Miracle-dz/UniFAR-FTUs huggingface dataset:
Region analysis and a pi-calculus with groups

We show that the typed region calculus of Tofte and Talpin can be encoded in a typed π-calculus equipped with name groups and a novel effect analysis. In the region calculus, each boxed value has a statically determined region in which it is stored. Regions are allocated and de-allocated according to a stack discipline, thus improving memory management. The idea of name groups arose in the typed ambient calculus of Cardelli, Ghelli, and Gordon. There, and in our π-calculus, each name has a statically determined group to which it belongs. Groups allow for type-checking of certain mobility properties, as well as effect analyses. Our encoding makes precise the intuitive correspondence between regions and groups. We propose a new formulation of the type preservation property of the region calculus, which avoids Tofte and Talpin's rather elaborate co-inductive formulation. We prove the encoding preserves the static and dynamic semantics of the region calculus. Our proof of the correctness of region de-allocation shows it to be a specific instance of a general garbage collection principle for the π-calculus with effects. We propose new equational laws for letregion, analogous to scope mobility laws in the π-calculus, and show them sound in our semantics.
Mutually Beneficial Foreign Language Learning: Creating Meaningful Interactions through Video-Synchronous Computer-Mediated Communication.

Providing learners of a foreign language with meaningful opportunities for interactions, specifically with native speakers, is especially challenging for instructors. One way to overcome this obstacle is through video-synchronous computer-mediated communication tools such as Skype software. This study reports quantitative and qualitative data from a Skype partner program that emphasized meaningful communication between American students learning Japanese in the United States and Japanese students learning English in Japan. Analysis of pre- and posttests showed significant improvement in the listening and speaking abilities of the Japanese participants and in the speaking abilities of the American participants.
Human Identification using Silhouette Gait Data

Identificaiton of people using a set of gait image sequences in varing situations is a challenging problem. We use a bilinear model to separate two independent factors, gait style and phase. N-normalized gait poses is defined and generated by embedding gait image sequences to a standard lower dimensional manifold and learning mapping from the manifold to every pixel. This normalized gait phase is used to collect aligned gait poses from different speed walking image sequence. We identify gait style-vectors, which represent factors invariant to gait pose. Gaitcontent vectors, dependent on the environment,are adapted to the new environment. Using a boosted gait content vector, we get a better human identification accuracy than when using the original phase vector before identifying gait content vector. Support vector machines are used to improve classification.
Multi-speaker DOA tracking using interactive multiple models and probabilistic data association

The general problem addressed in this work is that of tracking the Direction of Arrival (DOA) of active moving speakers in the presence of background noise and moderate reverberation level in the acoustic field. In order to efficiently beamform each moving speaker on an extended basis we adapt the theory developed in the context of Multi-target Tracking for military and civilian applications to the context of microphone array. Our approach employs Wideband MUSIC and Interacting Multiple Model (IMM) estimators to estimate the DOAs of the speakers under different kinds of motion and sudden change in their course. Probabilistic Data Association (PDA) is used to disambiguate and resolve DOA measurements. The efficiency of the approach is illustrated on simulated and real room experiments dealing with the crossing trajectories of two speakers.
Promotion and Prevention Across Mental Accounts: When Financial Products Dictate Consumers' Investment Goals

We propose that consumers’ investment decisions involve processes of promotion and prevention regulation that are managed across separate mental accounts, with different financial products seen as representative of promotion versus prevention. Consistent with this hypothesis, we show that (a) investors are differentially sensitive to gains and losses and differentially risk seeking depending on the financial products being considered and (b) that these phenomena occur because of strong associations between financial products and promotion versus prevention. Therefore, investors’ goals may be determined by the investment opportunities under evaluation rather than being independent of these opportunities, as is assumed in standard finance theory.
Applying reinforcement learning towards automating resource allocation and application scalability in the cloud

Public Infrastructure as a Service (IaaS) clouds such as Amazon, GoGrid and Rackspace deliver computational resources by means of virtualisation technologies. These technologies allow multiple independent virtual machines to reside in apparent isolation on the same physical host. Dynamically scaling applications running on IaaS clouds can lead to varied and unpredictable results because of the performance interference effects associated with co‐located virtual machines. Determining appropriate scaling policies in a dynamic non‐stationary environment is non‐trivial. One principle advantage exhibited by IaaS clouds over their traditional hosting counterparts is the ability to scale resources on‐demand. However, a problem arises concerning resource allocation as to which resources should be added and removed when the underlying performance of the resource is in a constant state of flux. Decision theoretic frameworks such as Markov Decision Processes are particularly suited to decision making under uncertainty. By applying a temporal difference, reinforcement learning algorithm known as Q‐learning, optimal scaling policies can be determined. Additionally, reinforcement learning techniques typically suffer from curse of dimensionality problems, where the state space grows exponentially with each additional state variable. To address this challenge, we also present a novel parallel Q‐learning approach aimed at reducing the time taken to determine optimal policies whilst learning online. Copyright © 2012 John Wiley & Sons, Ltd.
Further Investigation of Responding Elicited by BC and C after A+, AB-, ABC+ Training

