Miracle-dz/UniFAR-FTUs huggingface dataset:
Walking a Mile in Simulated Shoes : Development of an Assessment of Perspective Taking

Success in today’s global environment is often contingent on one’s ability to effectively navigate culturally complex situations. This ability, referred to as cross-cultural competence (3C), is actually a constellation of abilities that enables individuals to adapt to a wide range of interpersonal contexts. Despite the importance of 3C, adequate measurement of 3C is lacking and often overly reliant on self-evaluation, which can be inherently biased or unreliable. As a result, other methods by which 3C can be more validly assessed are being explored. This project focuses on one such method, namely, a game-based assessment of perspective taking. Perspective taking, a critical sub-facet of 3C, is a socialemotional skill that enables individuals to consider another’s point of view. In cultural contexts, perspective taking is particularly important, as it not only facilitates awareness of how cultural norms influence behavior, but also allows for more accurate prediction of behavior in future situations. The simulation described here takes place on an alien planet and requires players to complete several quests in service of a larger game goal. Each of the quests require players to learn about the planet’s culture and use what they’ve learned, along with their perspective taking skills, to achieve quest goals. Players’ skill levels are inferred from the decisions they make and the amount of feedback they require to successfully complete each quest. The presentation will focus on the theoretical foundation for the game’s development, as well as address the operationalization of the construct, game design, learning objectives, and scoring criteria.
Retraction Retracted : Collaborative Filtering Recommendation Algorithm Based on Knowledge Graph Mathematical Problems in Engineering

At the request of the authors, the article titled “Collaborative Filtering Recommendation Algorithm Based on Knowledge Graph” [1] has been retracted. The article was found to contain a substantial amount of material, without citation, from an earlier article in Chinese by other authors; [2] its details are as follows: XiyuWu,Qimai Chen, Hai Liu, and Chaobo He, “Collaborative filtering recommendation algorithm based on representation learning of knowledge graph,” Computer Engineering, 2018, 44(2): 226-232,263.
Complements and Alternatives to RCTs in evaluation in development

Randomised control trials (RCTs) have attracted increasing attention in evaluation of public policy. They have become some sort of gold standard to determine “what works” in international development. However, in some cases, the key feature of RCTs – the random allocation of treatment(s) – may be unethical, politically infeasible, or simply impossible. This paper discusses the main barriers to answer causal questions of key interest in policy evaluation. It then reviews approaches complement to RCTs which can be used to answer evaluation questions in conjunction with RCTs and alternatives useful whenever RCTs are not applicable. The paper discusses issues in drawing causal inference from these alternative approaches and provides some examples from specific sectors where standard RCTs are less likely to be applicable.
Dissimilarity of commodity prices – the results of time series clustering

Abstract. The behaviour of commodity prices is difficult to describe due to several reasons. Firstly, there is a large number of different categories of commodities. Secondly, some categories overlap with other categories, while others indirectly compete in the market. Thirdly, although essentially commodity prices react to changes in economic conditions or exchange rates, to a large extent these prices depend on supply disturbances. The objective of the article is to conduct the classification of the series of commodity prices in the pre-crisis and after-crisis periods and to asses whether the resulting clusters are similar in composition to the commodity indices. The analysis is based on monthly data from the period 1990-01 to 2014-02. All prices and price indices are published by the World Bank. The results obtained in dynamic time warping clustering reveal that commodity price co-movement is more evident in the pre-crisis period. There are only several paths which determine commodity prices.
The First Geodetic VLBI Field Test of LIFT: A 550-km-long Optical Fiber Link for Remote Antenna Synchronization

We present the first field test of the implementation of a coherent optical fiber link for remote antenna synchronization realized in Italy between the Italian Metrological Institute (INRIM) and the Medicina radio observatory of the National Institute for Astrophysics (INAF). The Medicina VLBI antenna participated in the EUR137 experiment carried out in September 2015 using, as reference systems, both the local H-maser and a remote H-maser hosted at the INRIM labs in Turin, separated by about 550 km. In order to assess the quality of the remote clock, the observed radio sources were split into two sets, using either the local or the remote H-maser. A system to switch automatically between the two references was integrated into the antenna field system. The observations were correlated in Bonn and preliminary results are encouraging since fringes were detected with both time references along the full 24 hours of the session. The experimental set-up, the results, and the perspectives for future radio astronomical and geodetic experiments are presented.
Discovering the Learning Styles of Malaysian University Students

