Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive-COSMO: Consensus Self-Organized Models for Fault Detection with Expert Feedback

Diagnosing deviations and predicting faults is an important task, especially given recent advances related to Internet of Things. However, the majority of the efforts for diagnostics are still carried out by human experts in a time-consuming and expensive manner. One promising approach towards self-monitoring systems is based on the "wisdom of the crowd" idea, where malfunctioning equipments are detected by understanding the similarities and differences in the operation of several alike systems. A fully autonomous fault detection, however, is not possible, since not all deviations or anomalies correspond to faulty behaviors; many can be explained by atypical usage or varying external conditions. In this work, we propose a method which gradually incorporates expert-provided feedback for more accurate self-monitoring. Our idea is to support model adaptation while allowing human feedback to persist over changes in data distribution, such as concept drift.
The Six Relative Advantages in Multichannel Retail for Three-Dimensional Virtual Worlds and Two-Dimensional Websites

Multichannel retail is now prevalent with retailers and consumers utilizing a number of channels in parallel or in some instances in an interconnected way. There is a degree of understanding on what each channel can offer but the Relative Advantage of each channel in relation to the others is less understood. This research evaluates the Relative Advantage between the three channels of three-dimensional Virtual Worlds, two-dimensional websites and offline retail stores. The consumer's preferences across the three channels were distinguished across six Relative Advantages. The three channels were then compared across the six Relative Advantages identified. Participants showed a preference for offline and 2D in most situations apart from enjoyment, entertainment, sociable shopping, the ability to reinvent yourself, convenience and institutional trust where the Virtual Worlds were preferred.
Take One For the Team: The Effects of Error Severity in Collaborative Tasks with Social Robots

We explore the effects of robot failure severity (no failure vs. low-impact vs. high-impact) on people's subjective ratings of the robot. We designed an escape room scenario in which one participant teams up with a remotely-controlled Pepper robot. We manipulated the robot's performance at the end of the game: the robot would either correctly follow the participant's instructions (control condition), the robot would fail but people could still complete the task of escaping the room (low-impact condition), or the robot's failure would cause the game to be lost (high-impact condition). Results showed no difference across conditions for people's ratings of the robot in terms of warmth, competence, and discomfort. However, people in the low-impact condition had significantly less faith in the robot's robustness in future escape room scenarios. Open-ended questions revealed interesting trends that are worth pursuing in the future: people may view task performance as a team effort and may blame their team or themselves more for the robot failure in case of a high-impact failure as compared to the low-impact failure.
TEXT: Traffic Entity eXtraction from Twitter

Traffic congestion is a significant problem for many developing countries. Among a variety of methods proposed to address this problem, extraction of road traffic conditions from microblogging platforms for dissemination to road users has gained popularity. Coupled with the use of Internet of Things (IoT) devices, up-to-date traffic condition reports from road users and road traffic authorities, can be effectively reconciled and communicated to the intended audience. However, the noisy and unstructured nature of Twitter texts causes a decline in the performance of conventional Named Entity Recognition (NER) techniques. NER techniques have traditionally been used to extract location information. In order to extract the corresponding traffic state information for each location, contextual information become important which are not implemented in conventional NER approaches. In this paper, a rule-based NER technique, which considers contextual clues, is proposed for the extraction of location and traffic state entities. The proposed approach has achieved significant improvement to the F1 score, 88.96 and 81.32, for location entity extraction from formal and informal sources, respectively.
Gene expression models for prediction of dam breach parameters

Data from a large database of 140 dam failure cases are used with gene expression programming (GEP) to develop new empirical formulae of physical meaning for prediction of non-dimensional key dam breach parameters. The GEP models are trained on 75% of the data set and validated on the remaining 25%. Parametric and error analyses are conducted to confirm the robustness of the developed relations. Moreover, uncertainty analyses using the Monte Carlo technique is performed to check for the output uncertainty of key dam breach parameters and the contribution of various input parameters to the overall output uncertainty. It is found that uncertainties of 20 to 40% are calculated for the developed GEP models with reservoir shape factor and dam erodibility being main influential predictors.
Modelling Therapeutic Alliance using a User-aware Explainable Embodied Conversational Agent to Promote Treatment Adherence