Two experiments with pigeons explored conditioned keypeck responding to new visual targets after visual compound discrimination training. In the first experiment, pigeons were trained with an A+, AB−, ABC+, AD−, ADC+ task, in which stimulus A signalled food, stimulus compounds AB and AD signalled no food, and stimulus compounds ABC and ADC signalled food. According to both an elemental model (Rescorla & Wagner, 1972) and a configural model (Pearce, 1987) of Pavlovian conditioning, test compounds BC and DC should elicit less responding than should C alone. However, the birds responded more to BC and DC than to C. In the second experiment, another set of pigeons was trained with an A+, AB−, ABC+, AD−, ADE+ task, in which stimulus A signalled food, stimulus compounds AB and AD signalled no food, and stimulus compounds ABC and ADE signalled food. Contrary to the prediction of the Rescorla-Wagner model, keypeck responding was not less on BC and DE trials than on C and E trials in testing. However, B and D attenuated responding to E and C, respectively, when presented in compounds BE and DC. The Pearce model was able to accommodate these results.
System Level Model for the Wireless Channel Unreliability in Mobile Cellular Networks

In this paper, a new system level approach for the wireless channel unreliability modeling is proposed. Firstly, in order to characterize the call interruption process due to the wireless channel unreliability, the Gilbert-Elliot model is used to obtain the probability distribution of the interruption time. Then, it is shown that link unreliability can be adequately modeled by considering a Poissonian call interruption process. This allows simplifying system level mathematical analysis and easily identifying the factors that mainly influence the performance of mobile cellular networks. For the characterization of the interruption process in real cellular networks, it is enough to know some few system level statistics that can be easily obtained at base stations. Then, with the proposed call interruption modeling, an elegant teletraffic analysis for the performance evaluation of mobile cellular networks considering both wireless link unreliability and resource insufficiency is developed.
Malnutrition in South-Asia. Poverty, diet or lack of female empowerment?

Despite economic growth, and a reduction in poverty, malnutrition is still rampant in South-Asia. This indicates that non-economic factors are important, and we use a nation-wide survey from Nepal to identify factors that may explain why small children are stunted. In contrast to designated studies of child nutrition we do not have information on individual food intake, but we demonstrate that analysis of large sample surveys is a good supplement to designated studies, with the main benefit being that findings are nationally representative. We find that pulses are critical for child growth, and that boys are more often malnourished, maybe because they are expected to take other food than breast milk. Furthermore we find that girls are more likely malnourished if they have many older brothers, and we find that female empowerment improves child nutrition.
Bag-of-visual-words vs global image descriptors on two-stage multimodal retrieval

The Bag-Of-Visual-Words (BOVW) paradigm is fast becoming a popular image representation for Content-Based Image Retrieval (CBIR), mainly because of its better retrieval effectiveness over global feature representations on collections with images being near-duplicate to queries. In this experimental study we demonstrate that this advantage of BOVW is diminished when visual diversity is enhanced by using a secondary modality, such as text, to pre-filter images. The TOP-SURF descriptor is evaluated against Compact Composite Descriptors on a two-stage image retrieval setup, which first uses a text modality to rank the collection and then perform CBIR only on the top-K items.
On the relationship between the streamfunction and velocity potential of the Madden-Julian oscillation

Abstract The streamfunction and velocity potential variances associated with the Madden–Julian oscillation are explained substantially by their zonal wavenumber-1 components, which are used to measure quantitatively the phase relationship between the two variables. There exists a quarter-cycle phase difference between them. A simplified streamfunction budget equation was used to demonstrate analytically that this spatial quadrature relationship is maintained through the counteraction between streamfunction tendencies induced by the horizontal advection of planetary vorticity and the divergence of planetary vorticity flux.
A Pragmatic Analysis of Humor Words in English Advertisements

As an independent discipline, pragmatics was through out thirty years’ development. It is also a young discipline. As a medium emerging commonly in advertising language art, humor has attracted wide attention of many producers. Previous scholars analyzed more from the perspective of grammar, vocabulary, rhetoric, etc. But the research of advertising language humor is lacking from the aspects of pragmatic rules. Our collection of data is quite open. Any advertisement that can be transcribed in to written form is our interest. They are excerpted from magazines, advertisement, collecting books, newspapers, TV and radio commercials. As we only focus on language humor, situational humor produced by visual performance is not involved this thesis. The advertising language art of humor has been widely paid attention. Based on the existing theories of humor research, author of this paper used many kinds of pragmatic theories to analyze English advertising humor language, and including reference, deixis, anaphora, presupposition, speech act theory, the cooperative principle, conversational implicatures, and the politeness principle. It can not only provide reference for the research of this field for later scholars, but also provide theoretical guidance for the AD makers of using humor language to produce a good advertising effect.
Perceived Social Support and Facebook Use Among Adolescents