University students’ achievement is often associated with their learning style. Many studies support that learning styles can give a strong impact to the program of study undertaken by the students. For example, using a model-based Jung's theory of Psychological Type (JTPT), students from the thinker or sensing element will be more successful in engineering programs because this group will make decisions based on logic and rules. The objective of this paper is to examine the learning styles of engineering students at Universiti Kebangsaan Malaysia (UKM) and how it shaped their academic achievement. Data were collected from questionnaires for the index of learning style that have been developed by Felder-Solomon. The number of respondents is 31 first year students from the Department of Electrical, Electronics and Systems (EES), Faculty of Engineering and Built Environment (FEBE), Universiti Kebangsaan Malaysia (UKM). The result of the analysis shows that the students are strongly visual learners. In the other three categories, these students are well-balanced between the two-elements. As this a longitudal study, nevertheless, this finding is hoped to enable educators to design and develop more effective teaching strategies to facilitate a more conducive learning environment. Key-Wwords -: Learning style, students’ performance, learning style index
It Takes A Village to Raise Water Quality: The Effects of Residential Voluntary Taxation Mechanisms on Lake Water Quality in Orange County, Florida

Achieving environmental standards with efficient and cost-effective economic systems is a subject whose importance is increasing in conjunction with growing technological innovation and urbanization. This project contributes to the subject’s literature by empirically examining the effects of a voluntary taxation mechanism on the water quality of designated lakes in Orange County, Florida. One of two taxing district types is voluntarily formed by lakefront or near-lakefront property owners: a Municipal Service Taxing District (MSTU), wherein participants pay an ad valorem tax based on property values, or a Municipal Service Benefit Unit (MSBU), wherein participants pay an equal flat rate tax independent of property value. The taxing districts’ purpose is to allocate specific funds for water management and water quality improvement, so the fixed effects econometric analyses examine the efficacy of the mechanisms using publicly available water quality data on Trophic State Index (TSI) ratings, Secchi disk depth measurements, phosphorus levels, and nitrogen levels. The empirical results show that MSTU/MSBU taxing districts are moderately effective at reducing phosphorus and nitrogen levels and that MSTU designation is weakly superior to MSBU designation. Moreover, certain taxing district characteristics are shown to be important for mechanism effectiveness.
BEHAVIORAL MODELING AND SIMULATION OF SPIRAL INDUCTORS WITH ANSOFT SIMPLORER

A behavioral model of spiral inductor is developed in the present paper realized using the possibilities of the Ansoft Simplorer simulator. The basic possibilities and advantages of Ansoft Simplorer for behavioral modeling and simulation of electronic circuits are presented. An example is presented illustrating the modeling and simulation of spiral inductors. A comparison of the results with a corresponding PSpice model is given. The designed VHDLAMS spiral inductor model is simple, algorithmic and realized to be easily implemented as a module in mixed signal simulation of large analog-digital projects.
Adaptive User Experience Based on Detecting User

As humans, our abilities and performance while carrying out different tasks differ due to several factors, such as health conditions, mental processing capabilities, emotional feelings, task difficulty and the desire to achieve it. Additionally, understanding human feelings and states that may entail information about achieving certain tasks can be an intricate job. Subsequently, this paper aims to outline the main aspects of self-ware systems and adaptive Human-Computer Interaction styles. There is an opportunity to enable machines to be more perceptive devices that can recognise innate human factors, which could be used to assist and improve the human's performance and effectiveness. This paper shows use-case scenarios of intelligent and affect-aware systems as well as presenting a conceptual model for User Perplexity as an important aspect an adaptive system should be able to capture to instantiate appropriate adaptation to the user experience. We argue that there is a subtle difference between adaptive user interfaces and adaptive user experiences.
dlexDB - A lexical database for the psychological and linguistic research

The lexical database dlexDB supplies in form of an online database frequency-based norms of numerous process-related word properties for psychological and linguistic research. These values include well known variables such as printed frequency of word form and lemma as documented also in CELEX (Baayen, Piepenbrock und Gulikers, 1995). In addition, we compute new values like frequencies based on syllables, and morphemes as well as frequencies of character chains, and multiple word combinations. The statistics are based on the Kernkorpus des Digitalen Wrterbuchs der deutschen Sprache (DWDS) with over 100 million running words. We illustrate the validity of these norms with new results about fixation durations in sentence reading.
Performance Study of Various Adaptive Filter Algorithms for Noise Cancellation in Respiratory Signals