Non-adherence to a treatment plan recommended by the therapist is a key cause of the increasing rate of chronic medical conditions globally. The therapist-patient therapeutic alliance is regarded as a successful intervention and a good predictor of treatment adherence. Similar to the human scenario, embodied conversational agents (ECAs) showed evidence of their ability to build an agent-patient therapeutic alliance, which motivates the effort to advance ECAs as a potential solution to improve treatment adherence and consequently the health outcome. Building therapeutic alliance implies the need for a positive environment where the ECA and the patient can share their knowledge and discuss their goals, preferences and tasks towards building a shared plan, which is commonly done using explanations. However, explainable agents commonly rely on their own knowledge and goals in providing explanations, rather than the beliefs, plans or goals of the user. It is not clear whether such explanations, in individual-specific contexts such as personal health assistance, are perceived by the user as relevant in decision-making towards their own behavior change. Therefore, in this research, we are developing a user-aware explainable ECA by embedding the cognitive agent architecture with a user model, explanation engine and modified planner to implement the concept of SharedPlans. The developed agent will be deployed and evaluated with real patients and the therapeutic alliance will be measured using standard measurements.
Towards an Adaptive Regulation Scaffolding through Role-based Strategies

Agents (virtual/physical) in a learning environment can be introduced in different roles, such as a tutor, mentor, motivator, expert, peer student etc. Each agent type brings an expertise, creating a unique social relationship with students. Depending on their role, agents have specific goals and beliefs, as well as attitudes towards the learners, thereby influencing different aspects of learning such as cognitive, affective and meta-cognitive processes in a learner. The proposed research will primarily investigate the meta-cognitive aspect of self-regulation in collaborative learning interactions and its variations with various scaffolding strategies based on agent roles. The learning interaction will be based on the socially shared regulation model of self regulation, which accommodates the social context of self regulated learning created by agents in multiples roles and behaviours. The objectives of this research will be to understand how various roles and behaviours of the agents would influence the self regulation skills of the learner and to design a role-based strategy selection model for regulation scaffolding, based on the behavioural, motivational and cognitive measures of the learning interaction.
Intrusion detection using dimensionality reduced soft matrix

The task of identifying attacks in the real time networks has become a recent point of focus in network security. A classifier performance depends on the input data. Preprocessing dataset fed as input for classifier is usually required to make the dataset suitable for efficient processing. Preprocessing is first stage of transforming data for better data representation. Dimensionality reduction is usually applied on datasets to reduce the space and time complexities and to facilitate easy handling of large datasets. This paper gives an approach for performing dimensionality reduction of input dataset. The resulting one is the soft matrix. This dimensional reduced input dataset is fed as input to classifier. The paper restricts to outlining the algorithm of proposed approach.
Active Learning for Streaming Data in A Contextual Bandit Framework

Contextual bandit algorithms have been shown to be effective in solving sequential decision making problems under uncertainty. A common assumption in the literature is that the realized (ground truth) reward is observed by the learner at no cost, which, however, is not realistic in many practical scenarios. When observing the ground truth reward is costly, a key challenge is how to judiciously acquire the ground truth by assessing the benefits and costs in order to balance learning efficiency and learning cost. In this paper, we design a novel contextual bandit-based learning algorithm and endow it with the active learning capability. In addition to sending a query to an annotator for the ground truth, prior information about the ground truth learned by the learner is sent together, thereby reducing the query cost. We prove that the learning regret of the proposed algorithm achieves the same order as that of conventional contextual bandit algorithms in cost-free scenarios, implying that, surprisingly, cost due to acquiring the ground truth does not increase the learning regret in the long-run, where the prior information about the ground truth plays a critical role.
Evaluation of Retiled Salted Fish according to Egyptian Standard

