Miracle-dz/UniFAR-FTUs huggingface dataset:
Regret Minimization for Reinforcement Learning with Vectorial Feedback and Complex Objectives

We consider an agent who is involved in an online Markov decision process, and receives a vector of outcomes every round. The agent aims to simultaneously optimize multiple objectives associated with the multi-dimensional outcomes. Due to state transitions, it is challenging to balance the vectorial outcomes for achieving near-optimality. In particular, contrary to the single objective case, stationary policies are generally sub-optimal. We propose a no-regret algorithm based on the Frank-Wolfe algorithm (Frank and Wolfe 1956), UCRL2 (Jaksch et al. 2010), as well as a crucial and novel gradient threshold procedure. The procedure involves carefully delaying gradient updates, and returns a non-stationary policy that diversifies the outcomes for optimizing the objectives.
Traffic Signs Recognition and Distance Estimation using a Monocular Camera

Traffic signs are integral component of road transport infrastructure. They deliver essential driving information to road users, which in turn require them to adapt their driving behavior to road regulations. In this study, the deep learning model is implemented with You Only Look Once (YOLO) based on active learning approach in order to minimize the size of the labeled dataset and provide higher accuracy. This is an efficient approach using a single monocular camera to perform real-time traffic signs recognition and distance estimation between traffic sign and camera pose. YOLO is one of the faster object detection algorithms, and it is a very good choice when real-time detection is needed, without loss of too much accuracy. The active learning algorithm will bridge the gap between labeled and unlabeled data, thus, only queries the samples that would lead to increase the accuracy. The aim of this work is to alarm and notify the drivers without having them to switch their focus. The results of the performed experiments show that about 97% recognition accuracies could be achieved with realtime capability in different real-world scenarios.
Chapter 2 Electroencephalogram

The electroencephalogram (EEG) is a widely used non-invasive method for monitoring the brain. It is based upon placing metal electrodes on the scalp which measure the small electrical potentials that arise outside of the head due to neuronal action within the brain. Its key benefits compared to other brain imaging techniques are that it has a very high time resolution – able to track events within the brain with millisecond accuracy – and that it is in principle portable allowing real-world neuroimaging to be performed outside of clinical and lab environments. As a result it is a very widely used sensing modality for a range of health and wellbeing applications ranging from epilepsy diagnosis to emotional monitoring. This chapter will overview the EEG: its set up, analysis and use. Section 2.2 discusses the principle of the EEG and how it is recorded and analysed, giving a practical getting started guide. Section 2.3 gives the technical details behind this set up, with significant attention given to overviewing the state of the art in the type of recorder and electrodes used. Section 2.4 then covers the typical applications where EEG is used today and discusses some of those which may become more common in the future as EEG systems become even smaller, easier to use and more robust to
The Lu-Hf systematics of meteorites: Consistent or not?

The discrepancy between the λLu value determined from terrestrial minerals (1.867 ± 0.011 ×10yr; [1-3]) and those derived from meteorite WR isochrons (1.93-1.98 ×10yr; [2,4-8]) remains unsolved. Meteorites that violate isochron assumptions are not ideally suited for λLu measurements [9]. Nevertheless, some internal (mineral) isochrons may yield valuable insights about the early solar system. Amelin [9] compared the Lu-Hf and U-Pb systematics of phosphates in the primitive achondrite Acapulco and the ordinary chondrite Richardton (H5), resulting in a λLu that is consistent with terrestrial mineral data, but yielding imprecise initial Hf/Hf values (i). Constraining the Richardton intercept further using the WR of [8] yields i = 0.279849 ±32, which is higher than expected for basaltic eucriteand chondrite WR isochrons (i ≈ 0.27964 ±4, wtd. mean of [5-7] & this work]), but would make sense if a positive correlation between Hf/Hf and Lu/Hf already existed in the earliest solar system materials. Photoexcitation by gamma irradiation could have temporarily increased the effective decay rate of Lu [10], creating anomalously steep Lu-Hf isochron slopes and high apparent λLu values for meteorites. Albarède et al. [10] argued that internal gamma sources such as Al→Mg and Fe→Co→Ni were not abundant enough to do this. For an external gamma source, such as the young Sun or a gamma ray burst from a supernova, significant photoexcitation would have been restricted to objects less than a few cm in radius, i.e., before the material coalesced into planetary bodies [10]. Igneous rocks crystallized in planetary interiors would not be expected to show anomalously high λLu. However, internal isochrons of the eucrite Juvinas (present study, [6 & 7], i = 0.27969 ±4, λLuapparent = 1.93 ±0.02 ×10yr), and the angrite SAH99555 ([11], i = 0.279682 ±30, λLuapparent = 1.99 ±0.02 ×10yr) show exactly that, suggesting that perhaps an internal source of gamma radiation did indeed exist [11] or that there is a different reason for the apparent Hf excesses.
Study on pharmacokinetics of epinastine hydrochloride tablets in Chinese Han and Tibetan healthy volunteers

