Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the mapping problem in multi-mode models

Multi-mode models have proposed dividing the realm of cognitive processes into two forms of categorization in daily life and science, the number and nature of the categories one chooses is context-dependent. Examples of categories of cognitive processes are heuristic and systematic; automatic and nonautomatic; associative and rule-based; sensory, analog, and conceptual; and neocortical and subcortical. It is perfectly legitimate to construe categories on the basis of one or another criterion. Most multi-mode models, however, take things one step further. They choose two or more criteria and make a priori assumptions of overlap among the categories obtained with these criteria. For example, the category of associative is often mapped onto the category of automatic and the category of rule-based onto the category of nonautomatic (e.g., E. R. Smith & DeCoster, 2000). For another example, associative processes are often said to operate on analog or perceptual codes and rule-based processes on conceptual codes (e.g., Leventhal & Scherer, 1987). For a final example, heuristic information (e.g., attractiveness of the speaker) is said to exert an automatic influence on decision making and systematic information (e.g., persuasive arguments of the speaker) a nonautomatic influence (e.g., Chaiken, Liberman, & Eagly, 1989). The question one may ask is whether the mappings of categories obtained with different dividing lines are justified. I propose to investigate the mapping problem in a step-wise manner. A first step is to engage in the conceptual analysis of a pair of criteria and see whether they can be defined in non-overlapping terms. If it turns out that theoretical overlap is not mandatory, a second step is to 2 investigate whether there is actual overlap among both categories in the real world. In the present paper I concentrate on the mapping of associative onto automatic and rule-based onto nonautomatic processing, and investigate it in the step-wise manner described above. Step 1 Definitions of concepts often involve an element of choice. My choice will be explicitly guided by the desire to avoid overlap among criteria. The main argument for this is that when criteria are kept apart theoretically, more options are created for empirical research. For example, when the criteria of automatic vs. nonautomatic and associative vs. rule-based are defined independently, four combinations are open to investigation: associative and automatic, associative and nonautomatic, rule-based and automatic, and rule-based and nonautomatic. When, by contrast, automatic processes are defined as associative ones, and rule-based processes are defined …
A Unified Framework for Augmented Reality and Knowledge-Based Systems in Maintaining Aircraft

Aircraft maintenance and training play one of the most important roles in ensuring flight safety. The maintenance process usually involves massive numbers of components and substantial procedural knowledge of maintenance procedures. Maintenance tasks require technicians to follow rigorous procedures to prevent operational errors in the maintenance process. In addition, the maintenance time is a cost-sensitive issue for airlines. This paper proposes intelligent augmented reality (IAR) system to minimize operation errors and time-related costs and help aircraft technicians cope with complex tasks by using an intuitive UI/UX interface for their maintenance tasks. The IAR system is composed mainly of three major modules: 1) the AR module 2) the knowledge-based system (KBS) module 3) a unified platform with an integrated UI/UX module between the AR and KBS modules. The AR module addresses vision-based tracking, annotation, and recognition. The KBS module deals with ontology-based resources and context management. Overall testing of the IAR system is conducted at Korea Air Lines (KAL) hangars. Tasks involving the removal and installation of pitch trimmers in landing gear are selected for benchmarking purposes, and according to the results, the proposed IAR system can help technicians to be more effective and accurate in performing their maintenance tasks.
Software for Creating Tutorials and Examinations on Natural Languages

Currently, philologists often use various software in studying and testing foreign languages. This work presents the software for creating tutorials and exams by philologists independently from software developers. To cover various features of natural languages and involve more abilities of users, such tutorials and exams contain randomly generated tasks of different types. Both questions and answers of the tasks can be text, graphic, sound, or combined. This software implements the algorithmic programming language for creating randomly generated (parameterized) tasks. The paper describes the objects, the syntax, and the procedure for generating random tasks in this programming language. The developed software is tested and used in secondary and higher educational institutions.
Assessing the Effects of Recombination with the Graph Colouring Problem

It is widely acknowledged that some of the most powerful algorithms for graph colouring involve the combination of evolutionary-based methods with exploitative local search-based techniques. This chapter conducts a review and discussion of such methods, principally focussing on the role that recombination plays in this process. In particular we observe that, while in some cases recombination seems to be usefully combining substructures inherited from parents, in other cases it is merely acting as a macro perturbation operator, helping to reinvigorate the search from time to time.
Soft Budget Constraint, Debt Financing and Investment