This study was conducted to confirm the bacterial and chemical conditionsof salted fishwith E.O. S, and its hazards on public health. A total of 90 samples of fesiekh , sardine and melloha (30 of each) were collected from different retail markets for bacteriological and chemical examination.The average of APC, Staphylococci ,S.aureus counts (cfu/g) ,pH ,sodium choride and histamine contents were 7.81x106 ± 1.62 x 106, 1.28x105±0.19x105 ,4.58x104±0.24x104, 6.39± 0.01+, 5.45± 0.13 and 18.06 ± 0.99+in fesiekh, respectively, 9.95 x 105± 2.08 x 105, 5.43x104±1.10x104 ,1.03x104± 0.17x104 ,6.24± 0.02,5.96±0.17 and 23.51±1.21 in sardine, respectively and 2.16x104 ± 0.31 x 104, 8.92x102±1.67x102 , 6.79x102±1.35x102 ,6.58± 0.01, 6.19± 0.22 and 14.79± 0.64 in melloha, respectively. The incidence of enterotoxins (A,B and C) produced by S. aureus were higher in fesiekh (13.33%) than sardine (10%) and melloha (3.33%). While , the incidence of isolated E.coli was higher in fesiekh(26.67%) than those isolated from sardine (16.67%) and melloha (10%). Also the incidence of V.parahaemolyticus in fesiekh(16.67%) was more that in sardine(6.67%) and melloha(6.67%).
nfluence of habitat structure and food on patch choice of aptive coyotes haron

Increasing urban development can have significant effects on wildlife species, including carnivores. Some carnivore species have been able to adapt to and even thrive in urban environments, including coyotes (Canis latrans). The presence of carnivores in urban areas can sometimes lead to conflicts with humans and their pets. Although coyotes may frequently use urban areas, they also inhabit natural areas surrounding urban development. Understanding the various factors affecting patch choice of urban coyotes may assist wildlife officials in managing human-coyote conflicts. Both sex and behavioral profile can influence patch choice; bold individuals are more likely to be exploratory than shy animals, which can result in increased conflicts in urban environments. Using a captive population of coyotes, we tested whether coyotes preferred urban (anthropogenic) habitat structure, natural structure, or a mixture of structures and whether sex, behavioral profile, biological season, or food manipulation affected coyote patch choice. Coyotes generally preferred the control, homogeneous structure representing their natal habitat (mean percentage of time 23.3% ± 19.3 SD; P = 0.037). The next most preferred habitat for coyotes, especially females (23.7 ± 16.6% for 25% urban pen; P = 0.020) and bold coyotes (27.8 ± 23.2% for 75% urban pen; P = 0.005), was a mixture of anthropogenic and natural structures rather than uniform structure (all natural or all anthropogenic), and this preference was more strongly expressed during the non-breeding season (25.6 ± 23.2% for 75% urban pen; P = 0.017). Food had no effect on patch choice (P = 0.983); coyotes appeared to be primarily motivated by the structure of the habitat rather than by the amount of food within each habitat. Our results suggested that urban areas containing large amounts of both natural and anthropogenic structures are more likely to be used by coyotes and, thus, could have the potential for human-coyote conflicts. © 2014 Elsevier B.V. All rights reserved.
Revealing the paradoxes of horsemeat – The challenges of marketing horsemeat in Finland

