Miracle-dz/UniFAR-FTUs huggingface dataset:
Negotiating intercultural experience through English as a foreign language in South Korea

ABSTRACT The ‘intercultural turn’ in foreign language education has brought to the fore the need to foster intercultural competences. Yet in contexts where virtually all intercultural communication is mediated by English as a foreign language (hereafter EFL), proficiency in that language determines to a large extent access to intercultural experiences, including coveted opportunities for international work and study. Such high stakes mean that acquiring competence in the language can be an emotionally charged process, and using it an emotionally salient feature of intercultural encounters. This paper draws upon an interview-based study of South Koreans’ ideologies of the intercultural to explore the complex emotions associated with using EFL in intercultural experiences. La ‘svolta interculturale’ nell'insegnamento delle lingue straniere ha messo in evidenza la necessità di promuovere le competenze interculturalie, nel processo, ha minimizzato il processo emotivo di acquisizione delle competenze in una lingua straniera. Tuttavia, in contesti in cui praticamente tutte le comunicazioni interculturali sono mediate dall'inglese, la capacità di parlare la lingua determina l'accesso a opportunità prestigiose per il lavoro e lo studio in contesti internazionali. Questo articolo è basato su una serie di interviste con dei soggetti sudcoreani dove si esplora come loro utilizzano delle complesse emozioni e ideologie interculturali associate all'uso dell'inglese come lingua straniera, per costruire l'esperienza interculturale.
Dynamic intrahousehold bargaining, matrimonial property law and suicide in Canada

This paper develops a dynamic model of household bargaining and uses it to motivate an empirical analysis of the impact changes in Canadian laws regarding the allocation of family assets upon divorce on female suicide. Using time series data, we show that in Ontario, the passage of Canadian legislation that improved women's rights to assets upon divorce was associated with reductions in the rate of female suicide amongst older (married) women while not affecting younger (unmarried) women. As suggested by our model, its impact was asymmetric in that male suicide rates were unaffected by this change. We also exploited a quasi-natural experiment in these data, namely that no comparable legislative change occurred in Quebec. Here, we do not observe a structural break in the data.
Direction-Preserving Trajectory Simplification

Trajectories of moving objects are collected in many applications. Raw trajectory data is typically very large, and has to be simplified before use. In this paper, we introduce the notion of direction-preserving trajectory simplification, and show both analytically and empirically that it can support a broader range of applications than traditional position-preserving trajectory simplification. We present a polynomial-time algorithm for optimal direction-preserving simplification, and another approximate algorithm with a quality guarantee. Extensive experimental evaluation with real trajectory data shows the benefit of the new techniques.
Tag Ranking by Linear Relational Neighbourhood Propagation

We propose a tag recommendation method which can assist users in tagging process by suggesting relevant tags. The method is based on query-based ranking on relational multi-type graphs which capture the annotation relationship between objects and tags, as well as the object similarity and tag correlation. The additional advance consists in extending the linear neighbourhood propagation to the relational graphs with the Laplacian regularization framework. We report evaluation results on a large-scale Flickr data set.
Pareto-Optimal Cloud Bursting

Large-scale Bag-of-Tasks (BoT) applications are characterized by their massively parallel, yet independent operations. The use of resources in public clouds to dynamically expand the capacity of a private computer system might be an appealing alternative to cope with such massive parallelism. To fully realize the benefit of this `cloud bursting', the performance to cost ratio (or cost efficiency) must be thoroughly studied and incorporated into scheduling and resource allocation strategies. In this paper, we present PANDA, a framework for static scheduling BoT applications across resources in both private and public clouds. The framework at the core incorporates a fully polynomial-time approximation scheme (FPTAS) as a novel scheduling algorithm, which generates schedules with the best trade-off point between cost and performance; hence Pareto-optimality. We have theoretically discussed the complexity and correctness of our algorithms, and experimentally verified their efficacy and practicality using ISOMAP-a widely-used nonlinear manifold method as a real-world BoT application. Our evaluation conducted in a 'multi-cloud' environment of our 40-core private system and Amazon EC2 public cloud demonstrates the scheduling quality of PANDA is guaranteed to be within a measurable distance from the optimal solution. Results obtained from our experiments show such quality is 8 percent or less from the optimum. We also show the sensitivity and robustness of our scheduling solutions against performance errors in both resources and applications.
URBAN SPATIAL STRUCTURE.

