Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-control conflict in the eating domain : A cognitive, affective, and behavioral perspective

Sometimes we are tempted to do one thing (e.g., order the burger) but know we should do another (e.g., choose a healthier alternative). Such self-control conflicts, moments in which an impulse and a higher order goal are in conflict, are pervasive in everyday life. They are at the heart of the self-control process, given that without such a conflict self-control would be unnecessary. In my thesis I investigated how people experience and deal with conflict, and whether this knowledge helps to improve control over eating behavior. In one line of research I investigated the interplay between cognitive control and motivational processes, and found that cognitive control is weakened when in direct competition with processing motivationally salient information. In the second line of research I studied how people feel about making conflicted self-control choices (i.e., giving in vs. resisting temptation). Interestingly, the more conflict people experienced during decision making the more negative they felt about their choices – even if they had made the ‘healthy’ choice. Only if people were reminded that their healthy choice was a successful act of self-control did conflict strength predict increased feelings of pride. Finally, I tested whether reducing impulse strength by means of the approach avoidance training could increase control over eating behavior. Three lab studies produced null results, suggesting that more research is needed before the approach avoidance training can be used in the applied setting. Together, those findings help understand why self-control often fails, and generate several interesting ideas for how to improve self-control.
DOA Estimation with Local-Peak-Weighted CSP

This paper proposes a novel weighting algorithm for Cross-power Spectrum Phase (CSP) analysis to improve the accuracy of direction of arrival (DOA) estimation for beamforming in a noisy environment. Our sound source is a human speaker and the noise is broadband noise in an automobile. The harmonic structures in the human speech spectrum can be used for weighting the CSP analysis, because harmonic bins must contain more speech power than the others and thus give us more reliable information. However, most conventional methods leveraging harmonic structures require pitch estimation with voiced-unvoiced classification, which is not sufficiently accurate in noisy environments. In our new approach, the observed power spectrum is directly converted into weights for the CSP analysis by retaining only the local peaks considered to be harmonic structures. Our experiment showed the proposed approach significantly reduced the errors in localization, and it showed further improvements when used with other weighting algorithms.
Towards improving the performance of Vector Space Model for Chinese Frequently Asked Question Answering

This paper presents a method which improves the performance of Vector Space Model (VSM) when applying it to Chinese Frequently Asked Questions (FAQ). This method combines unigram and bigram models in determining the similarity of document vectors. The performance is further improved by applying shallow lexical semantics and the document length information. Experiments showed that the proposed methods outperform baselines (segmentation and bigram) across different datasets which include FAQs from restricted domains and open domains.
Trust matters: a cross-cultural comparison of Northern Ghana and Oaxaca groups

A cross-cultural analysis of trust and cooperation networks in Northern Ghana (NGHA) and Oaxaca (OAX) was carried out by means of ego networks and interviews. These regions were chosen because both are inhabited by several ethnic groups, thus providing a good opportunity to test the cultural group selection hypothesis. Against the predictions of this approach, we found that in both regions cooperation is grounded in personal trust groups, and that social cohesion depends on these emotional bonds. Moreover, in agreement with Fiske's notion of “evolved proclivities,” we also found two distinct kinds of trust networks, one for each region, which vary in terms of the degree of ethnic interrelation. This pattern suggests that social cohesion increases when environmental resources are scarce.
An IEEE standard Ontology for Robotics and Automation

This article discusses a newly formed IEEE-RAS working group entitled Ontologies for Robotics and Automation (ORA). The goal of this working group is to develop a standard ontology and associated methodology for knowledge representation and reasoning in robotics and automation, together with the representation of concepts in an initial set of application domains. The standard provides a unified way of representing knowledge and provides a common set of terms and definitions, allowing for unambiguous knowledge transfer among any group of humans, robots, and other artificial systems. In addition to describing the goal and structure of the group, this article gives some examples of how the ontology, once developed, can be used by applications such as industrial kitting.
A fast fuzzy path tracking controller for mobile robots

In this paper, we proposed a simple but robust fuzzy logic path tracking controller for a mobile robot in a deterministic environment. Although some related works consider multiple dependent decision variables to determine the control inputs, we introduce two independent controllers with one input variable and one output variable which we named as control input. These two input variables are distance and angular difference and the two control inputs are linear and angular velocities. The comparison of the proposed method with the other previous works shows the higher speed, lower complexity and robustness in the presence of added observation noise.
Border bases of positive dimensional polynomial ideals