Online social networks have gained considerable popularity among adolescents, but investigations on adolescent engagement with this technology have been limited. The current study investigated adolescentsâ€™ Facebook use with regard to their perceived social support characteristics. The data were collected from 255 adolescents in two provincial state schools in Turkey. A personal information form and 12 scaled items were used to collect data. A confirmatory factor analysis was conducted on scale items and relationships between social support and Facebook use behaviors were investigated. Findings revealed that perceived social support from significant others were predicted by the time spent on Facebook. More support from actual face-to-face friends meant fewer online friends whereas more support from significant others meant more online friends. Profile and security settings varied with regard to perceived social support as well. Regardless of socioeconomic status, less family support was related with adding unknown people haphazardly, and using Internet cafA©s. Finally, less friend support was related with resorting to nicknames rather than real names. Findings are discussed accompanied with limitations of the current study and suggestions for further research.
Comparison between type-1 fuzzy membership functions for sign language applications

The paper presents a comparison between different membership functions based type-1 fuzzy set for automatic hand gesture recognition for American Sign Language recognition. First pre-processing of the images is done using skin color based segmentation, morphological operations and to extract the hand gesture image from the background, Sobel edge detection technique is performed. Then the image is sub-divided into 9 quadrants and for each quadrant, the area enclosed by the image in that specific quadrant is calculated. Based on areas from 15 images for a particular quadrant, the Gaussian three membership curves triangular, trapezoidal and Gaussian are designed. Now for an unknown gesture, nine membership values are determined and the summation of these membership values produces the strength of the unknown hand gesture matched with a known gesture. The highest strength obtained for a known gesture is the desired result. Experimentally, it is found that trapezoidal membership function outperforms the other two membership functions and gives overall an accuracy of 85.83%.
SQuAVisiT: A Software Quality Assessment and Visualisation Toolset

Software quality assessment of large COBOL industrial legacy systems, both for maintenance or migration purposes, mounts a serious challenge. We present the software quality assessment and visualisation toolset (SQuAVisiT), which assists users in performing the above task. First, it allows a fully automatic extraction of metrics, call information, and code duplication from COBOL source code. This information, stored into a database, can be easily converted and exported to a set of visualization tools. We incorporated several such third-party tools for the visualization of call relations and system structure, and metrics visualization. These tools use novel visualization techniques such as bundled edges, matrix plots, and table lens. We illustrate the usage of our toolset with an industrial case study on a COBOL system comprising about 3000 modules and 1.7 million lines of code.
Entity Oriented Task Extraction from Query Logs

Identifying user tasks from query logs has garnered considerable interest from the research community lately. Several approaches have been proposed to extract tasks from search sessions. Current approaches segment a user session into disjoint tasks using features extracted from query, session or clicked document text. However, user tasks most often than not are entity centric and text based features will not exploit entities directly for task extraction. In this work, we explore entity specific task extraction from search logs. We evaluate the quality of extracted tasks with Session track data. Empirical evaluation shows that terms associated with entity oriented tasks can not only be used to predict terms in user sessions but also improve retrieval when used for query expansion.
Space-efficient parallel algorithms for combinatorial search problems

We present space-efficient parallel strategies for two fundamental combinatorial search problems, namely, backtrack search and branch-and-bound, both involving the visit of an n-node tree of height h under the assumption that a node can be accessed only through its father or its children. For both problems we propose efficient algorithms that run on a distributed-memory machine with p processors. For backtrack search, we give a deterministic algorithm running in \({O}\left(n/p+h\log p\right)\) time, and a Las Vegas algorithm requiring optimal \({O}\left(n/p+h\right)\) time, with high probability. Building on the backtrack search algorithm, we also derive a Las Vegas algorithm for branch-and-bound which runs in \({O}\left((n/p+h\log p \log n)h\log n\right)\) time, with high probability. A remarkable feature of our algorithms is the use of only constant space per processor, which constitutes a significant improvement upon previously known algorithms whose space requirements per processor depend on the (possibly huge) tree to be explored (\({\Omega}\left(h\right)\) for backtrack search and \({\Omega}\left(n/p\right)\) for branch-and-bound).
Picosecond-petawatt laser-block ignition for avalanche fusion of boron by ultrahigh acceleration and ultrahigh magnetic fields