Removal of noises from respiratory signal is a classicl problem. In recent years, adaptive filtering has become one of the effective and popular approaches for the processing and analysis of the respiratory and other biomedical signals. Adaptive filters permit to detect time varying potentials and to track the dynamic variations of the signals. Besides, they modify their behavior according to the input signal. Therefore, they can detect shape variations in the ensemble and thus they can obtain a better signal estimation. This paper focuses on (i) Model Respiratory signal with second order Auto Regressive process. Then synthetic noises have been corrupted with respiratory signal and nullify these noises using various adaptive filter algorithms (ii) to remove motion artifacts and 50Hz Power line interference from sinusoidal 0.18Hz respiratory signal using various adaptive filter algorithms. At the end of this paper, a performance study has been done between these algorithms based on various step sizes. It has been found that there will be always tradeoff between step sizes and Mean square error.
Benefit-Cost Analysis for Earthquake Mitigation : Evaluating Measures for Apartment Houses in Turkey

In the wake of the 1999 earthquake destruction in Turkey, the urgent need has arisen to evaluate the benefits of loss mitigation measures that could be undertaken to strengthen the existing housing stock. A cost benefit analysis for the implementation of various seismic retrofitting measures is performed on a common and vulnerable type of apartment building located in Istanbul. The analysis was performed probabilistically, through the development of fragility curves of the structure in its different retrofitted configurations. By incorporating the probabilistic seismic hazard for the region, expected losses were obtained for arbitrary time-horizons. By including realistic cost estimates of the retrofitting schemes and costs of direct losses, one can estimate the benefit of the retrofitting measures in present day values. A sensitivity analysis was performed to determine the effects of varying cost parameters and also the assumed cost of human lives. The analysis implies that, even when considering only direct losses, all of the retrofitting measures considered are very desirable for all but the very shortest time-horizons. The sensitivity analyses conducted suggests that this conclusion is very robust for a wide range of estimates regarding costs of mitigation, discount rates and time-horizons even if no fatalities are associated with the collapse of the building. The methodology developed here can be extended to an entire region by incorporating additional structure types, soil types, retrofitting measures etc. It is hoped that this work can support some of the most urgent decisions and serve as a benchmark for more realistic and targeted cost-benefit analyses
Design and Development of Ensemble of Naïve Bayes Classifiers to predict Social and Communication Deficiency among Children

In the last two decades, there has been a tremendous rise in psychological problems in children. Early detection of psychological problems and proper treatment ensure quality life at a later stage. This study tries to assist mental health care professionals in early diagnosis of social and communication deficiency from the psychometric profiles of children collected by the psychologists. Ensemble of Naïve Bayes classifiers along with Fuzzy clustering of attributes has been applied for classifying the children with and without deficiency. The prediction of ensemble of classifiers was made using majority voting and weighted average techniques. The performance of the classifiers has been analysed with tenfold cross validation technique and measures like Sensitivity, Specificity, Kappa statistic value and the Balanced accuracy. The study reveals that the ensemble of Naïve Bayes classifiers using weighted average technique performed better than the ensemble of classifiers using majority voting technique.
Robust Malware Detection for Internet of (Battlefield) Things Devices Using Deep Eigenspace Learning

Internet of Things (IoT) in military settings generally consists of a diverse range of Internet-connected devices and nodes (e.g., medical devices and wearable combat uniforms). These IoT devices and nodes are a valuable target for cyber criminals, particularly state-sponsored or nation state actors. A common attack vector is the use of malware. In this paper, we present a deep learning based method to detect Internet Of Battlefield Things (IoBT) malware via the device’s Operational Code (OpCode) sequence. We transmute OpCodes into a vector space and apply a deep Eigenspace learning approach to classify malicious and benign applications. We also demonstrate the robustness of our proposed approach in malware detection and its sustainability against junk code insertion attacks. Lastly, we make available our malware sample on Github, which hopefully will benefit future research efforts (e.g., to facilitate evaluation of future malware detection approaches).
1 Predictive Coding for Dynamic Visual Processing : Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model Author 1 , 2 1

The current paper proposes a novel predictive coding type neural network model, the predictive multiple spatio-temporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN learns to predict visually perceived human whole-body cyclic movement patterns by exploiting multiscale spatio-temporal constraints imposed on network dynamics by using differently sized receptive fields as well as different time constant values for each layer. After learning, the network becomes able to proactively imitate target movement patterns by inferring or recognizing corresponding intentions by means of the regression of prediction error. Results show that the network can develop a functional hierarchy by developing a different type of dynamic structure at each layer. The paper examines how model performance during pattern generation as well as predictive imitation varies depending on the stage of learning. The number of limit cycle attractors corresponding to target movement patterns increases as learning proceeds. And, transient dynamics developing early in the learning process successfully perform pattern generation and predictive imitation tasks. The paper concludes that exploitation of transient dynamics facilitates successful task performance during early learning periods.
Consequence of chromium-tainted soil on physical and biochemical responses of Vigna radiata L.