The border bases were generalized to general polynomial ideals (zero and positive dimensional ideals). A new algorithm to compute a border basis for a given polynomial system w.r. t. a specified term order was presented. This algorithm computes a border basis, as well as a reduced Gröbner basis for the polynomial system. A particular eigenvector method to find some components of positive dimensional polynomial systems was sketched too.
Private Entity Authentication for Pervasive Computing Environments

Entity authentication becomes ubiquitously necessary in pervasive computing environments. We provide taxonomy of entity authentication between keys and locks. Based on the discussion, we propose a novel authentication approach for pervasive computing environments. A person uses a single device, the Master Key, which aggregates all his digital keys for entity authentication. The Master Key initiates authentication and selects proper keys by exchanging code words with locks. With an emphasis on usability, the Master Key secures authentication, keeps authentication private, and supports various key-lock interactions. We analyze privacy and security properties, verify the protocols, and measured performance.
OPI: Semeval-2014 Task 3 System Description

In this paper, we describe the OPI system participating in the Semeval-2014 task 3 Cross-Level Semantic Similarity. Our approach is knowledge-poor, there is no exploitation of any structured knowledge resources as Wikipedia, WordNet or BabelNet. The method is also fully unsupervised, the training set is only used in order to tune the system. System measures the semantic similarity of texts using corpusbased measures of termsets similarity.
Analysis of variance, coefficient of determination and $F$-test for local polynomial regression

This paper provides ANOVA inference for nonparametric local polynomial regression (LPR) in analogy with ANOVA tools for the classical linear regression model. A surprisingly simple and exact local ANOVA decomposition is established, and a local R-squared quantity is defined to measure the proportion of local variation explained by fitting LPR. A global ANOVA decomposition is obtained by integrating local counterparts, and a global R-squared and a symmetric projection matrix are defined. We show that the proposed projection matrix is asymptotically idempotent and asymptotically orthogonal to its complement, naturally leading to an F-test for testing for no effect. A by-product result is that the asymptotic bias of the "projected" response based on local linear regression is of quartic order of the bandwidth. Numerical results illustrate the behaviors of the proposed R-squared and F-test. The ANOVA methodology is also extended to varying coefficient models.
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization

Motivated by various applications in machine learning, the problem of minimizing a convex smooth loss function with trace norm regularization has received much attention lately. Currently, a popular method for solving such problem is the proximal gradient method (PGM), which is known to have a sublinear rate of convergence. In this paper, we show that for a large class of loss functions, the convergence rate of the PGM is in fact linear. Our result is established without any strong convexity assumption on the loss function. A key ingredient in our proof is a new Lipschitzian error bound for the aforementioned trace norm-regularized problem, which may be of independent interest.
1 The Epistemic View of Games 1 . 1 Classical Game Theory

Foundational work in game theory aims at making explicit the assumptions that underlie the basic concepts of the discipline. Non-cooperative game theory is the study of individual, rational decision making in situations of strategic interaction. This entry presents the epistemic foundations of non-cooperative game theory (this area of research is called epistemic game theory). Epistemic game theory views rational decision making in games as something not essentially different from rational decision making under uncertainty. As in Decision Theory (Peterson, 2009), to choose rationally in a game is to select the “best” action in light of one’s beliefs or information. In a decision problem, the decision maker’s beliefs are about a passive state of nature, the state of which determines the consequences of her actions. In a game, the consequences of one’s decision depend on the choices of the other agents involved in the situation (and possibly the state of nature). Recognizing this—i.e., that one is interacting with other agents who try to choose the best course of action in the light of their own beliefs—brings higher-order information into the picture. The players’ beliefs are no longer about a passive or external environment. They concern the choices and the information of the other players. What one expects of one’s opponents depends on what one thinks the others expect from her, and what the others expect from a given player depends on what they think her expectations about them are. This entry provides an overview of the issues that arise when one takes this broadly decision-theoretic view on rational decision making in games. After some general comments about information in games, we present the formal tools developed in epistemic game theory and epistemic logic that have been used to understand the role of higher-order information in interactive decision making. We then show how these tools can be used to characterize known “solutions” of games in terms of rational decision making in specific informational contexts. Along the way, we highlight a number of philosophical issues that arise in this area.
The Transgressor's Response to Denied Forgiveness

