, participants tested 3 different visual feedback interfaces: 2-Pillar, 1-Pillar, and Ribbon.We evaluated the effect of the interfaces on the performance, e.g., Pearson's correlation coefficient.Additionally, we applied the questionnaires Flow-Short-Scale, NASA-TLX, AttrakDiff2, and System Usability Scale among others.The results of our user study will enable designers to make more appropriate design choices for future exercise support systems.
Conclusion – Finishing the Race

We hope that you had the light switch moment while reading this book. Web programming is complex but it does not need to be complicated or convoluted. The pursuit of developer happiness and maintainability productivity is endless. But the pursuit can be painless too.
A Study on Agent-Based Web Searching and Information Retrieval

In this day and age of information overload, it becomes difficult to filter information that is relevant to our needs. World Wide Web is the largest database of information available to us. It stores information using the hypertext paradigm, i.e., interlinking web pages through hyperlinks, which users can click on to access related information. An agent acting on behalf of humans, can make the task of sifting through information to find what we need easier for us. This paper focuses on the application of intelligent agents in the field of web browsing and searching, mostly web spidering, indexing, and retrieval of information most relevant to us, based on keywords, from the vast database of knowledge available.
The Condition of the Cryptocurrency Market and Exchanges in Poland

The development of the cryptocurrency market and the implications for the whole economy and finance for all traders cause a keen interest in this subject. The chapter discusses the functioning of a financial system based on cryptocurrencies and its significance for economies. In this chapter, the development of the global cryptocurrency market was presented and the history of the most popular cryptocurrency, bitcoin, was analyzed. The analysis and the assessment of the state and structure of the Polish cryptocurrencies market were presented on the background of the global cryptocurrency market. Also, we presented the possible development paths for the cryptocurrencies market in Poland and in the world.
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards

We propose a new complexity measure for Markov decision processes (MDPs), the maximum expected hitting cost (MEHC). This measure tightens the closely related notion of diameter [JOA10] by accounting for the reward structure. We show that this parameter replaces diameter in the upper bound on the optimal value span of an extended MDP, thus refining the associated upper bounds on the regret of several UCRL2-like algorithms. Furthermore, we show that potential-based reward shaping [NHR99] can induce equivalent reward functions with varying informativeness, as measured by MEHC. By analyzing the change in the maximum expected hitting cost, this work presents a formal understanding of the effect of potential-based reward shaping on regret (and sample complexity) in the undiscounted average reward setting. We further establish that shaping can reduce or increase MEHC by at most a factor of two in a large class of MDPs with finite MEHC and unsaturated optimal average rewards.
Financiadores da pesquisa brasileira e os dados científicos abertos.

Recent studies indicate that Brazilian and international development agencies have included initiatives for funded research projects to present a scientific data management plan for open access sharing. In order to investigate this issue, a research was developed with the following objectives: a) To identify the main financiers of Brazilian research; b) identify if there are institutional policies for open scientific data; c) Analyze policies regarding their character (mandatory or recommendatory), coverage and support. This is an exploratory-descriptive, qualitative study supported by bibliographical-documentary research. Data from the institutions that promote research in Brazil were recovered through the extraction of information from the Lattes Platform, using the scriptLattes tool. As a result, 15 national and 15 international agencies were selected to promote research in Brazil. Information on Policy or Open Data Instruction was located in five national agencies. In relation to the international ones, they were located in nine agencies. As a model, a framework of criteria was used to analyze the coverage of the open funding policies of the UK funders, provided by the Digital Curation Center (DCC) in its electronic portal. The model of the applied study addressed aspects of the characterization of the Agencies that foment the research developed by Brazilian researchers. Its adaptation to different realities, and / or objectives, will depend on the introduction of other variables that act on the interactions, according to the interest of the study.
Scaling of Fault Damage Zones and Implications for Naturally Fractured Reservoirs

