Miracle-dz/UniFAR-FTUs huggingface dataset:
Please Scroll down for Article Journal of the Learning Sciences Flowing toward Correct Contributions during Group Problem Solving: a Statistical Discourse Analysis Flowing toward Correct Contributions during Group Problem Solving: a Statistical Discourse Analysis Group Problem-solving Processes

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Groups that created more correct ideas (correct contributions or CCs) might be more likely to solve a problem, and students' recent actions (micro-time context) might aid CC creation. 80 high school students worked in groups of 4 on an algebra problem. Groups with higher mathematics grades or more CCs were more likely to solve the problem. Dynamic multilevel analysis statistically identified watersheds (break-points) that divided each group's conversation into distinct time periods with many CCs versus few CCs, and modeled the groups' 2,951 conversation turns. Wrong contributions , correct evaluations of one another's ideas, justifications, and polite disagreements increased the likelihood of a CC. In contrast, questions, rude disagreements , and agreements reduced it. Justifications had the largest effects, whereas the effects of correct evaluations lasted 3 speaker turns. Some effects differed across groups or time periods. In groups that solved the problem, justifications were more likely to yield CCs, and questions were more likely to elicit explanations. Meanwhile , the effects of agreements and correct evaluations on CCs differed across time periods. Applied to practice, teachers can encourage students to evaluate others' ideas carefully and politely, express and justify their own ideas, and explain their answers to group members' questions. Past research suggests that groups with more CCs are more likely to solve a problem correctly than other groups (functional theory of group decision-making; Orlitzky & Hirokawa, 2001). Let us call this Hypothesis 1 (H-1). (Hypotheses are numbered according to their level of analysis: group, 1; time period, 2; speaker turn, 3.) H-1.Groups with more CCs are more likely to solve the problem correctly.
Sales Force Control: A Synthesis of Three Theories

This article, first, synthesizes three theoretical approaches to salesforce control systems and, second, examines the effect of the control mechanisms on key consequence variables. More specifically, the manuscript develops a comprehensive model of salesforce control by integrating key constructs from three alternative theories: organization theory, agency theory, and transaction cost analysis. The constructs are (1) outcome observability from organization theory, (2) behavior observability from agency theory, (3) transaction-specific assets (TSA) from transaction cost analysis, and (4) task programmability or environmental task uncertainty, a key construct in all three theories. In addition, the study examines the effects of controls on certain consequence variables: salesperson-customer relationships and salespersons' motivation and organizational commitment.
Social inclusion as feature to improve BCI skill training: A feasibility case study in cerebral palsy

Introduction: Operating brain-computer interfaces (BCIs) that are based on modulation of spontaneous electroencephalogram (EEG) rhythms is a skill that users have to learn. Training time varies significantly among users and it can take up to several months of time before minimum BCI control becomes possible. One reason for this may be the design of BCI training paradigms [1]. Trials of mental activity are collected prior to BCI use and used to calibrate BCI model parameters. During this initial data collection no feedback is provided to users. This is not very motivating and engaging for users. Recently, we introduced a thought-based one-switch row-column communication board for users with cerebral palsy [2]. To make BCI skill learning more motivating, we lately also introduced a jigsaw puzzle game-based training paradigm [3] that presents feedback from the very start. Initially sham feedback and once enough data is available for BCI calibration, online feedback. Moreover, the game was designed following user-centered design principles and explains the concept of BCI use and allows users to get familiar with the dynamics of BCI control. A pilot study in four users with cerebral palsy (CP) showed that the acceptance was high and users liked the game-based training approach [3]. Three out of the four users achieved performance better than chance level after about 30 minutes of training. Fig. 1 shows a user assembling a puzzle. Here, we propose social inclusion as another feature for improving BCI training. End users should not perform training alone but engage in direct competition with other persons.
Exploiting collaborative learning for concept extraction in the medical field

With the increasing interests of second use of medical data, concept extraction in Electronic Medical Records has drawn more and more scholars' attention. Owing to the artificial data annotation task is labor intensive, the method of concept extraction is mainly to use the fully labeled documents as training data in order to build a concept instance identifier. However, in many cases, the available training data are sparse labeling. This fact makes the performance of the constructed classifier is poor. Existing methods for extracting concepts either considered the diversity of datasets or considered the various learning models. Therefore, this paper proposes a novel approach to improve the performance of concept extraction from electronic medical records by combining the diversity of datasets with the various learning models. The large sparsely labeled dataset is split into multiple subsets. Then the different subsets are trained by different learning models, such as HMM, MEMM, and CRF, in an iterative way. Our technique leverages off the fact that different learning algorithms have different inductive biases and that better predictions can be made by the voted majority.
ASYMPTOTIC BEHAVIOUR OF A METAPOPULATION MODEL