The study of forgiveness has flourished in recent years, but little is known about how transgressors respond when their request for forgiveness is denied. Two studies examined how transgressors react to a denied request for forgiveness in romantic relationships. Across both studies, when participants were denied forgiveness or delayed in receiving a forgiving response, they exhibited differences in the degree to which they held unforgiving motivations (e.g., anger and avoidance) and experienced positive emotions (e.g., empathy). The observed effects remained even after controlling for relationship commitment in Study 2. These results expand our knowledge of forgiveness processes by describing in more detail the internal experience and motivations of the transgressor toward the victim when forgiveness is denied, which has implications for relational repair (e.g., transgressor's motivations toward re-engaging and repairing the relationship) after an offense has occurred in romantic relationships.
Is the Productivity-Based Explanation for the Time-Varying US NAIRU Valid？

This paper empirically examines whether the productivity-based explanation for the time-varying US NAIRU is valid. We apply a novel filter known as the 1d fused lasso. This procedure enables us to estimate the mean trend of the labor productivity as a step function, without specifying the location and number of breaks a priori. This paper reports that although there exists an impressive similarity between the US NAIRU and the US labor productivity, changes in the US labor productivities do not necessarily lead to changes in the US NAIRU.
A Theoretical and Methodological Approach to Examine Young Learners’ Cognitive Engagement in Science Learning

Children start learning science in formal school settings as early as kindergarten ages. Scientific literacy is an essential component in forming science curriculum for students’ knowledge and understanding of scientific concepts across grades and with different scientific disciplines. Students’ cognitive engagement is displayed through different levels of cognitive processes involved during their knowledge construction. Much of the research in students’ cognitive engagement of science learning focuses on older students and the use of self-report measures on their cognitive strategies. Research on young learners’ cognitive engagement in science learning is missing in current literature. Part of the reason may be young learners are just beginning to develop a repertoire of cognitive strategies as well as lacking sufficient linguistic competence to accurately articulate the cognitive strategies involved in their science learning. The chapter introduces a theoretical and methodological approach, quantitative content analysis, to fulfill the gap. The chapter manifests the approach through three perspectives: (a) methodological approaches being employed in current studies of cognitive engagement in science learning, (b) the need for a different methodological approach for young learners, and (c) how this particular approach can be adopted in future research on young learners’ cognitive engagement in science learning. A Theoretical and Methodological Approach to Examine Young Learners’ Cognitive Engagement in Science Learning
Hedging Against Uncertainty: A Tale of Internet Data Center Operations Under Smart Grid Environment

Internet Data Center (IDC) supports the reliable operations of many important online services. As the demand of Internet services and cloud computing keep increasing in recent years, the power usage associated with IDC operations had been surging significantly. Such mass power consumption has brought heavy burden on IDC operators. Recently there are extensive research on power management for IDCs. However, one important challenge faced by IDC operators has been overlooked. How to handle the uncertainties in IDC operations is a challenging task. The uncertainties come from both the dynamic workload and time-varying electricity prices. In this paper, we systematically investigate the problem of minimizing the operation risk of IDCs against those uncertainties at the same time guaranteeing quality of service under deregulated electricity market environment. We propose a novel hedging scheme and model the operation risk minimization problem as a bilevel programming. We also design an optimal hedging algorithm. We conduct extensive evaluations based on real-life workload data from Google and electricity price data from deregulated electricity market for multiple IDC locations. Results show that our scheme can significantly reduce the operation risk by countering the uncertainties.
Applying Computational Complexity Theory and Cryptography to the Pursuit of Concept Understanding : An Overview of Current Work

Our research is motivated by a simple but deep question: can computers work with high-level ideas to solve problems as well as they can push symbols and crunch numbers? By “high-level”, we mean a notion that is best illustrated with a common example. Compare almost every proof published in mathematics journals with a completely formal proof, having every detail down to the axioms; the first is what we call a ”high-level” proof, and the second is the current kind of proof that a theorem-proving computer system generates. For another example, compare the best chess programs with the best chess Grandmasters. The best chess programs perform a highly optimized search over all possible moves, assigning numerical values to board positions and looking for moves that lead to the highest values. In stark contrast, Grandmasters only consider 2-3 moves at a time. Grandmasters are only looking at the most relevant and interesting moves; they think in terms of general, high-level trends in the game. A “yes” answer to our question would suggest that perhaps computers can even achieve a kind of deep understanding in some areas of knowledge. A “yes” answer to our research question would suggest that perhaps computers can even achieve a true understanding of some areas of knowledge, similar to that of humans. All of us constantly work with “high-level ideas” . We don’t study the details of the road while driving, we merely keep track of general positions where other cars are, our approximate speed, etc. We intuitively understand what is important to our everyday tasks and what is not, but we lack a formal understanding of our own “understanding”. A general mathematical theory of understanding would guide us in this direction, and possibly lead to more intelligent software. Under current software design, “true understanding” does not appear to be possible, and some philosophers such as Searle [Sea80] argue that computers with true understanding are an impossibility. While we do not assert that our work will answer the above question on a philosophical level, we believe that our research will yield significant progress on both a mathematical and practical level. We approach the problem of equipping computers with high-level reasoning from a top-down, theoretical perspective. Rather than building up from examples or particular types of intelligent reasoning (e.g. the work of McCarthy, Lenat, and Reiter [McC90, LGPPS90, Rei80]), we have tried to step back as far away from the problem as possible, in order to grasp the larger picture. With such a broad perspective, we hope to discover underlying principles that pervade all high-level reasoning. A coherent and formal mathematical theory would bring new clarity and precision to a seemingly intractable subject.
Asynchronous approximate agreement