This study aims to analyse the different cultural meanings attached to horsemeat consumption in the context of the Finnish market. We take the “meat paradox” as a theoretical starting point and investigate the underlying cultural structures that guide consumers’ meaning-making and consumption decisions in regard to horsemeat. The data were generated after the horsemeat scandal, drawing on a wide variety of media texts about horsemeat consumption. The data were analysed through qualitative content analysis and the findings reveal five horsemeat paradoxes. Each paradox contains meanings that reflect both the justifications for and avoidance of eating horsemeat. The findings show how horsemeat consumption holds various and even contradictory meanings, elucidating how it may be difficult for consumers to take a stand towards eating horsemeat. Thereby, the study provides novel ideas for marketing that are grounded in our deep-rooted and ingrained cultural understandings.
Ecological Momentary Assessment based Differences between Android and iOS Users of the TrackYourHearing mHealth Crowdsensing Platform

mHealth technologies are increasingly utilized in various medical contexts. Mobile crowdsensing is such a technology, which is often used for data collection scenarios related to questions on chronic disorders. One prominent reason for the latter setting is based on the fact that powerful Ecological Momentary Assessments (EMA) can be performed. Notably, when mobile crowdsensing solutions are used to integrate EMA measurements, many new challenges arise. For example, the measurements must be provided in the same way on different mobile operating systems. However, the newly given possibilities can surpass the challenges. For example, if different mobile operating systems must be technically provided, one direction could be to investigate whether users of different mobile operating systems pose a different behaviour when performing EMA measurements. In a previous work, we investigated differences between iOS and Android users from the TrackYourTinnitus mHealth crowdsensing platform, which has the goal to reveal insights on the daily fluctuations of tinnitus patients. In this work, we investigated differences between iOS and Android users from the TrackYourHearing mHealth crowdsensing platform, which aims at insights on the daily fluctuations of patients with hearing loss. We analyzed 3767 EMA measurements based on a daily applied questionnaire of 84 patients. Statistical analyses have been conducted to see whether these 84 patients differ with respect to the used mobile operating system and their given answers to the EMA measurements. We present the obtained results and compare them to the previous mentioned study. Our insights show the differences in the two studies and that the overall results are worth being investigated in a more in-depth manner. Particularly, it must be investigated whether the used mobile operating system constitutes a confounder when gathering EMA-based data through a crowdsensing platform.
A Study of Taiwanese College Students ’ Responses to a Blog-based English Writing Project and its Effectiveness

This study intended to explore Taiwanese college students’ responses and their English writing performance after a blog-based English writing project. 65 non-English major college students participated in this study. The EG received blog-based writing exercises, while the CG took traditional writing training. All subjects were required to take a pretest and a post-test writing and answer a questionnaire of blog-based English writing project. The major findings included, first, the EG displayed significant difference from the CG in the post-test writing, particularly in content, organization, and average length of sentences; second, there is no significant difference between the subjects’ attitude toward the multi-level writing assessment on their post-test writing; third, the EG subjects held positive attitude toward the Blog-based English writing project for its convenient working platform for students to upload or modify their own assignments, to obtain the teacher’s corrective feedbacks, to observe peers’ model sample works or peers’ comments, and most importantly, to analyze the subject learning process and improvement . In light of the findings from the study, some pedagogical implications are suggested.
Effect of haemoglobin concentration on cardiovascular system by heart rate variability modulations