Objective: To investigate the pharmacokinetics of epinastine hydrochloride tablets after a single oral dose in Chinese Han and Tibetan healthy volunteers.Methods: Ten Han and ten Tibetan healthy volunteers were givien a single dose of 20 mg epinastine hydrochloride tablets orally.The plasma concentrations of epinastine were determined by HPLC method.The pharmacokinetic parameters were calculated by DAS 2.1 software and the statistical analysis of pharmacokinetic parameters of volunteers with different ethnics and genders were performed with SPSS 10.0 software.Results: The main pharmacokinetic parameters of Han and Tibetan volunteers were as follows: cmax(53.21±14.23) and(51.39±17.11) ng/ml,t max(1.88±0.36) and(1.98±0.32) h,t1/2(9.32±1.53) and(9.36±1.32) h,AUC0-60(684.62±203.43) and(702.13±157.22) ng·h·ml-1,AUC0-∞(789.53±212.31) and(828.32±244.63) ng·h·ml.Conclusion: The plasma concentration-time curve of epinastine is fitted to a two-compartment open model and there is no significant difference in the pharmacokinetic parameters of epinastine between Chinese Han and Tibetan volunteers.
Switching-based stabilization of aperiodic sampled-data Boolean control networks with all subsystems unstable

We aim to further study the global stability of Boolean control networks (BCNs) under aperiodic sampled-data control (ASDC). According to our previous work, it is known that a BCN under ASDC can be transformed into a switched Boolean network (SBN), and further global stability of the BCN under ASDC can be obtained by studying the global stability of the transformed SBN. Unfortunately, since the major idea of our previous work is to use stable subsystems to offset the state divergence caused by unstable subsystems, the SBN considered has at least one stable subsystem. The central thought in this paper is that switching behavior also has good stabilization; i.e., the SBN can also be stable with appropriate switching laws designed, even if all subsystems are unstable. This is completely different from that in our previous work. Specifically, for this case, the dwell time (DT) should be limited within a pair of upper and lower bounds. By means of the discretized Lyapunov function and DT, a sufficient condition for global stability is obtained. Finally, the above results are demonstrated by a biological example.
Regional granulite-facies metamorphism in the northeastern Kisseynew Domain, Manitoba (parts of NTS 63O)

Observed metamorphic assemblages in the Wuskwatim Lake corridor of the northeastern Kisseynew Domain indicate upper-amphiboliteand granulitefacies conditions in Burntwood migmatite, as well as in a structurally underlying basement-cover sequence thought to be correlative with the Superior Province and Ospwagan Group in the Thompson Nickel Belt. The high-temperature metamorphism occurred at about 775°C, 6.8 kbar and 1806 to 1797 Ma.
Long telomeres in Peripheral Blood Leukocytes are associated with an increased risk of neuroblastoma

Telomere dysfunction is an important feature of tumorigenesis. Prior epidemiological studies have associated shorter telomere length in peripheral blood leukocytes with the development of many pediatric malignancies. However, the association between telomere length and the risk of neuroblastoma remains unclear. In this matched case-control study, we determine the relative telomere length (RTL) in the peripheral blood leukocytes from 20 neuroblastoma cases and 40 apparently healthy controls, and evaluated the association between RTL and neuroblastoma risk.By using median RTL in the healthy controls as a cutoff, children who had longer telomeres were at an increased risk of developing a solid tumor (odds ratio [OR] 9.45; P = 0.0037). When participants were categorized according to quartile RTL values of controls, a significant dose-response relation was observed (χ28.64; P < 0.01) between longer RTL and increased risk of neuroblastoma.Our pilot study provides evidence that RTL in peripheral blood leukocytes could potentially be used as a biomarker for neuroblastoma risk.
Happiness Raised by Raising Awareness: Effect of Happiness Using the Happiness Indicator