This paper examines the Approximate Agreement Problem in an asynchronous failure-by-omission system with deterministic protocols. We give a simple algorithm, and prove that the algorithm is optimal by considering the power of the "adversary" scheduler to disrupt processors? views. We show that the adversary need not cause any omissions to achieve its purpose, and therefore no algorithm can do better than simply to operate round-by-round, as our does. We extend these results to asynchronous crash-failure systems. The resulting understanding of the adversary should be applicable to other problems in asynchronous failure-by-omission or crash-failure-systems.
Effects of Tetramethylpyrazine on Functional Recovery and Neuronal Dendritic Plasticity after Experimental Stroke

The 2,3,5,6-tetramethylpyrazine (TMP) has been widely used in the treatment of ischemic stroke by Chinese doctors. Here, we report the effects of TMP on functional recovery and dendritic plasticity after ischemic stroke. A classical model of middle cerebral artery occlusion (MCAO) was established in this study. The rats were assigned into 3 groups: sham group (sham operated rats treated with saline), model group (MCAO rats treated with saline) and TMP group (MCAO rats treated with 20 mg/kg/d TMP). The neurological function test of animals was evaluated using the modified neurological severity score (mNSS) at 3 d, 7 d, and 14 d after MCAO. Animals were euthanized for immunohistochemical labeling to measure MAP-2 levels in the peri-infarct area. Golgi-Cox staining was performed to test effect of TMP on dendritic plasticity at 14 d after MCAO. TMP significantly improved neurological function at 7 d and 14 d after ischemia, increased MAP-2 level at 14 d after ischemia, and enhanced spine density of basilar dendrites. TMP failed to affect the spine density of apical dendrites and the total dendritic length. Data analyses indicate that there was significant negative correlation between mNSS and plasticity measured at 14 d after MCAO. Thus, enhanced dendritic plasticity contributes to TMP-elicited functional recovery after ischemic stroke.
A Versatile 1.4-mW 6-bits CMOS ADC for Pulse-Based UWB Communication Systems

An Analog to Digital Converter (ADC) using the low duty-cycle nature of pulse-based Ultra Wide-Band (UWB) communications to reduce its power consumption is proposed. Implemented in CMOS 180 nm technology, it can capture a 5 ns window at 4 GS/s each 100 ns, which corresponds to the acquisition of one UWB pulse at the pulse repetition rate of 10 mega pulses per second (Mpps). By using time-interleaved Redundant Signed Digit (RSD) ADCs, the complete ADC occupies only 0.15 mm2 and consumes only 1.4 mW from a 1.8 V power supply. The ADC can be operated in two modes using the same core circuits (operational transconductance amplifier, comparators, etc.). The first mode is the standard RSD doubling mode, while the second mode allows improving the signal-to-noise ratio by adding coherently the transmitted pulses of one symbol. For example, for audio applications, a 300 kbps data rate and processing gain up to 15 dB can be achieved at a clock frequency of 10 MHz.
A Cross National Study Using Anecdotal Accounts ofTrauma Reaction in Police Officers

This cross-national exploratory study was carried out to assess the nature of traumatic experiences, psychological reactions and challenges related to coping among police officers from Pakistan and the United Kingdom. The existing gap in available literature limits our understanding about how police officers involved in traumatic work experiences, cope and achieve resilient emotional reactions. The comparison of data obtained from five police officers of each country was made to assess similarities and differences in phenomenon. Analyses identified some of the main challenges to coping were negative public image, lack of logistic facilities and psychological support systems, and other personal and professional difficulties. These challenges are discussed from the perspective of trauma experiences in the two countries and coping strategies employed by security personnel to deal with the psychological outcomes. The findings have revealed that stigmatization was associated with psychological help and police officers consult their families and friends instead of professionals for mental health issues.