We study the behaviour of an infinite system of ordinary differential equations modelling the dynamics of a meta-population, a set of (discrete) populations subject to local catastrophes and connected via migration under a mean field rule; the local population dynamics follow a generalized logistic law. We find a threshold below which all the solutions tend to total extinction of the meta-population, which is then the only equilibrium; above the threshold, there exists a unique equilibrium with positive population, which, under an additional assumption, is globally attractive. The proofs employ tools from the theories of Markov processes and of dynamical systems.
Synergies in learning words and their referents

This paper presents Bayesian non-parametric models that simultaneously learn to segment words from phoneme strings and learn the referents of some of those words, and shows that there is a synergistic interaction in the acquisition of these two kinds of linguistic information. The models themselves are novel kinds of Adaptor Grammars that are an extension of an embedding of topic models into PCFGs. These models simultaneously segment phoneme sequences into words and learn the relationship between non-linguistic objects to the words that referto them. We show (i) that modelling inter-word dependencies not only improves the accuracy of the word segmentation but also of word-object relationships, and (ii) that a model that simultaneously learns word-object relationships and word segmentation segments more accurately than one that just learns word segmentation on its own. We argue that these results support an interactive view of language acquisition that can take advantage of synergies such as these.
An Integrated Framework for Robust Human-Robot Interaction

Developments in sensor technology and sensory input processing algorithms have enabled the use of mobile robots in real-world domains. As they are increasingly deployed to interact with humans in our homes and offices, robots need the ability to operate autonomously based on sensory cues and high-level feedback from non-expert human participants. Towards this objective, this chapter describes an integrated framework that jointly addresses the learning, adaptation, and interaction challenges associated with robust human-robot interaction in real-world application domains. The novel probabilistic framework consists of: (a) a bootstrap learning algorithm that enables a robot to learn layered graphical models of environmental objects and adapt to unforeseen dynamic changes; (b) a hierarchical planning algorithm based on partially observable Markov decision processes (POMDPs) that enables the robot to reliably and efficiently tailor learning, sensing, and processing to the task at hand; and (c) an augmented reinforcement learning algorithm that enables the robot to acquire limited high-level feedback from non-expert human participants, and merge human feedback with the information extracted from sensory cues. Instances of these algorithms are implemented and fully evaluated on mobile robots and in simulated domains using vision as the primary source of information in conjunction with range data and simplistic verbal inputs. Furthermore, a strategy is outlined to integrate these components to achieve robust human-robot interaction in real-world application domains.
Design of a rotary elastic actuator for use as torque-actuator in rehabilitation robots

In this paper, the modelling and control of an elastic actuator are investigated. First, the specifications of the actuator are defined and then a model of the actuator is presented reflecting the required specification. Further, the model is analysed and investigated to evaluate the specification of the system. Moreover, a control algorithm is proposed to be used for the actuator. The control algorithm utilizes a PI controller for the actuator speed, and a PID controller for the actuator output torque. Integrating the controllers into the actuator, a series of tests are performed on the actuator to show the actuator performance. The first is the accuracy of the output torque delivered by the spring. The results of the first test indicate that the spring behaves linearity, and can be used simply to deliver linear torque. The second test is the frequency response bandwidth measurement. The results show that the actuator is capable of excreting torque in the frequency range of rehabilitation applications. Finally, it is shown that the actuator can provide the rehabilitation requirements properly.
USAAR-SAPE: An English–Spanish Statistical Automatic Post-Editing System

We describe the USAAR-SAPE English‐ Spanish Automatic Post-Editing (APE) system submitted to the APE Task organized in the Workshop on Statistical Machine Translation (WMT) in 2015. Our system was able to improve upon the baseline MT system output by incorporating Phrase-Based Statistical MT (PBSMT) technique into the monolingual Statistical APE task (SAPE). The reported final submission crucially involves hybrid word alignment. The SAPE system takes raw Spanish Machine Translation (MT) output provided by the shared task organizers and produces post-edited Spanish text. The parallel data consist of English Text, raw machine translated Spanish output, and their corresponding manually post-edited versions. The major goal of the task is to reduce the post-editing effort by improving the quality of the MT output in terms of fluency and adequacy.
DR AF T TeXCP : Responsive Yet Stable Traffic Engineering