Introduction: Decreased Heart rate variability (HRV) is associated with increased cardiac risk in several conditions. Previous studies show decreased heart rate variability among subject with low haemoglobin concentration. However the underlying pathology of anaemia may be the direct cause of low HRV which may preclude from drawing the conclusion that anaemia per se cause decreased HRV. Aims: To study the relationship between HRV and haemoglobin concentration on cardiac autonomic modulation in HRV. Settings and Design: The study includes 50 apparently healthy paramedical students of age 18 to 25. They were divided into two groups I (Hb>12gm %) and II (Hb<12gm %). It was a case control study. Methods and Material: Haemoglobin estimation: Colorimetric method was used for estimation of Haemoglobin. HRV Analysis: RMS Polyrite D polygraph version 3.0. 11 was used for HRV recording and analysis. Statistical analysis used: Results were expressed as means + S.D. using an SPSS package version 10.0. Results: The mean haemoglobin concentration of group I (mean +SD= 14.03+1.69) was significantly higher compared with mean haemoglobin of group II M+SD=10.28+1.12). There is no statistically significant relation found between haemoglobin concentration and HRV in mild to moderate anaemia. (For all HRV parameters P value > .05). Key-words: Anaemia, Autonomic nervous system, Heart rate variability, Haemoglobin Introduction Anemia has major consequences on human health as well as on social and economic development; it is the world’s second leading cause of disability and is responsible for about 1million deaths a year, of which three quarters occur in Africa and South East Asia. India is among the countries with high prevalence of anemia. It is widely prevalent in all age groups. [1] Heart rate variability (HRV) is the cardiac beat to beat variation mainly occurring due to variations in cardiac activities, which vary under autonomic control. Decreased HRV has been recognized as a strong indicator of risk related to adverse events in healthy individuals as well as in diseased ones, reflecting the vital role of the autonomic nervous system in maintaining health. [2-7] HRV is analyzed under two domains: the time domain and the frequency domain. In the time domain method, mean heart rate (MHR), mean heart beat interval (MNN), the square root of variance of RR intervals (SDNN), and square root of the mean squared differences of successive RR intervals (RMSSD) are calculated. SDNN reflects all Indian Journal of Basic and Applied Medical Research; March 2016: Vol.-5, Issue2, P. 855-860
THE STATE OF THE WORLD’s BIODIVERSITY

The axes comprise 23 actions that are coordinated and implemented with a (INRA), the involved and the network of Chambers of Agriculture. The objective of the Agroforestry Development Plan is to develop existing agroforestry systems such as hedgerows (about 1 million ha in France, but decreasing), tree intercropping (about 5 000 ha), fruit-tree silvopasture and silvopastoralism.
English psych verbs in light of the ExoSkeletal Research Program

Psych verbs challenge the mapping rules (UTAH). There are two major lines of accommodating psych verbs in modern syntactic theory: syntactically motivated approaches and semantically motivated accounts of various sorts. These approaches view psych verbs as a separate semantic class with peculiar syntactic properties. This paper aims to show that psych verbs (i.e., verbs that describe mental states and emotions) do not represent idiosyncratic grammatical patterns and thus do not differ from other verbs. Rather, like other verbs they fall into two functional structures: receptive and causative. Subject Experiencer verbs such as love, hate fall into the receptive structure, whereas Object Experiencer verbs such as frighten and please fall into the causative one. The distinction between receptive and causative structures is not determined by lexical properties or nominal arguments but by derivational markers, including -en, -fy, -ate and -ize. To provide evidence for this claim, a synchronic study of the morphology of English psych verbs is conducted here, supported by the theoretical assumptions of Borer’s Exo-Skeletal Research Program (2003, 2005ab, 2013). Moreover, previous research on the classification of Old English psych verbs in regard to their grammatical relations and categories is also taken into account (Allen, 1995; Brody, 1989; Elmer, 1981; Fisher & van der Leek, 1983; Guidi 2011).
The Stability of Neighborhood Racial / Ethnic Diversity in the United States , 1980-20001

Over the past several decades, metropolitan areas in the United States have become increasingly racially and ethnically diverse (Denton and Massey 1991; Frey and Farley 1996; Iceland 2003), and recent research indicates that diversity within neighborhoods may also be increasing in several U.S. cities (Alba et al. 1995; Fasenfest, Booza, and Metzger 2004; Rawlings et. al. 2004). These trends have sparked renewed optimism for the prospect that residential integration among diverse racial/ethnic groups is possible (e.g., McKnight Foundation 2004). In particular, researchers and urban planners are interested in the possibility that increasing diversity will be accompanied by increasing racial/ethnic stability, since the benefits of diversity may best be realized when the racial/ethnic mix of a neighborhood remains consistent over time. Stable racial/ethnic diversity may signal increasingly tolerant racial attitudes (Farley et al. 1994; Schuman et al. 1997), reduce racial/ethnic inequalities produced by high levels of segregation (Galster 1988; Massey and Denton 1993), and attract residents to urban areas, thus revitalizing deteriorated inner cities (Florida 2002; Jacobs 1961).