Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Normative Model of Grounding in Collaboration

We investigate the process by which individuals add information is to the common ground. This process, called grounding Clark and Schaefer, 1989] involves performing communicative actions of various sorts. The actions include those which present content to be added, as well as feedback Allwood et al., 1992], displaying the reaction to that content. Feedback can be either positive | an acknowledgment of understanding, or negative | repairing or displaying a lack of comprehension. We will call any action (whether presentation or feedback) that contributes to grounding, a grounding action. There have been several theories in the cognitive science literature about what minimal set of grounding actions and conditions is necessary for content to be considered grounded. Clark and Marshall, 1981] suggested that copresence of some sort, along with other assumptions, are one means to justify the assumption of common ground. Clark and Schaefer, 1989], on the other hand, contended that each presentation must be accepted, with an appropriate level of positive feedback. Traum and Allen, 1992], in presenting a computational account, took a somewhat intermediate approach, claiming that acknowledgments themselves did not require additional feedback to have their grounding eeect. These theories can provide justiication for an assumption about whether or not some content is part of the common ground, given some sequence of communicative acts. However, there has been comparatively less work on explaining exactly what kind, if any, grounding act should be made by a communicator at a particular time. Corpus studies have shown that the level and type of feedback varies widely with the medium of communication, among other things. E.g., Traum and Heeman, 1997] report that in a corpus of task-oriented spoken dialogue, over 95% of speaker turns begin with some form of feedback on the previous turn 1. On the other hand, we have seen in multi-modal computer-mediated collaboration experiments that typed \chat" messages received a direct acknowledgment only 41% of the time, while information displayed on a shared whiteboard received signiicantly fewer acknowledgments Dillenbourg et al., 1997a]. Media factors can be used to explain which content can be considered grounded, with reference to some of the assumptions like those of Clark and Marshall, 1981], which are present in the media. For example, speech has no temporal persistence, and so is either perceived immediately or is gone, while messages on a shared whiteboard are present until explicitly removed. However, there is still a problem: communicators …
Scalable entity matching computation with materialization

Entity matching (EM) is the task of identifying records that refer to the same real-world entity from different data sources. While EM is widely used in data integration and data cleaning applications, the naive method for EM incurs quadratic cost with respect to the size of the datasets. To address this problem, this paper proposes a scalable EM algorithm that employs a pre-materialized structure. Specifically, once the structure is built, our proposed algorithm can identify the EM results with sub-linear cost. In addition, as the rules evolve, our algorithm can efficiently adapt to new rules by selectively accessing records using the materialized structure. Our evaluation results show that our proposed EM algorithm is significantly faster than the state-of-the-art method for extensive real-life datasets.
Uncertain Litigation Cost and Seller Behavior: Evidence from an Auditing Game

This paper reports the results of two experiments, each consisting of six sessions, designed to investigate difficulties that arise in estimating expected litigation costs in an auditing game. In each experimental session, the game consists of a series of periods in which sellers submit sealed offers to computerized buyers and, if hired, choose an effort level (low or high). The effort level affects the certain (direct) and uncertain (litigation) costs of performing the engagement. Across the two experiments, we vary the uncertainty surrounding the determination of the expected litigation cost. Our results strongly suggest that cognitive limitations hinder sellers' abilities to estimate total expected litigation costs. Across both experiments we observe a nontrivial number of suboptimal effort choices. Moreover, as the uncertainty of determining the expected litigation cost increases, the frequency of observed fee offers below the total expected cost of an engagement increases markedly.
Approaching downlink capacity of multiplexing relay channels with imperfect channel information

This paper studies the multi-antenna relay downlink channel with quantized channel information feedback from both two-hop links. By characterizing the system capacity loss due to channel quantization, we propose a strategy of controlling feedback sizes to help the system approach the channel capacity with respect to full channel information case within an arbitrary predetermined capacity loss. It reveals that the feedback load B1 from the relay station (RS) to the base station (BS) needs to scale in proportion to both the transmit power at the BS and RS while the feedback size B2 from each user to the RS only needs to scale linearly with the transmit power at the RS. Simulation results illustrate the effectiveness of the proposed design strategy.
An Investigation into the Adoption of Electronic Commerce among Saudi Arabian SMEs