Mung bean (Vigna radiata L.) is one of the important leguminous plants of India, with shorter growing season. In this work the intention was to correlate the effects of Chromium on physical and biochemical responses of Vigna radiata L. Mung bean seeds were germinated and grown under controlled treatment, with different concentrations of waste soil mixed with garden soil. Physical parameters like shoot length, root length, fresh weight were found highest in control soil and 25% of contaminated soil whereas 50% and pure contaminated soil showed poor growth stage and poor quality physical parameters. Biochemical parameters like total chlorophyll content, protein content, and starch content were found highest in control soil and 25% contaminated soil but these parameters were found to be less in 50% and pure contaminated soil. It was observed that physical and chemical parameters were declining with increasing chromium contamination.
Evaluation of Gardner timing recovery in a land mobile satellite channel

The performance of the Gardner timing recovery scheme is evaluated in a Markov-based land mobile satellite channel model. Various different scenarios of the channel model are used to evaluate the timing recovery scheme. The performance of the scheme in the land mobile satellite (LMS) channel is compared to the performance of the scheme in a Gaussian channel. The results from this evaluation can be used to determine if the Gardner timing recovery scheme is suitable for LMS communication system. The results can be used to make a decision regarding coding schemes to be employed with this timing recovery scheme.
Assessment of the Genetic Variability and Fibre Composition of Gamma Ray induced Mutant Lines of Ginger ( Zingiber officinale Roscoe )

This study looked at mutagenic effectiveness of gamma rays d on two varieties of Zingiber officinale Roscoe: Bentong and Tanjung Sepat. The rhizomes were exposed to different doses (0, 5, 7, 9, 11, 13 and 15 Gy) using Caesium-137 as source of the gamma rays. The effect of different gamma doses on the crude fibre composition of irradiated ginger was studied and genetic variability was assessed using molecular marker technique, RAPD. Findings showed different doses of gamma rays could induce variability in these two ginger varieties and the effect was found to be variety-dependent. Bentong variety irradiated with 9 Gy recorded 8.53% of crude fibre composition while Tanjung Sepat irradiated ginger with 5 Gy recorded 8.70% of crude fibre which gave the lowest composition compared with other irradiated ginger. A total of nine different arbitrary decamers were used as primers to amplify DNA from mutant plant material to assess their polymorphism level of ginger mutant lines. Polymorphism of all mutant lines was 97.62% indicating that there were significant changes in genetic sequences in irradiated ginger genotypes.
Folktale similarity based on ontological abstraction

This paper presents a method to compute similarity of folktales based on conceptual overlap at various levels of abstraction as defined in Dutch WordNet. The method is applied on a corpus of Dutch folktales and evaluated using a comparison to traditional folktale similarity analysis based on the Aarne–Thompson–Uther (ATU) classification system. Document similarity computed by the presented method is in agreement with traditional analysis for a certain amount of folktale pairs, but differs for other pairs. However, it can be argued that the current approach computes an alternative, data-driven type of similarity. Using WordNet instead of a domain-specific ontology or classification system ensures applicability of the method outside of the folktale domain.
Automatic tracking and control for web recommendation New approaches for web recommendation

Recommender systems provide users with pertinent resources according to their context and their profiles, by applying statistical and knowledge discovery techniques. This paper describes a new approach of generating suitable recommendations based on the active user's navigation stream, by considering long distance resources in the history. Our main idea to solve this problem is the following: we consider that users browsing web pages or web contents can be seen as objects moving along trajectories in the web space. Having this assumption, we derive the appropriate description of the so-called recommender space to propose a mathematical model describing the behavior of the users/targets in the web/along the trajectories inside the recommender space. The second main assumption can then be expressed as follow: if we are able to track the users/targets along their trajectories, we are able to predict the future positions in the sub-spaces of the recommender space i.e., we are able to derive a new method for web recommendation and behavior monitoring. To achieve these objectives, we use the theory of the dynamic state estimation and more specifically the theory of Kalman filtering. We establish the appropriate model of the target tracker and we derive the iterative formulation of the filter. Then, we propose a new recommender system formulated as a control loop. We validate our approach on data extracted from online video consumption and we derive a users monitoring approach. Conclusions and perspectives are derived from the analysis of the obtained results and focus on the formulation of a topology of the recommender space.