This paper analyses the impact of debt on corporate investment under the framework of duplicate soft budget constraint among the government, banks and firms in China. I find that in the corporate with low growth opportunity and high CFO, it shows significantly negative relationship between debt and investment in non-state-owned company. But in state-owned company it doesn’t. There is a significantly negative relationship between short-term debt and investment in non-state-owned corporate. It shows negative relationship between bank loan and investment to non-state-owned corporate. In the corporate with high growth opportunity and low CFO, there is a significantly negative relationship between debt and investment in all corporate, There is a significantly negative relationship between short-term debt and investment in non-state-owned corporate, but in absolute state-controlled corporate the relationship becomes positive. It shows positive relationship between bank loan and investment to non-state-owned corporate.
Identifying Discriminating Network Motifs in YouTube Spam

Like other social media websites, YouTube is not immune from the attention of spammers. In particular, evidence can be found of attempts to attract users to malicious thirdparty websites. As this type of spam is often associated with orchestrated campaigns, it has a discernible network signature, based on networks derived from comments posted by users to videos. In this paper, we examine examples of different YouTube spam campaigns of this nature, and use a feature selection process to identify network motifs that are characteristic of the corresponding campaign strategies. We demonstrate how these discriminating motifs can be used as part of a network motif proling process that tracks the activity of spam user accounts over time, enabling the process to scale to larger networks.
Gesture Recognition and Generation for HOAP-2 Robots by Fuzzy Inference System

Since HOAP series robots resemble human body structure, a HOAP robot is expected to interact with others in real-time. However, it has proven hard in terms of learning, recognition, and interaction in real-time. In this paper a Fuzzy Inference System (FIS) is proposed, which learns gestures with segmentation and motion primitives, recognize gestures with created rule-based system in learning phase, and generate interactive gesture for HOAP-2 robot using real-world human interaction patterns. We also have a pre-processing element during gesture learning, which helps in better fuzzy rule generation and recognition with motion recognizer. Finally, at interactive gesture generation phase, some interactive parameters are incorporated to generate best possible response. We demonstrate the validity of proposed model with several interactive gestures of HOAP-2 robot in real-time.
One-bit stochastic resonance storage device

The increasing capacity of modern computers, driven by Moore's Law, is accompanied by smaller noise margins and higher error rates. In this paper we propose a memory device, consisting of a ring of two identical overdamped bistable forward-coupled oscillators, which may serve as a building block in a larger scale solution to this problem. We show that such a system is capable of storing one bit and its performance improves with the addition of noise. The proposed device can be regarded as asynchronous, in the sense that stored information can be retrieved at any time and, after a certain synchronization time, the probability of erroneous retrieval does not depend on the interrogated oscillator. We characterize memory persistence time and show it to be maximized for the same noise range that both minimizes the probability of error and ensures synchronization. We also present experimental results for a hard-wired version of the proposed memory, consisting of a loop of two Schmitt triggers. We show that this device is capable of storing one bit and does so more efficiently in the presence of noise.
Neural Specificity for Grammatical Operations is Revealed by Content-Independent fMR Adaptation

The ability to generate novel sentences depends on cognitive operations that specify the syntactic function of nouns, verbs, and other words retrieved from the mental lexicon. Although neuropsychological studies suggest that such operations rely on neural circuits distinct from those encoding word form and meaning, it has not been possible to characterize this distinction definitively with neuroimaging. We used functional magnetic resonance imaging (fMRI) to show that a brain area engaged in a given grammatical operation can be identified uniquely by a monotonic decrease in activation as that operation is repeated. We applied this methodology to identify areas involved selectively in the operation of inflection of nouns or verbs. By contrast, areas involved in processing word meaning do not show this monotonic adaptation across stimuli. These results are the first to demonstrate adaptation in the fMR signal evoked not by specific stimuli, but by well-defined cognitive linguistic operations.
Enhanced Energy Efficient Depth Based Routing Protocol for Underwater WSNs

Developing an energy efficient routing protocol for underwater wireless sensor networks (UWSNs) is a challenging task due to long propagation delay, low bandwidth, high error probability, and most importantly limited energy. Unlike ter-restrial sensor networks, UWSN environment is harsh. Nodes are provided with limited energy. The replacement or charging of batteries is not an easy task. By minimizing number of transmissions and considering some time critical applications. We have proposed an enhanced energy efficient depth based routing protocol, EEEDBR, for UWSNs. EEEDBR, selects a forwarding node based on high residual energy, least depth from the sink. In EEEDBR network lifetime is increased by deploying idle nodes in the medium depth region. As, sensor nodes gets die earlier in low or medium depth region due to the additional relaying of data packets. Moreover, In our proposed scheme nodes can vary their transmission range up to a certain limit in order to find a suitable forwarding node.
Gender and Race Sorting at the Application Interface