Summary In this study, we focus on fault damage zones in carbonate rocks. We analyse fracture damage from small-scale outcrops to map-scale analyses, using scanlines adjacent to fault cores ( Figure 1a, b ) far from fault tip zones, and aerial images. This enabled the detailed characterisation of 12 faults, on which we define the Displacement-Thickness relationship. We analyse the resulting scaling laws and discuss their properties with respect to the map scale observations and previous models proposed in the literature. Finally, we propose new explanations based on fault segmentation and linkage and discuss their application to NFR.
Research Guides: News: Where to Get Your News

Resources for getting reliable news fast. Steps for solving various off-campus database access problems.
3D Object Trajectory Reconstruction using Instance-Aware Multibody Structure from Motion and Stereo Sequence Constraints

Three-dimensional environment perception is a key element of autonomous driving and driver assistance systems. A common image based approach to determine three-dimensional scene information is stereo matching, which is limited by the stereo camera baseline. In contrast to stereo matching based methods, we present an approach to reconstruct three-dimensional object trajectories combining temporal adjacent views for object point triangulation. We track two-dimensional object shapes on pixel level exploiting instance-aware semantic segmentation techniques and optical flow cues. We apply Structure from Motion (SfM) to object and background images to determine initial camera poses relative to object instances as well as background structures and refine the initial SfM results by integrating stereo camera constraints using factor graphs. We compute object trajectories using stereo sequence constraints of object and background reconstructions. We show qualitative results using publicly available video data of driving sequences. Due to the lack of suitable ground truth, we create a synthetic benchmark dataset of stereo sequences with vehicles in urban environments. Our algorithm achieves an average trajectory error of 0.09 meter using the dataset. The dataset is on our website <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> publicly available.
AI now masters six-player poker

Computer ScienceComputer programs have shown superiority over humans in two-player games such as chess, Go, and heads-up, no-limit Texas hold'em poker. However, poker games usually include six players—a much trickier challenge for artificial intelligence than the two-player variant. Brown and Sandholm developed a program, dubbed Pluribus, that learned how to play six-player no-limit Texas hold'em by playing against five copies of itself (see the Perspective by Blair and Saffidine). When pitted against five elite professional poker players, or with five copies of Pluribus playing against one professional, the computer performed significantly better than humans over the course of 10,000 hands of poker.Science , this issue p. [885][1]; see also p. [864][2] [1]: /lookup/doi/10.1126/science.aay2400 [2]: /lookup/doi/10.1126/science.aay7774
Ontology Design Rules Based on Comparability via Particular Relations

The difficulty of representing and organizing knowledge in reasonably complete ways raises at least two research questions: "how to check that particular relations are systematically used not just whenever possible but whenever relevant for knowledge providers?" and "how to extend best practices, ontology patterns or methodologies advocating the systematic use of particular relations and, at the same time, automatize the checking of compliance with these methods?". As an answer, this article proposes a generic "ontology design rule" (ODR). A general formulation of this generic ODR is: in a given KB, for each pair of knowledge base objects (types or individuals) of a given set chosen by the user of this ODR, there should be either statements connecting these objects by relations of particular given types or statements negating such relations. This article further specifies this ODR and shows its interests for subtype relations and other transitive relations, e.g. part relations and specialization relations with genus & differentia. This article shows how this ODR can be implemented via OWL and SPARQL, at least for common simple cases (and, generically, via an higher-order logic based language).
A Topic Modeling Approach to the Analysis of Issues for Kids Creators