Intra-domain Traffic Engineering (TE) aims to route around failures and congestion, and balance load in an ISP’s network. Current TE relies on offline methods which use long term average traffic demands. It cannot react to traffic changes caused by BGP reroutes, diurnal traffic variations, attacks, or flash crowds. Further, current TE deals with network failures by pre-computing alternate routings for a limited set of failures. It may fail to prevent congestion when unanticipated or combination failures occur even though the network may have enough capacity to handle those failures. Since ISPs must ensure that each path in the network can cope with the peak load both during normal operation and under failures, current TE requires extensive over-provisioning. This paper presents TeXCP, an online distributed TE protocol that balances load in real-time, responding to actual traffic demands and failures. TeXCP uses multiple paths to deliver demands from an ingress to an egress router, adaptively moving traffic from overutilized to under-utilized paths. These adaptations are carefully designed such that, though done independently by each edge router based on local information, they balance load in the whole network without oscillations. We prove TeXCP is stable and show it is easy to implement. Our extensive simulations show that, for the same traffic demands, a network that uses TeXCP can support the same utilization and failure resilience as a network that uses traditional offline TE, but with a half or a third of the capacity.
Adaptive scheduling to maximize NIC throughput in a COTS router

In routers based on commodity off-the-shelf (COTS) hardware and open-source operating systems, there are correlations between the transmission and reception capabilities of individual network interface cards (NICs) and multiple NICs on the same bus because of NIC/bus bottlenecks. To manage the adverse effects of this correlation, we propose an adaptive scheduling mechanism based on system state information, which balances transmission and reception rates and increases the overall forwarding rate.
Mismatch of Sleep and Work Timing and Risk of Type 2 Diabetes

OBJECTIVE To examine whether a mismatch between chronotype (i.e., preferred sleep timing) and work schedule is associated with type 2 diabetes risk. RESEARCH DESIGN AND METHODS In the Nurses’ Health Study 2, we followed 64,615 women from 2005 to 2011. Newly developed type 2 diabetes was the outcome measure (n = 1,452). A question on diurnal preference ascertained chronotype in 2009; rotating night shift work exposure was assessed regularly since 1989. RESULTS Compared with intermediate chronotypes, early chronotypes had a slightly decreased diabetes risk after multivariable adjustment (odds ratio 0.87 [95% CI 0.77–0.98]), whereas no significant association was observed for late chronotypes (1.04 [0.89–1.21]). Among early chronotypes, risk of type 2 diabetes was modestly reduced when working daytime schedules (0.81 [0.63–1.04]) and remained similarly reduced in women working <10 years of rotating night shifts (0.84 [0.72–0.98]). After ≥10 years of shift work exposure, early chronotypes had a nonsignificant elevated diabetes risk (1.15 [0.81–1.63], Ptrend = 0.014). By contrast, among late chronotypes, the significantly increased diabetes risk observed among day workers (1.51 [1.13–2.02]) appeared largely attenuated if their work schedules included night shifts (<10 years: 0.93 [0.76–1.13]; ≥10 years: 0.87 [0.56–1.34]; Ptrend = 0.14). The interaction between chronotype and shift work exposure was significant (Pinteraction = 0.0004). Analyses restricting to incident cases revealed similar patterns. CONCLUSIONS In early chronotypes, type 2 diabetes risk increased with increasing duration of shift work exposure, whereas late types had the highest diabetes risk working daytime schedules. These data add to the growing body of evidence that workers could benefit from shift schedules minimizing interference with chronotype-dependent sleep timing.
Two algorithms for maintaining order in a list

The order maintenance problem is that of maintaining a list under a sequence of Insert and Delete operations, while answering Order queries (determine which of two elements comes first in the list). We give two new algorithms for this problem. The first algorithm matches the O(1) amortized time per operation of the best previously known algorithm, and is much simpler. The second algorithm permits all operations to be performed in O(1) worst-case time.
T-less : A novel touchless human-machine interface based on infrared proximity sensing

In today's industry, intuitive gesture recognition, as manifested in numerous consumer electronics devices, becomes a main issue of HMI device research. Although finger-tip touch based user interface has paved a main stream in mobile electronics, we envision touch-less HMI as a promising technology in futuristic applications with higher potential in areas where sanity or outdoor operation become of importance. In this paper, we introduce a novel HMI device for non-contact gesture input for intuitive HMI experiences. The enabling technology of the proposed device is the IPA (infrared Proximity Array) sensor by which realtime 3 dimensional depth information can be captured and realized for machine control. For the usability study, two different operating modes are adopted for hand motion inputs: one is a finger tip control mode and the other is a palm control mode. Throughput of the proposed device has been studied and compared to a traditional mouse device for usability evaluation. During the human subject test, the proposed device is found to be useful for PC mouse pointer control. The experimental results are shared in the paper as well.
Generating Facial Expressions