An interview with Chicago's current mayor, Richard M. Daley: 'New York is too big this way,' the mayor says, raising a thick hand over his head. Stretching both arms out at his sides, he adds, 'Los Angeles is too big this way. All the other cities are too small. We're just right. ' (Bailey and Coleman, 1996, p. 6) Mayor Daley is catering to a widespread fascination with the roles that urban size and structure play in people's lives. Academic as well as other observers have long sought explanations for urban development patterns and criteria by which to judge their desirability. Furthermore, as we shall see, understanding the organization of cities yields insights about economy-wide growth processes and sheds light on economic concepts of long standing interest: returns to scale, monopolistic competition, vertical integration, technological innovation, innovation diffusion, and international specialization. Cities also are prime illustrations of some newer academic interests such as complex structural evolution and self-organization.
The minimum principle for hybrid systems with partitioned state space and unspecified discrete state sequence

The hybrid minimum principle (HMP) gives necessary conditions to be satisfied for optimal solutions of a hybrid dynamical system. In particular, the HMP accounts for autonomous switching between discrete states that occurs whenever the trajectory hits switching manifolds. In this paper, the existing HMP is extended for hybrid systems with partitioned state space to provide necessary conditions for optimal trajectories that pass through an intersection of switching manifolds. This extension is especially useful for the numerical solution of hybrid optimal control problems as it allows for algorithms with significant reduction of computational complexity. Algorithms based on previous versions of the HMP solve separate optimal control problems for each possible sequence of discrete states. The extension enables us to consider the optimal sequence as subject of optimal control that is varied and finally determined during a single optimization run. A first numerical result illustrates the effectiveness of an algorithm based on the extended HMP.
Compressed feature-based filtering and verification approach for subgraph search

Subgraph search in graph datasets is an important problem with numerous applications. Many feature-based indexing methods have been proposed for solving this problem. These methods have to index too many features or select some of them in order to get an index with good pruning capabilities. None of these directions can give an effective solution to all graph indexing issues. In this paper, we propose an efficient indexing approach which improves over current feature-based methods, neither by the costly feature selection nor by explicitly indexing a multitude of features. We achieve this by compressing multiple features into one feature with some neighborhood information encoded. Neighborhood is further used to prune unmatched feature occurrences between the query and data graphs, thus cutting down the search space of subgraph matching, which significantly reduce the verification cost. We implement the approach by exhaustively enumerating small paths as features. A novel path-at-a-time verification method that benefits from the occurrences pruning method is introduced. Via an extensive evaluation on both real and synthetic datasets, we show that our approach is effective and scalable, and outperforms state-of-the-art indexing methods.
SECURE IMAGE PROCESSING

OF THESIS SECURE IMAGE PROCESSING In todays heterogeneous network environment, there is a growing demand for distrusted parties to jointly execute distributed algorithms on private data whose secrecy needed to be safeguarded. Platforms that support such computation on image processing purposes are called secure image processing protocols. In this thesis, we propose a new security model, called quasi information theoretic (QIT) security. Under the proposed model efficient protocols on two basic image processing algorithms – linear filtering and thresholding – are developed. For both problems we consider two situations: 1) only two parties are involved where one holds the data and the other possesses the processing algorithm; 2) an additional non-colluding third party exists. Experiments show that our proposed protocols improved the computational time significantly compared with the classical cryptographical couterparts as well as providing reasonable amount of security as proved in the thesis.
An implementation of a verification condition generator for foundational proof-carrying code

Proof-carrying code (PCC) is a technique that addresses the problem of mobile code safety. It is a mechanism in which a code producer provides both code and a proof certifying that the code will run safely on a code consumer's machine. The code consumer or the host system will validate the proof against a safety policy before executing the source code. Foundational proof-carrying code (FPCC) aims to minimize the amount of code that must be trusted (the “trusted computing base” or TCB) with the goal of providing more flexibility and increased security. In both PCC and FPCC, the verification-condition generator (VCG) constructs the statement of the safety theorem from the source code, and is an important part of the TCB. This paper presents an implementation of a VCG based on a sound set of Hoare-style rules for machine instructions in the context of FPCC. The implementation in OCaml is described and examples illustrating the approach are given. The output of our VCG is a list of verification conditions that are directly inserted into a proof script that serves as input to the Coq proof assistant, and represents an important part of the safety proofs of our programs. We also present examples showing how these verification conditions are used to complete the proofs of safety. This work represents an important step in automating proofs for PCC.
A Fast and Accurate Amplitude-Only Transmission-Reflection Method for Complex Permittivity Determination of Lossy Materials

Complex scattering parameter measurements using expensive vector network analyzers make microwave techniques inconvenient for industrial-based applications. In industry, accurate and fast evaluation of materials' properties using a relatively inexpensive measurement setup is a key issue. In this paper, we derive an objective function for fast and accurate complex permittivity (epsiv) determination of lossy materials using amplitude-only reflection and transmission scattering parameter measurements. The measurements can be carried out by relatively inexpensive microwave instruments such as a scalar network analyzer. The domain for computations of the epsiv is significantly reduced to facilitate rapid epsiv determination. The objective function is verified by measurements of a commercially available antifreeze solution and binary mixture of ethyl alcohol and water solution.
Accelerating linpack with CUDA on heterogenous clusters