We document gender and race sorting of candidates into various jobs at the point of initial application to a company. At this step of the hiring process, the firm has implemented a policy whereby organizational screeners’ discretion has been eliminated such that there is no opportunity for contact between hiring agents and applicants. Thus, the job choices studied here offer unique insight as they are uncontaminated by screeners’ steering of candidates toward genderor race-typed jobs. Even in the absence of steering, we find clear patterns of gendered job choices that line up with gender stereotypes of job roles. Moreover, these gendered patterns recur both within individuals and within race groups. Comparing our findings to the pattern of job sorting in the external local labor market, we find that supply-side factors do not fully account for the levels of race and gender segregation observed in the open labor market. Although probably not the entire story, it is clear that supply-side gender sorting processes cannot be ruled out as important factors contributing to job sex segregation. Much recent scholarship has been devoted to documenting the patterns and trends of gender and race job segregation (Charles and Grusky 2004; Jacobs 1989; McCall 2001; Tomaskovic-Devey 1993). This attention is justified because gender and race segregation of jobs has important consequences for inequality in wages. Many studies have shown that men earn more than women, and that whites earn more than minorities, even after controlling for human capital factors. These wage differences, however, are significantly diminished once men and women, or whites and minorities, doing the same job are compared (e.g., England et al. 1994; Petersen and Morgan 1995; Tomaskovic-Devey 1993). As a consequence, understanding the mechanisms that lead to gender and race differences in job assignment has become a top priority in current labor market research. A key debate in the research on job segregation has been the degree to which gender and race sorting is attributable to demand side factors—e.g., employers’ actions and attitudes (e.g., Fernandez and Sosa 2005; Graves 1999; Kaufman 2002; Kmec 2005; Moss and Tilly 2001; Mun 2010)—or reflects a feature of labor supply, e.g., the skills and preferences of individual job seekers (England 1982; Grodsky and Pager 2001; Neal and Johnson 1996; O'Neill 1990; Okamoto and England 1999; Polachek 1981; Tam 1997). This issue is of substantial practical importance, since the idea that demographic groups differ in their degree of interest in jobs has emerged as an employer’s legal defense against charges of discrimination (Nelson and Bridges 1999; see the discussion of the controversial "lack of interest" defense in Schultz and Peterson
Notice of RetractionStudy of the relationship between IPO market timing and capital structure of Real Estate companies Econometric evidence from the Panel Data of Hong Kong Main Board Stock Market

Based on the observations of IPO Panel Data of listed firms in Hong Kong Main Board Stock Market during the year of 1992 to 2009, the paper tests the influence of IPO market timing of real estate companies to the capital structure. In this paper, the market timing index is measured by market-to-book ratio and we choose the non-debt tax shields, company growth, company size and the liquidity of assets as control variables. The study finds that market timing does not have a short run impact on the capital structure of real estate companies of Hong Kong Main Board stock market, but there is a weak negative correlation between the historical evaluation and the capital structure of a firm. With every unit the historical evaluation of a firm goes up, the book leverage would go down for 0.02 units. Further investigation shows that the influence of market timing to listed firms in the Main Board Stock Market of Hong Kong last for 2 year, and disappear in the third year of IPO.
Estudo da viabilidade do desenvolvimento de sistemas integrados baseados em redes em chip sem processadores: sistema IPNoSys

O aumento na capacidade de integracao de transistores permitiu o desenvolvimento de sistemas completos, com inumeros componentes, dentro de um unico chip, sao os chamados SoCs (System-on-Chip). No entanto, o subsistema de interconexao utilizado pode limitar a escalabilidade dos SoCs, como os barramentos, ou ser uma solucao ad hoc, como a hierarquia de barramentos. Desse modo, a solucao ideal para interconexao no SoCs sao as redes em chip ou NoCs (Network-on-Chip). As NoCs permitem multiplas conexao ponto-a-ponto entre os componente e podem ser reusadas em projetos diversos. Entretanto, o uso de NoCs pode representar o aumento na complexidade do projeto do sistema, da area em chip e/ou potencia dissipada. Dessa forma, e necessario ampliar o horizonte de utilizacao dos sistemas ou quebrar o paradigma do seu desenvolvimento. Assim, e proposto um sistema baseado em uma NoC, onde as aplicacoes sao descritas em forma de pacotes e executadas de roteador em roteador durante o percurso entre origem e destino dos pacotes, sem a necessidade do uso de processadores convencionais. Para permitir a execucao de aplicacoes, independente do numero de instrucoes e das dimensoes da rede, foi desenvolvido o algoritmo spiral complement, que permite re-rotear pacotes ate que todas as instrucoes contidas nele sejam executadas. Portanto, o objetivo desse trabalho foi estudar a viabilidade do desenvolvimento de tal sistema, denominado sistema IPNoSys. Nesse estudo, foi desenvolvida em SystemC, com precisao de ciclo, uma ferramenta para simulacao do sistema, a qual permite executar aplicacoes implementadas na linguagem de descricao de pacotes, tambem desenvolvida para esse fim. Atraves da ferramenta podem ser obtidos diversos resultados que permitem avaliar o funcionamento e desempenho do sistema. A metodologia empregada para descricao das aplicacoes corresponde, a priori, em obter o grafo de fluxo de dados da aplicacao em alto nivel, e desse grafo descreve-la em um ou mais pacotes. Utilizando essa metodologia, foram realizados tres estudos de casos: contador, DCT-2D e adicao de ponto flutuante. O contador foi usado para avaliar a capacidade do sistema em tratar situacoes de deadlock e executar aplicacoes em paralelo. A DCT-2D foi utilizada para realizar comparacoes com a plataforma STORM. E, finalmente, a adicao de ponto flutuante teve como objetivo ser usada como rotina de tratamento de uma instrucao nao implementada em hardware. Os resultados de simulacao apontam favoravelmente com relacao a viabilidade do desenvolvimento do sistema IPNoSys. Mostrando que e possivel executar aplicacoes em forma de pacotes, inclusive paralelamente, sem interrupcoes provocadas por eventuais deadlocks, e ainda indicam maior eficiencia do sistema IPNoSys a respeito do tempo de execucao comparada a plataforma STORM
Dynamic Reconfiguration Planning with Influence Control