In this report, I use CAS-PEAL dataset [1] to try and generate facial expressions. That is, I take in, say, a smiling face, and try to generate a face that is neutral. I build off Ghodrati’s, et al. [2] to see if I generate facial expressions. Finally, I use a variant of Deep Convolutional Adversarial Networks, hereafer DCGAN’s, [7] to generate a facial expressions.
Observation of isoprene hydroxynitrates in the southeastern United States and implications for the fate of NOx

Abstract. Isoprene hydroxynitrates (IN) are tracers of the photochemical oxidation of isoprene in high NOx environments. Production and loss of IN have a significant influence on the NOx cycle and tropospheric O3 chemistry. To better understand IN chemistry, a series of photochemical reaction chamber experiments was conducted to determine the IN yield from isoprene photooxidation at high NO concentrations (> 100 ppt). By combining experimental data and calculated isomer distributions, a total IN yield of 9(+4/−3) % was derived. The result was applied in a zero-dimensional model to simulate production and loss of ambient IN observed in a temperate forest atmosphere, during the Southern Oxidant and Aerosol Study (SOAS) field campaign, from 27 May to 11 July 2013. The 9 % yield was consistent with the observed IN/(MVK+MACR) ratios observed during SOAS. By comparing field observations with model simulations, we identified NO as the limiting factor for ambient IN production during SOAS, but vertical mixing at dawn might also contribute (~ 27 %) to IN dynamics. A close examination of isoprene's oxidation products indicates that its oxidation transitioned from a high-NO dominant chemical regime in the morning into a low-NO dominant regime in the afternoon. A significant amount of IN produced in the morning high NO regime could be oxidized in the low NO regime, and a possible reaction scheme was proposed.
Ricci flow with surgery on three-manifolds

This is a technical paper, which is a continuation of math.DG/0211159. Here we construct Ricci flow with surgeries and verify most of the assertions, made in section 13 of that e-print: the exceptions are (1) the statement that manifolds that can collapse with local lower bound on sectional curvature are graph manifolds - this is deferred to a separate paper, since the proof has nothing to do with the Ricci flow, and (2) the claim on the lower bound for the volume of maximal horns and the smoothness of solutions from some time on, which turned out to be unjustified and, on the other hand, irrelevant for the other conclusions.
Practical Protection of Kernel Integrity for Commodity OS from Untrusted Extensions

Kernel extensions are widely used by attackers to compromise the operating system kernel. With the presence of various untrusted extensions, it remains a challenging problem to comprehensively preserve the integrity of OS kernels in a practical and generic way. In this paper, we present HUKO, a hypervisor-based integrity protection system designed to protect commodity OS kernels from untrusted extensions. In HUKO system, untrusted kernel extensions can safely run to provide desired functionalities. The behaviors of untrusted extensions, however, are confined by mandatory access control policies, which significantly limit the attacker’s ability to compromise the integrity of the kernel. To guarantee multi-aspect protection and enforcement, HUKO leverages hardware assisted paging to transparently isolate untrusted extensions from the OS kernel. Moreover, HUKO overcomes the challenge of mediation overhead by introducing a novel design named subject-aware protection state transition to eliminate unnecessary privilege transitions caused by mediating allowed accesses. Our approach is practical because it requires little change for either OS kernel or extensions, and it can inherently support multiple commodity operating systems and legacy extensions. We have implemented a prototype of HUKO based on the open source Xen hypervisor. The evaluation results show that HUKO can comprehensively protect the integrity for both Linux and Windows kernel from various kinds of malicious extensions with an acceptable performance cost.
A SURVEY ON ENERGY EFFICIENT SERVER CONSOLIDATION THROUGH VM LIVE MIGRATION

Virtualization technologies which are heavily relied on by the Cloud Computing environments provide the ability to transfer virtual machines (VM) between the physical systems using the technique of live migration mainly for improving the energy efficiency. Dynamic server consolidation through live migration is an efficient way towards energy conservation in Cloud data centers. The main objective is to keep the number of power-on systems as low as possible and thus reduce the excessive power used to run idle servers. This technique of VM live migration is being used widely for various system-related issues like load balancing, online system maintenance, fault tolerance and resource distribution. Energy efficient VM migration becomes a main concern as the data centers are trying to reduce the power consumption. Aggressive consolidation may even lead to performance degradation and hence can result in Service Level Agreement (SLA) violation. Thus there is a trade-off between energy and performance. Various protocols, heuristics and architectures have been proposed for the energy aware server consolidation via live migration of VMs and are the main area for this survey.