1인 미디어 크리에이터로 참여하는 아이들의 수가 점차 증가하고 있으며, 이에 대한 사회적 관심이 또한 증대되고 있음에도 불구하고 이에 대한 학술적 논의는 매우 미미한 실정이다. 이에, 본 연구에서는 뉴스 데이터 분석을 통하여 ‘키즈 크리에이터’들이 현재 우리 사회에서 어떠한 이슈를 만들어내고 있으며, 우리 사회는 이들을 어떻게 바라보고 있는지를 포착해보고자 하였다. 빅카인즈(BigKinds)를 통하여 2,947개의 뉴스 데이터를 수집 후 중복 데이터를 제거하고, 적합성 검토를 수행하여 517개의 뉴스 데이터를 최종 분석대상으로 선정하였다. 이어 해당 뉴스 데이터에 등장하는 단어들의 속성을 추출하고 이에 담긴 잠재적인 정보를 발굴하는 토픽 모델링을 수행하여 6개의 토픽을 추출하였다.Recently, the number of children participating as one-person media creators is gradually increasing, and social interest is also increasing. However, there is no comprehensive study on social issues related to the kids creators. This study examines how the kids creators are perceived through news data analysis. This study analyzed the related news data by applying the text mining technique. In other words, the collection of news data was carried out through Bigkines. A total of 2,947 news items were gathered, and the redundancy and relevance were reviewed. Finally, 517 news items were included for the LDA, one of topic modeling techniques. Six major topics were extracted.
KNOWLEDGE SHARING AND JOB PERFORMANCE FROM PSYCHO-SOCIAL PERSPECTIVES: A CONCEPTUAL STUDY ON AL AIN MUNICIPALITY IN UAE

Purpose of the study: The purpose of this paper is to assess the knowledge sharing and job performance from psycho-social perspectives on Al Ain Municipality in UAE.&#x0D; Methodology: Since this is a conceptual study, so this paper only focuses on the literature survey and logical explanation based on the facts discussed.&#x0D; Results: The results of this study show that loss of knowledge can result in duplication of work, unreasonable searches for expertise and knowledge, and employees not learning from the experienced. Not all knowledge in the organisations is of critical value, and therefore need not be captured and retained, but the critical knowledge that is at risk of loss should be captured.&#x0D; Implications: The awareness of knowledge loss through staff attrition may motivate companies to institutionalise specific processes to capture the tacit knowledge of their employees as much as possible. It is advisable for firms to have strategies in place on how to capture and retain their workforce’s knowledge.&#x0D; Novelty: This research contributes significantly on the knowledge management from psycho-social perspectives and from the vantage point of United Arab Emirates. Upon the analysis of the data collected, the research may provide recommendations for the policy makers, academicians, practitioners as well as decision-makers and other stakeholders.
Card Game (Part 1)

Card games are always one of the best starting points to learn game development. They feature all the characteristics that a game needs, but they often have very streamlined graphics and aesthetics, which is good and makes them an easy pick for game development’s beginners.
Search-Based Motion Planning for Aggressive MAV with Limited Sensors FOV

This paper presents a search-based motion planning method to generate resolution-complete, collision-free, dynamically feasibility trajectories for Micro Aerial Vehicles (MAVs) aggressive flight in an obstacle-cluttered environment. This method searches for smooth trajectories by exploring the map using a set of short-duration motion primitives. The primitives are generated by solving an optimal control problem and induce a finite lattice discretization on the state space which can be explored using a graph-search algorithm. Finally, we extend the search-based planning approach for Aggressive MAV with constraints on Field-of-View (FOV) while navigating in an unknown, obstacle-cluttered environment, and the MAV uses its onboard depth sensor (RGB-D or event camera) with FOV to detect obstacles, and perform real-time trajectory re-planning. Simulation results demonstrate the feasibility of the generated trajectories in an obstacle-cluttered environment.
FPGA Implementation of Data Fusion Algorithms

In general, all tasks that urge any type of parameter estimation from several sources can benefit from the use of information /data fusion methods. The fused data is highly appreciated because of less probability error detection with high reliability using data from several distributed sources. Data Fusion algorithms are important because of its less probability error. Implementation of these algorithms as standalone hardware requires their conversion to either ASICs or FPGA. But fabrication of ASIC require sophisticated foundry facilities that are not easily accessible. FPGAs provide a good alternative for such implementations. Therefore in this paper, foundations of FPGA implementation of MATLAB algorithm is showcased with the help of an illustrated synthetic problem. This will enable the researchers to realize the implementation of various algorithms developed for different applications.