Despite the proliferation of e-commerce adoption by SMEs and the world-wide growth of e-commerce, in general there is a paucity of empirical studies that examine the adoption of e-commerce by SMEs in the Middle East. In this paper, the authors provide insights into the salient e-commerce adoption issues by focusing on Saudi Arabian SMEs. This research was designed using a qualitative approach through in-depth case studies selected from firms in Saudi Arabia. The findings contribute toward a better conceptual and practical understanding of the main factors driving SMEs to adopt e-commerce. The authors find that the level of e-commerce implementation has yet to mature and customer readiness for Internet shopping must improve before e-commerce reaches the levels of maturity seen in other regions of the world. This study highlights directions for future inquiry and implications for information and technology managers and policymakers in developing Arab nations.
Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis

User studies are typically difficult, recruiting enough users is often problematic and each experiment takes a considerable amount of time to be completed. In these studies, eye tracking is increasingly used which often increases time, therefore, the lower the number of users required for these studies the better for making these kinds of studies more practical in terms of economics and time expended. The possibility of achieving almost the same results with fewer users has already been raised. Specifically, the possibility of achieving 75% similarity to the results of 65 users with 27 users for searching tasks and 34 users for browsing tasks has been observed in scanpath trend analysis which discovers the most commonly followed path on a particular web page in terms of its visual elements or areas of interest (AOIs). Different approaches are available to segment or divide web pages into their visual elements or AOIs. In this paper, we investigate whether the possibility raised by the previous work is restricted to a particular page segmentation approach by replicating the experiments with two other segmentation approaches. The results are consistent with ~5% difference for the searching tasks and ~10% difference for the browsing tasks.
Self-adjusting Associative Rules Generator for Classification : An Evolutionary Computation Approach

The problem of generating efficient association rules can seen as search problem since many different sets of rules are possible from a given set of instances. As the application of evolutionary computation in searching is well studied, it is possible to utilize evolutionary computation in mining for efficient association rules. In this paper, a program known as self-adjusting associative rules generator (SARG) is described. SARG is a data mining program which can generate associative rules for classification. It is an improvement of the data mining program called genetic programming for inductive learning (GPIL). Both utilize evolutionary computation in inductive learning. The shortcoming of GPIL lies in the operations crossover and selection. These two operations were inflexible and not able to adjust themselves in order to select suitable methods for the task at hand. SARG introduces new method of crossover known as MaxToMin crossover together with a self-adjusting reproduction. It has been tested on several benchmark data sets available in the public domain. Comparison between GPIL and SARG revealed that SARG achieved better performance and was able to classify these data sets with higher accuracy. The paper also discusses relevant aspects of SARG and suggests directions for future work
How to represent scenes for classification?

Object-based scene image representations can effectively capture the semantic meanings of a scene. However, they usually neglect a scene's structure information. In this paper, we propose a novel and effective detector-based scene representation method for scene classification. In particular, we extract object features by object detectors. By sensible principal component analysis, we obtain a compact representation vector of objects in a scene image. To capture the scene layout, we then train lots of deformable part models to form a scene response vector. By concatenating these two vectors we use a linear support vector machine for scene classification. When combining with DeCAF [1] in a special way, our method is even more powerful on complex scene categorization. Experimental results on the MIT indoor database show that our approach achieves state-of-the-art performance on scene classification compared with several popular methods.
Center for Policy Research Working Paper No . 105 THE EFFECT OF DISABILITY INSURANCE ON HEALTH INVESTMENT : EVIDENCE FROM THE VA DISABILITY COMPENSATION PROGRAM

I examine whether individuals respond to monetary incentives to detect latent medical conditions. The effect is identified by an amendment to Title 38 that deemed diabetes associated with Agent Orange exposure a compensable disability under the VA’s Disability Compensation program. Since a diagnosis is a requisite for benefit eligibility, and nearly one-third of diabetics remain undiagnosed, the advent of disability insurance may have encouraged the detection of diabetes among the previously undiagnosed population. Evidence from the National Health Interview Survey suggests that the policy increased the prevalence of diabetes by 2.7 percentage points among veterans. JEL Codes: H0, I12
A representation independent geometric modeling kernel

This paper is concerned with "open kernel" geometric modelling systems. It uses industrial needs to identify requirements for the geometric objects of a proposed interface. The necessary mixed-dimension cellular objects are formally defined as the fundamental data abstractions for that interface. Such definitions are imperative for the construction of robust functions and the integrity of data transfer. As an example, formal specifications are provided for "set-like" object combination functions.
Using Computational Thinking Patterns to Scaffold Program Design in Introductory Programming Course