The Happiness Indicator (www.happinessindicator.nl) is an online tool designed to make people more aware of their own happiness. Participants periodically record how happy they feel on the present day and how happy they have felt over the past month, using the Happiness Comparer. They also have the option of indicating in the Happiness Diary how happy they felt during the various activities of the previous day. Participants receive feedback in the form of a comparison with their earlier scores and with the average scores of similar participants. The theory behind the website is that a keener awareness of one’s own happiness helps users find an optimal lifestyle and consequently promotes happiness among participants. The website has been online since January 2011; 5,411 participants have participated at least twice, and 64% of them used the Happiness Diary one or more times. These numbers are now high enough to permit an initial analysis of the effect of the use of the Happiness Indicator on the participants’ happiness. We find that the use of the Happiness Comparer only marginally increases happiness. The effect of using the Happiness Diary turns out to be stronger. Using the Happiness Diary 10 times results in an average increase in happiness of 2%. This 2% increase in happiness can be compared to the effects of an increase of € 600 in annual income. In addition, we find that repeated use of the Happiness Diary had a particularly strong effect for those who felt less happy when they first used the Happiness Indicator. 1 Erasmus University Rotterdam, Faculty of Social Sciences, Department of Psychology and Erasmus Happiness Economics Research Organization (EHERO) 2 Erasmus University Rotterdam, Erasmus School of Economics, Department of Applied Economics and Erasmus Happiness Economics Research Organization (EHERO) 3 VGZ insurance company, Arnhem, The Netherlands, Department of Innovation 4 Technical University Eindhoven, The Netherlands, Faculteit Industrial Engineering & Innovation Sciences, Department Industrial Engineering: 5 Erasmus University Rotterdam, Netherlands, Faculty of Social Sciences, Department of Sociology and Erasmus Happiness Economics Research Organization (EHERO). Corresponding author: veenhoven@ese.eur. nl
Android App to provide Context and Mood Based Music Recommendation System Using Sentiment Analysis

The rapid growth of digital music formats and availability of online music sources makes the music listeners painful in managing and searching their favorite music. Though the existing music recommendation system helps to resolve these problems, it lacks in fetching the relevant songs based on the current moods of music listeners. This paper implements a smart music recommendation system for the users to get songs as per their current mood. Naïve Bayes classification and Sentiment Analysis is used to extract the Sentiment involved in the song lyrics which are the actual human feel attached to each song. This system analysis the current mood of the user with the help of a small questionnaire in order to provide a list of recommended music which is based on the emotional feel of the user. The current music recommendation systems uses usage patterns, demographic and location based charts along with a standard music recommendation based on similar user patterns and desires. This model uses information from their usage pattern and other sources like Facebook to provide contextually correct music through crowd sourcing mechanism. Moreover, this music recommendation system is multilingual which creates a solitary user-oriented music recommendation for regional language using real time user data to perform emotion analysis to suggest an apt list of songs for the current mood.
Semantic Patterns Extraction of Code Smells: Retrieving the Solutions of Bugs

The understanding of code smells have exerted profound influence in the quality and the performance of programming codes. There are various type of code smells require various solutions. In order to interpret the solutions available in code smells, this research uses NLP (natural language programming) techniques to comprehend contents of messages from Technical Debt Dataset. Based on phrase structure rules, semantic patterns were extracted from the Dataset to build connection between trigger words and dependency tree. Verb Phrases are considered as the actions taken by programmers encountering code smells.
Impact of Socio-Economic Profile on Nutritional Status of Adult Tharu Population in Bahraich District of Uttar Pradesh , India

Background: Tribes constitute a considerable proportion of the indian population. Most of them are underpriviliged. Objectives: The principal aim of this study was to assess the impact of socio economic condition on nutitional status of adult tharu population in Bahraich district of Uttar Pradesh. Method : A total of 356 adult (aged >18 years) tharus of four villages of Bahraich district, Uttar Pradesh, India were studied. Height,weight has been taken as anthropometric measurements and BMI was calculated to ascertain nutritional status. To classify the socioeconomic status of the respondents,Uday Pareek and Trivedi scale has been adopted with subject to preliminary test and slight modification as per the need of the study. Result: Co-relation between socio economic and nutritional status was found to be positive , therefore it can be concluded as the socio economic status increases, simultaneous increases was observed in the nutritional status also. Conclusions: The level of undernutrition among adult tharu was high. It is suggested that some immediate nutritional intervention programme are needed for implementing among Tharu community of Bahraich district of Uttar Pradesh.
Evaluation of Students’ Satisfaction on Learning Calculus using Fuzzy Conjoint Model

Learning Calculus is one of the challenges that must be faced by engineering students in a university. In this study, students’ satisfaction of using PowerPoint in learning Calculus was evaluated. There are several ways in analyzing effectiveness in learning Calculus. So far, not much attention has been given to analyzing evaluation of students’ satisfaction from the fuzzy theory perspective. This paper employed the Fuzzy Conjoint Model to evaluate student’s satisfaction in learning the topic ‘integration’ using PowerPoint application. The fuzzy conjoint model presents the linguistic terms in five-point Likert scale. In this model, three main attributes of learning were evaluated: anxiety, learning enjoyment and mobility. The sample of the study consisted of undergraduate students randomly selected from computer science and applied sciences program in the Universiti Teknologi MARA (UiTM) Pahang, Malaysia. The results of the study support the use of fuzzy conjoint model in the evaluation of student’s satisfaction in learning Calculus.
Empirically Evaluating Co-Training