This paper describes the use of CUDA to accelerate the Linpack benchmark on heterogenous clusters, where both CPUs and GPUs are used in synergy with minor or no modifications to the original source code. A host library intercepts the calls to DGEMM and DTRSM and executes them simultaneously on both GPUs and CPU cores. An 8U cluster is able to sustain more than a Teraflop using a CUDA accelerated version of HPL.
Weighted anytime search : new schemes for optimization over graphical models

Weighted search (best-first or depth-first) refers to search with a heuristic function multiplied by a constant w [Pohl (1970)]. The paper shows for the first time that for graphical models optimization queries weighted best-first and weighted depth-first Branch and Bound search schemes are competitive energy-minimization anytime optimization algorithms. Weighted best-first schemes were investigated for path-finding tasks, however, their potential for graphical models was ignored, possibly because of their memory costs and because the alternative depth-first Branch and Bound seemed very appropriate for bounded depth. The weighted depth-first search has not been studied for graphical models. We report on a significant empirical evaluation, demonstrating the potential of both weighted best-first search and weighted depth-first Branch and Bound algorithms as approximation anytime schemes (that have suboptimality bounds) and compare against one of the best depth-first Branch and Bound solvers to date.
Phylogenetic species delimitation for the widespread spider wasp Ageniella accepta (Hymenoptera: Pompilidae), with new synonyms

Ageniella is the second-most diverse spider wasp genus in Ageniellini (Pepsinae). The Ageniella (Ageniella) accepta species-group is found from Canada to Panama and is composed of three Nearctic species: A. accepta (Cresson), A. blaisdelli (Fox), and A. conflicta Banks. Within this group, species-level identification is difficult, because diagnostic characters are questionable, and subjective for both males and females. Furthermore, sexes of each species are not reliably associated. Herein, we investigate sex associations and the validity of described species within the A. accepta species-group based on three molecular markers (cytochrome oxidase I, wingless, long-wavelength rhodopsin) by using maximum likelihood and Bayesian phylogenetic analyses, and species-delimitation approaches. Additionally, we mapped 12 morphological traits onto the molecular phylogeny to discuss evolution of diagnostic characters. We concluded that the three species of the A. accepta species-group are actually a single, wide-ranging species with strong geographical signal. Moreover, our results suggest introgression at the mitochondrial level.
Head-to-Head Comparison of Three Vaccination Strategies Based on DNA and Raw Insect-Derived Recombinant Proteins against Leishmania

Parasitic diseases plague billions of people among the poorest, killing millions annually, and causing additional millions of disability-adjusted life years lost. Leishmaniases affect more than 12 million people, with over 350 million people at risk. There is an urgent need for efficacious and cheap vaccines and treatments against visceral leishmaniasis (VL), its most severe form. Several vaccination strategies have been proposed but to date no head-to-head comparison was undertaken to assess which is the best in a clinical model of the disease. We simultaneously assayed three vaccination strategies against VL in the hamster model, using KMPII, TRYP, LACK, and PAPLE22 vaccine candidate antigens. Four groups of hamsters were immunized using the following approaches: 1) raw extracts of baculovirus-infected Trichoplusia ni larvae expressing individually one of the four recombinant proteins (PROT); 2) naked pVAX1 plasmids carrying the four genes individually (DNA); 3) a heterologous prime-boost (HPB) strategy involving DNA followed by PROT (DNA-PROT); and 4) a Control including empty pVAX1 plasmid followed by raw extract of wild-type baculovirus-infected T. ni larvae. Hamsters were challenged with L. infantum promastigotes and maintained for 20 weeks. While PROT vaccine was not protective, DNA vaccination achieved protection in spleen. Only DNA-PROT vaccination induced significant NO production by macrophages, accompanied by a significant parasitological protection in spleen and blood. Thus, the DNA-PROT strategy elicits strong immune responses and high parasitological protection in the clinical model of VL, better than its corresponding naked DNA or protein versions. Furthermore, we show that naked DNA coupled with raw recombinant proteins produced in insect larvae biofactories –the cheapest way of producing DNA-PROT vaccines– is a practical and cost-effective way for potential “off the shelf” supplying vaccines at very low prices for the protection against leishmaniases, and possibly against other parasitic diseases affecting the poorest of the poor.
Theoretical Studies on Structures, Properties and Dominant Debromination Pathways for Selected Polybrominated Diphenyl Ethers