Visual programming languages (VPLs), such as Scratch and StarLogo TNG, can make computer science education more accessible to everyone. Current researches in the study of using VPLs for educational purposes primarily focus on understanding motivational benefits and computational thinking gains. All these educational VPLs claim to scaffold students learning computational thinking concepts. Although the evaluations show that students may exhibit more enthusiasm, it is not clear what computational thinking concepts are actually learned by students. In this paper, we attempt to develop a visual programs recognition tool for student-created StarLogo TNG simulations which representing the computational thinking concepts implemented by the students. Through collecting student's created projects over time, this visual programs recognition tool can possibly indicate the patterns of computational thinking in science simulations created by StarLogo TNG.
Silicon-Integrated Differential Bandpass Filters Based on Recursive and Channelized Principles and Methodology to Compute Their Exact Noise Figure

In this paper, two silicon-integrated differential active bandpass filters are presented. The first one is a recursive filter based on a cellular approach. This circuit is independently tunable in terms of power transmission gain, center frequency, and bandwidth. The chip surface is less than 1.4 mm2. For this prototype, measurements demonstrate a 1.9-2.4-GHz center-frequency tuning range with a typical gain of 15 dB and a 3-dB bandwidth of 60 MHz. Gains of up to 40 dB and bandwidths as low as 20 MHz are also achievable in the 2.05-2.38-GHz range. Subsequently, the design of an integrated three-branch channelized bandpass filter is addressed. The proposed filter uses an active power splitter at its input. Moreover, the channels are based on elementary first-order tunable recursive stages derived from the previously described topology, thus making the overall filter fully reconfigurable. This second circuit, whose layout size is smaller than 3 mm2, can exhibit 3-dB bandwidths of ap90 MHz and gains of up to 20 dB within a 1.95-2.23-GHz tuning range. Controllable high selectivity for each rejected band can be obtained through the generation of adjustable out-of-band transmission zeros. Furthermore, a dual-band behavior is also feasible through this filter. To conclude, an original method to extract the exact noise figure of differential circuits is reported, and applied to the filter prototypes developed in this study. The Philips QUBIC4 0.25-mum silicon BiCMOS process has been used for the design of the two circuits presented
Verbs as Linguistic Markers of Agency - The Social Side of Grammar

Basic grammatical categories may carry social meaning irrespective of their semantic content. In a set of four studies, we demonstrate that verbs – a basic linguistic category present and distinguishable in most languages – are related to the perception of agency, a fundamental dimension in social perception. In an archival analysis on actual language use in Polish and German, we found that targets stereotypically associated with high agency (men and young people) are presented in the immediate neighborhood of a verb more often than non-agentic social targets (women and old people). Moreover, in three experiments using a pseudo-word paradigm, verbs (but not adjectives and nouns) were consistently associated with agency (but not communion). These results provide consistent evidence that verbs, as grammatical vehicles of action, are linguistic markers of agency. In demonstrating meta-semantic effects of language, these studies corroborate the view of language as a social tool and of language as an integral part of social perception.
Data Transfer Matters for GPU Computing

Graphics processing units (GPUs) embrace many-core compute devices where massively parallel compute threads are offloaded from CPUs. This heterogeneous nature of GPU computing raises non-trivial data transfer problems especially against latency-critical real-time systems. However even the basic characteristics of data transfers associated with GPU computing are not well studied in the literature. In this paper, we investigate and characterize currently-achievable data transfer methods of cutting-edge GPU technology. We implement these methods using open-source software to compare their performance and latency for real-world systems. Our experimental results show that the hardware-assisted direct memory access (DMA) and the I/O read-and-write access methods are usually the most effective, while on-chip micro controllers inside the GPU are useful in terms of reducing the data transfer latency for concurrent multiple data streams. We also disclose that CPU priorities can protect the performance of GPU data transfers.
Socio-Demographic Correlates of Volunteerism among Undergraduate Students at North-West University, South Africa

ABSTRACT This article reports on a study that used a sample of undergraduate students at the North-West University, Mafikeng Campus, South Africa, to examine the effect of selected sociodemographic factors on the participation of voluntary activities amongst youth who have been exposed to the country’s higher education system. Specifically, the binary logit regression model was employed to analyse the effects of sociodemographic factors, such as age, gender, race, ethnicity, religion, family structure, maternal education, family socioeconomic status, academic performance and respondents’ perception of the importance of volunteering on five voluntary activities. The study found that male, older, black African, and Afrikaans-speaking youth are more likely to be involved in voluntary activities. Moreover, higher parental education, regular church attendance and being a Protestant as opposed to being a Catholic are all positively associated with youth volunteering. The single most important factor with regard to youth volunteerism is their perception of the importance of volunteering, a finding which underscores the role of socialisation in youth volunteerism.
Marriage Promotion and Low-Income Communities: An Examination of Real Needs and Real Solutions. Briefing Paper.