Co-training is a classification scheme needing only a small set of training instances for correct classification. The main question assessed in this thesis was how co-training performance varies with varying representativeness of the training data. 1280 co-training runs have been made, to test the generalization accuracy of co-training classification when using different selections of the training data. The results indicate that the availability of training data that are typical for their class or a distribution in the training data matching the a priori distribution of the corpus as a whole is a good condition for the generalization accuracy of co-training.
Determination of the experiment size for the optimum reasoning on success probability in binominal distribution for experiments in agricultural engineering

In the study the method of determination of the experiment size is provided so that the optimum reasoning could be applied on the basis of experiment results. The parameter estimation is examined here at the set absolute or relative error as well as hypothesis testing at pre-set (high) power. The considerations contained in the paper refer to success probability in binominal distribution. Such a distribution frequently occurs in the research in agricultural engineering.
RGCL at IDAT: Deep Learning models for Irony Detection in Arabic Language

This article describes the system submitted by the RGCL team to the IDAT 2019 Shared Task: Irony Detection in Arabic Tweets. The system detects irony in Arabic tweets using deep learning. The paper evaluates the performance of several deep learning models, as well as how text cleaning and text pre-processing inﬂuence the accuracy of the system. Several runs were submitted. The highest F1 score achieved for one of the submissions was 0.818 making the team RGCL rank 4th out of 10 teams in ﬁnal results. Overall, we present a system that uses minimal pre-processing but capable of achieving competitive results.
Review of Security Methods in Cloud Computing

In modern computing, Cloud computing is an important part of any small or large organization. Today cloud computing can be considered as a service, similar to the way that electricity is considered a service in urban areas. A cloud user can utilize different computing resources (e.g. network, storage, software application), whenever required, without being concerned with the complex underlying technology and infrastructure architecture. The most important feature is that the computing resources are available whenever they are needed. Additionally, users pay only for the resource they actually use. As a result, cloud users can easily scale their information technology infrastructure, based on their business policy and requirements. However, there is often a lack of security when realizing such cloud-based solutions. In the longer term, the problems caused by this lack of security might inhibit companies from taking advantage of cloud-based solutions. This paper provides literature review on various methods for implementing security in cloud environment.
A MULTI-SCALE/MULTI-PHYSICS MODELING FRAMEWORK FOR SOLIDIFICATION SYSTEMS

Models of solidification need to account for multiple physical processes that occur at multiple length scales. A general solidification modelling framework is outlined which can be used to systematically handle the multiscale/multi-physics nature of a given process. This framework is illustrated by considering specific models, a model of a alloy casting, and a model of dendrite growth in an under cooled melt. The paper concludes by quantifying the computer requirements for an integrated solidification model that would span across the length scales of interest.
OTHER-REGARDING PREFERENCES FOR REDISTRIBUTION

What determines support among individuals for redistributive policies? Do individuals care about others when they assess the consequences of redistribution? This paper proposes a model of other-regarding preferences for redistribution, which we term “income-dependent altruism. ” Our model predicts that an individual’s preferred level of redistribution is decreasing in income, increasing in inequality, and, more importantly, that the inequality effect is increasing in income. Thus, even though the rich prefer less redistribution than the poor, the rich are more responsive, in a positive way, to changes in inequality than are the poor. We contrast these results with several other prominent alternatives of other-regarding behavior. Using data for the US from 1978 to 2010, we find significant support for our claims.
Design and applications to Euler-Lagrange systems

Estimation of unknown inputs and/or disturbances has been a topic of constant interest in the control engineering for the past several decades. The reader is referred to [1] for a 2 detailed survey on the development of unknown input observers. Disturbance observers (DOB) are a special class of unknown input observers that were introduced for robust motion control 4 applications in the early 1980s [2]. Since their introduction in the literature, DOBs have been employed efficaciously in numerous robust control and fault detection applications ranging from 6 process control [3], [4] to mechatronics [5], [6], [7], [8], [9]. Figure 1 depicts a DOB that is employed in a typical control system. As can be seen in the figure, the DOB is used to reconstruct 8 unknown disturbances that are acting on the plant from the measured output variables and the known control inputs applied to the system. The output of the DOB, namely, the estimated 10 disturbance, can then be used in feedforward compensation of disturbances or faults. Disturbance observers possess several promising features in control applications [10]. 12 The most important feature is the add-on or “patch” feature. The disturbance feedforward compensation can be employed as an add-on to a previously designed feedback control. Indeed, 14 there is no need to change the existing control laws, which might have been extensively used and established in their respective literatures, such as PID feedback control used in industrial systems, 16 model predictive control used in process systems, and gain scheduling feedback control used in flight control. In order to improve the disturbance rejection and robustness abilities, DOB-based 18 compensation can be augmented with the baseline feedback control designed using conventional techniques. This feature has made using DOBs an appealing approach for rejecting disturbances 20 in commercial control applications. See [11] for a discussion on commercialization aspects of DOBs. 22