Fusion energy from reacting hydrogen (protons) with the boron isotope 11 (HB11) resulting in three stable helium nuclei, is without problem of nuclear radiation in contrast to DT fusion. But the HB11 reaction driven by nanosecond laser pulses with thermal compression and ignition by lasers is extremely difficult. This changed radically when irradiation with picosecond laser pulses produces a non-thermal plasma block ignition with ultrahigh acceleration. This uses the nonlinear (ponderomotive) force to surprizingly resulting in same thresholds as DT fusion even under pessimistic assumption of binary reactions. After evaluation of reactions trapped cylindrically by kilotesla magnetic fields and using the measured highly increased HB11 fusion gains for the proof of an avalanche of the three alphas in secondary reactions, possibilities for an absolutely clean energy source at comptitive costs were concluded.
The role of actin in the temperature-dependent gelation and contraction of extracts of Acanthamoeba

The temperature-dependent assembly and the interaction of Acanthamoeba contractile proteins have been studied in a crude extract. A cold extract of soluble proteins from Acanthamoeba castellanii is prepared by homogenizing the cells in a sucrose-ATP-ethyleneglycol-bis-(beta- aminoethyl ether) N,N'-tetraacetic acid buffer and centrifuging at 136,000 g for 1 h. When this supernate of soluble proteins is warmed to room temperature, it forms a solid gel. Upon standing at room temperature, the gel slowly contracts and squeezes out soluble components. The rates of gelation and contraction are both highly temperature dependent, with activation energies of about 20 kcal per mol. Gel formation is dependent upon the presence of ATP and Mg++. Low concentrations of Ca++ accelerate the contractile phase of this phenomenon. The major protein component of the gel is actin. It is associated with myosin, cofactor, a high molecular weight protein tentatively identfied as actin-binding protein, and several other unidentified proteins. Actin has been purified from these gels and was found to be capable of forming a solid gel when polymerized in the presence of ATP, MgCl3, and KCL. The rate of purified actin polymerication is very temperature dependent and is accelerated by the addition of fragments of muscle actin filaments. These data suggest that Acanthamoeba contractile proteins have a dual role in the cell; they may generate the forces for cellular movements and also act as cytoskeletal elements by controlling the consistency of the cytoplasm.
Social Status and Social Influence: Process Considerations

Process data from an investigation of the relationship between relative social status and interpersonal influence in small group interactions support and refine conclusions derived in an earlier report employing aggregate analyses. A simple process model is presented and data evaluated in light of expected results generated by the model. Discrepancies between expected and attained results are discussed, and interpretations provided for further experimental evaluation. A reward-cost or exchange paradigm is proposed as a necessary theoretical addition for adequate understanding of status-influence relationships.
Retinoic Acid Induces Embryonic Stem Cell Differentiation by Altering Both Encoding RNA and microRNA Expression

Retinoic acid (RA) is a vitamin A metabolite that is essential for early embryonic development and promotes stem cell neural lineage specification; however, little is known regarding the impact of RA on mRNA transcription and microRNA levels on embryonic stem cell differentiation. Here, we present mRNA microarray and microRNA high-output sequencing to clarify how RA regulates gene expression. Using mRNA microarray analysis, we showed that RA repressed pluripotency-associated genes while activating ectoderm markers in mouse embryonic stem cells (mESCs). Moreover, RA modulated the DNA methylation of mESCs by altering the expression of epigenetic-associated genes such as Dnmt3b and Dnmt3l. Furthermore, H3K4me2, a pluripotent histone modification, was repressed by RA stimulation. From microRNA sequence data, we identified two downregulated microRNAs, namely, miR-200b and miR-200c, which regulated the pluripotency of stem cells. We found that miR-200b or miR-200c deficiency suppressed the expression of pluripotent genes, including Oct4 and Nanog, and activated the expression of the ectodermal marker gene Nestin. These results demonstrate that retinoid induces mESCs to differentiate by regulating miR-200b/200c. Our findings provide the landscapes of mRNA and microRNA gene networks and indicate the crucial role of miR-200b/200c in the RA-induced differentiation of mESCs.
Invariant Face Recognitionin a Network of Cortical Columns

We describe a neural network for invariant object recognition. The network is generative in the sense that it explicitly represents both the recognized object and the extrinsic properties to which it is invariant (especially object position). The model is biologically plausible, being formulated as a neuronal system composed of cortical columns. At the same time it has competitive face recognition performance.
Near-Optimal Online Algorithms for Dynamic Resource Allocation Problems

In this paper, we study a general online linear programming problem whose formulation encompasses many practical dynamic resource allocation problems, including internet advertising display applications, revenue management, various routing, packing, and auction problems. We propose a model, which under mild assumptions, allows us to design near-optimal learning-based online algorithms that do not require the a priori knowledge about the total number of online requests to come, a first of its kind. We then consider two variants of the problem that relax the initial assumptions imposed on the proposed model.