One of the most private, personal, and critical decisions one makes in life is if, when, and whom one should marry. It seems the ultimate in big government, if not social engineering, to have public policy anywhere near these critical, life-altering decisions; but this is precisely what some members of Congress and the Bush Administration have in mind, to the tune of $200-300 million per year, in the context of TANF reauthorization. Described in language that articulates the desire to help build only “healthy” marriages, the proposal may at first, seem reasonable—that is, until the plan’s many inclusions come into full view. For example: why use poverty reduction dollars to fund marriage counseling activities for individuals who may or may not be poor; and why even take the risk of potentially encouraging low-income women to stay in abusive marriages? Ultimately, why not seek to build strong, healthy, and economically-secure families of all types, regardless of marital status, instead of being limited to the Ozzie and Harriet model? To think more broadly in this way is not anti-marriage. To the contrary, it is pro-family in the ultimate sense, in that it respects and supports the many faces of America’s families. Be they single, divorced, widowed, same-sex couples, or involved in cohabitating relationships, low-income families of all types deserve the same care and support that married families do if our ultimate goal is to provide stable, economically secure households within which children can flourish.
Eigenface-Gabor Algorithm for Features Extraction in Face Recognition

Algorithms; several methods are used to extract image face features vector, which presents small inter-person variation. This feature vector is feed to a multilayer perceptron to carry out the face recognition or identity verification tasks. Proposed system consists in a combination of Gabor and Eigenfaces to obtain the feature vector. Evaluation results show that proposed system provides robustness against changes in illumination, wardrobe, facial expressions, scale, and position inside the captured image, as well as inclination, noise contamination and filtering. Proposed scheme also provides some tolerance to changes on the age of the person under analysis. Evaluation results using the proposed scheme with identification and verification configurations are given and compared with other feature extraction methods to show the desirable features of proposed algorithm.
Genome-Wide Analysis of Citrus R2R3MYB Genes and Their Spatiotemporal Expression under Stresses and Hormone Treatments

The R2R3MYB proteins represent one of the largest families of transcription factors, which play important roles in plant growth and development. Although genome-wide analysis of this family has been conducted in many species, little is known about R2R3MYB genes in citrus, In this study, 101 R2R3MYB genes has been identified in the citrus (Citrus sinesis and Citrus clementina) genomes, which are almost equal to the number of rice. Phylogenetic analysis revealed that they could be subdivided into 21 subgroups. The evolutionary relationships and the intro-exon organizations were also analyzed, revealing strong gene conservation but also the expansions of particular functional genes during the plant evolution. Tissue-specific expression profiles showed that 95 citrus R2R3MYB genes were expressed in at least one tissue and the other 6 genes showed very low expression in all tissues tested, suggesting that citrus R2R3MYB genes play important roles in the development of all citrus organs. The transcript abundance level analysis during abiotic conditions (NaCl, abscisic acid, jasmonic acid, drought and low temperature) identified a group of R2R3MYB genes that responded to one or multiple treatments, which showed a promising for improving citrus adaptation to stresses. Our results provided an essential foundation for the future selection of the citrus R2R3MYB genes for cloning and functional dissection with an aim of uncovering their roles in citrus growth and development.
Ontology-based architecture with recommendation strategy in java tutoring system

The aim of Semantic Web is to provide distributed information with well-defined meaning, understandable for humans as well as machines. E-learning is an important domain which can be benefited from the Semantic Web technology. Ontologies, as a building structure of Semantic Web, will fundamentally change the way in which e-learning systems are constructed. The explicit conceptualization of system components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration among system components, and construction of intensive and expressive systems. In previous research, we implemented tutoring system named Protus (PRogramming TUtoring System) that is used for learning basic concepts of Java programming language. Protus uses principles of learner style identification and content recommendation for course personalization. The new version of the system called Protus 2.0, supported by several ontologies, as well as examples of its usage for performing personalization are presented in this paper. Architecture of new system extends the usage of Semantic Web concepts, where the representation of each Protus 2.0 component is made by a specific ontology, making possible a clear separation of the tutoring system components and explicit communication among them. [Projekat Ministarstva nauke Republike Srbije, br. III47003]