The B3LYP/6-311+G(d)-SDD method, which considers the relativistic effect of bromine, was adopted for the calculations of the selected polybrominated diphenyl ethers (PBDEs) in the present study, in which the B3LYP/6-311+G(d) method was also applied. The calculated values and experimental data for structural parameters of the selected PBDEs were compared to find the suitable theoretical methods for their structural optimization. The results show that the B3LYP/6-311+G(d) method can give the better results (with the root mean square errors (RMSEs) of 0.0268 for the C–Br bond and 0.0161 for the C–O bond) than the B3LYP/6-311+G(d)-SDD method. Then, the B3LYP/6-311+G(d) method was applied to predict the structures for the other selected PBDEs (both neutral and anionic species). The lowest unoccupied molecular orbital (LUMO) and the electron affinity are of a close relationship. The electron affinities (vertical electron affinity and adiabatic electron affinity) were discussed to study their electron capture abilities. To better estimate the conversion of configuration for PBDEs, the configuration transition states for BDE-5, BDE-22 and BDE-47 were calculated at the B3LYP/ 6-311+G(d) level in both gas phase and solution. The possible debromination pathway for BDE-22 were also studied, which have bromine substituents on two phenyl rings and the bromine on meta-position prefers to depart from the phenyl ring. The reaction profile of the electron-induced reductive debromination for BDE-22 were also shown in order to study its degradation mechanism.
A compact representation of graph databases

Graph databases have emerged as an alternative data model with applications in many complex domains. Typically, the problems to be solved in such domains involve managing and mining huge graphs. The need for efficient processing in such applications has motivated the development of methods for graph compression and indexing. However, most methods aim at an efficient representation and processing of simple graphs (without attributes in nodes or edges, or multiple edges for a given pair of nodes). In this paper we present a model for compact representation of general graph databases. It represents an attractive alternative due to the compression rates it achieves and its efficient navigation operations.
A Network-Flow Based Influence Propagation Model for Social Networks

Due to its popularity, influence propagation model has been recently exploited in several social network applications. However, there are some limitations in applying the model to the social network, in which negative information is propagated. In this paper, we present an effective information propagation model to overcome these limitations. Our minimum cost flow model effectively propagates influences to neighbouring nodes with minimum costs in each path of the social network. The model removes noise associated with social network marketing information and propagates influences without overlapping in information nodes.
WORKTIME AND CREATIVITY – THE MEDIATING ROLE OF PROBLEM STRUCTURING

The relationship between creative processes and problem structuring (PS - selfinterpretation of a problem while solving it) is often overlooked in research. We explored how PS affects the outcome’s creativity in the context of two problem types: open or closed presentation, and novelty or usefulness focus. 48 students and architects completed a preliminary design task. Analyses show how outcomes’ novelty and usefulness are positively affected by PS under certain conditions, and how worktime indirectly affects creativity through PS. The study offers new insights on the worktime-creativity positive relationship; it opens new directions towards a comprehensive understanding of PS and creativity; and it suggests how both PS and creativity may be promoted through proper time allocation.
Load Balancing in P2P Networks: Using Statistics to Fight Data and Execution Skew

In recent years, structured peer-to-peer (P2P) have gained an important role in the design of large-scale distributed systems. However, due to their strict data placement rules, they are often prone to three main load imbalances, i.e., range, data, and execution skew. Many of today’s load balancing algorithms focus only on range skew and assume the network data rate to be the bottleneck. In applications that focus on distributed request processing, those assumptions are not valid as messages are typically small but can produce significant load at the application level. Examples of such applications are complex name resolution mechanisms that, e.g., involve security checks, or multi-dimensional search. Here, data skew and execution skew are most important and the system performance is limited by the number of application requests a peer can process. To provide a solution for such scenarios, we have developed a new load balancing algorithm which is based on ID management. Our algorithm collects statistics of overlay link usage during normal operation and uses this information to provide suitable IDs to joining peers. Without using regular maintenance messages, it improves the rate of successfully answered requests by a factor of up to 3 in typical scenarios. We have evaluated the algorithm via extensive simulation that also includes scenarios with churn and heterogeneous peers. This work presents the first load balancing algorithm that can handle all three types of skew in scenarios that focus on processed application requests as the bottleneck.
The Design of Web Based Car Recommendation System using Hybrid Recommender Algorithm

Web based recommendations for any item is mandatory in E-commerce based web sites. This paper is about the design of web based car recommendation system using the hybrid recommender algorithm. The proposed hybrid recommender algorithm is the combination of user-to-user and item-to-item collaborative filtering method to generate the car recommendations. The user model is designed using demographic features, click data and browsing history. Item profile is built using the various attributes of car, 40 brands of car including 224 car types are used in this work. The synthetic dataset of 300 users with 10000 sessions is used to build user model. The proposed algorithm is evaluated with 100 real time users and shows the 83% accuracy in generating recommendations.