The automated way of dynamic reconfiguration has many advantages comparing with the manual way. But the existing approaches to automated dynamic reconfiguration are not integrated with the methods for influence control. In this paper, we propose an approach to dynamic reconfiguration planning with build-in influence control. A reconfigurable data flow model is designed as the underlying model. Given a specification of the source configuration and the target configuration, a reconfiguration plan can be automatically generated by a planning algorithm. In the plan, new components are started before the removal of the original components in order to theoretically avoid any interruption to the system services. A version control mechanism is used to support the coexistence of original versioned transactions and new versioned transactions without interference. A flow tracing method is used to ensure the transaction completeness.
Image segmentation based on fuzzy flood fill mean shift algorihm

In this paper, the fuzzy flood fill mean shift algorithm is introduced. This algorithm is developed for the methodology of robust segmentation by improving the mean shift algorithm through the fuzzy kernels and the flood fill technique, instead of those based on the spatial bandwidth. Due to this exchange, the flood fill mean shift involves only one parameter, the range bandwidth, which is less sensitive and is able to acquire the global characteristics. If the image parts affected by the illumination changes are sufficiently small and their boundaries are not clear, the illumination effects do not have an influence on the mode seeking procedure of the proposed fuzzy flood fill mean shift. To prove the usefulness and the validity of our algorithm, we present several experiments and analysis of the results.
Selective wordline voltage boosting for caches to manage yield under process variations

One of the most important hurdles of technology scaling is process variations, i.e., variations in device characteristics. Process variations cause large fluctuations in performance and power consumption in the manufactured chips. In addition, these fluctuations cause reductions in the chip yields. In this work, we present an analysis of a representative high-performance processor architecture and show that the caches have the highest probability of causing yield losses under process variations. We then propose a novel selective wordline voltage boosting mechanism that aims at reducing the latency of the cache lines that are affected by process variations. We show that our approach can eliminate over 80% of the yield losses under medium level of variations, while incurring less than 1% per-access energy overhead on average and less than 4.5% area overhead.
Trial-Based Dynamic Programming for Multi-Agent Planning

Trial-based approaches offer an efficient way to solve single-agent MDPs and POMDPs. These approaches allow agents to focus their computations on regions of the environment they encounter during the trials, leading to significant computational savings. We present a novel trial-based dynamic programming (TBDP) algorithm for DEC-POMDPs that extends these benefits to multi-agent settings. The algorithm uses trial-based methods for both belief generation and policy evaluation. Policy improvement is implemented efficiently using linear programming and a sub-policy reuse technique that helps bound the amount of memory. The results show that TBDP can produce significant value improvements and is much faster than the best existing planning algorithms.
Detection of Hazardous Weather Phenomena Using Data Assimilation Techniques.

Currently, the most widely used paradigm for the automated detection of tornadoes and other hazardous weather events involves identifying patterns in Doppler radar reflectivity and velocity data. The patterns include gate-to-gate shear, strong convergence oriented in lines, descending areas of high reflectivity, etc. The Warning Decision Support System-Integrated Information (WDSS-II), a highly developed detection suite by the National Severe Storms Laboratory, uses this general methodology, incorporating near storm environment analyses for hail detection, satellite data for clutter suppression, and a variety of other advanced tools. The major limitation of tools such as WDSS-II, however, is that new detection algorithms must be created, or existing ones adapted, each time a new observation system is deployed (e.g., TDWR). Further, they operate principally on data directly measured by the sensor (e.g., radial velocity and reflectivity) and thus cannot make use of fine-scale fields that are potentially available (e.g., pressure deviation and temperature fields within the storms). Finally, such systems are limited in their ability to synthesize data from other observing platforms in a dynamically consistent manner.