Miracle-dz/UniFAR-FTUs huggingface dataset:
Scale of Positive and Negative Experience (SPANE): Factor Structure and Measurement Invariance Across Gender in Korea

The Scale of Positive and Negative Experience (SPANE) is a newly developed emotional scale to measure well-being that was designed to overcome the limitations of the previous emotional scales (Diener et al., 2010). It comprises 12 items that measure positive and negative emotional experiences, including general (e.g., positive, negative) and specific (e.g., joyful, sad) items. It also reflects all levels of arousal. This study examined the factor structure and gender invariance of the Korean version of the SPANE. For this purpose, responses to the scale of a sample of 551 Korean college students (276 males and 275 females) were analyzed. The results exhibited high internal consistency reliability and construct validity for a Korean population. Furthermore, the configural, metric, and scalar invariance of the SPANE held across gender. These results suggest that the Korean version of the SPANE is a valid scale for measuring the emotional experiences of Korean students, and it is appropriate to use in future studies of gender difference in emotional well-being.
A Multi-Objective Genetic Algorithm to Test Data Generation

Evolutionary testing has successfully applied search based optimization algorithms to the test data generation problem. The existing works use different techniques and fitness functions. However, the used functions consider only one objective, which is, in general, related to the coverage of a testing criterion. But, in practice, there are many factors that can influence the generation of test data, such as memory consumption, execution time, revealed faults, and etc. Considering this fact, this work explores a ultiobjective optimization approach for test data generation. A framework that implements a multi-objective genetic algorithm is described. Two different representations for the population are used, which allows the test of procedural and object-oriented code. Combinations of three objectives are experimentally evaluated: coverage of structural test criteria, ability to reveal faults, and execution time.
Decoupled Shading and Compositing for Volumetric Global Illumination

This document describes a technique we have used in our volumetric global illumination rendering architecture, GI-Cube, to s upport deferred shading and compositing. This portion of the architecture has been superceded by a newer algorithm which is more appropriate for rendering a single volume. However, we feel that this algorithm is important for use in other contexts, particularly a more flexible volume rendering and processing engine such as contemplated in Cube-5. In volumetric global illumination, shadow rays are commonly used to determine light source visibility in order to generate shadows. These shadow rays are generated at every visible (nontransparent) sample along the ray until the ray reaches full opacity. In a straightforward software rendering system, shadow rays (see Figure 1) are computed fully before computation proceeds. In GI-Cube, tracing a ray is achieved by data parallel rendering on distributed processing elements. For that reason, it is difficult to complete processing of all the shadow rays before proceeding along the ray, as this would create a stall condition. Therefore, we needed to find a way to defer the shadowing computation until the shadow rays have completed without sta lling the primary ray.
SKETURE: A Sketch-based Packet Analysis Tool

In this study we introduce SKETURE, a packet analysis tool leveraging a sketch-based architecture. SKETURE generates statistical summaries that describe the behavior of each node in a network without violating users' privacy. It also extracts information from each packet it processes instead of sampling packets avoiding thus the risk to lose valuable information. We argue that statistical sketches are better suited than signatures to detect insider threats as they can capture any anomalous behavior.
Complexes of HLA-G Protein on the Cell Surface Are Important for Leukocyte Ig-Like Receptor-1 Function1

The nonclassical class I MHC molecule HLA-G is selectively expressed on extravillous cytotrophoblast cells at the maternal-fetal interface during pregnancy. HLA-G can inhibit the killing mediated by NK cells via interaction with the inhibitory NK cell receptor, leukocyte Ig-like receptor-1 (LIR-1). Comparison of the sequence of the HLA-G molecule to other class I MHC proteins revealed two unique cysteine residues located in positions 42 and 147. Mutating these cysteine residues resulted in a dramatic decrease in LIR-1 Ig binding. Accordingly, the mutated HLA-G transfectants were less effective in the inhibition of NK killing and RBL/LIR-1 induced serotonin release. Immunoprecipitation experiments demonstrated the involvement of the cysteine residues in the formation of HLA-G protein oligomers on the cell surface. The cysteine residue located at position 42 is shown to be critical for the expression of such complexes. These oligomers, unique among the class I MHC proteins, probably bind to LIR-1 with increased avidity, resulting in an enhanced inhibitory function of LIR-1 and an impaired killing function of NK cells.
Chronic Traumatic Encephalopathy: The Impact on Athletes

Chronic traumatic encephalopathy (CTE) is a devastating neuropsychological condition afflicting a small percentage of athletes partaking in high-impact sports. The onset of symptoms lags years behind the inciting events. Repetitive minor head injuries are felt to be the main etiology behind CTE. Routine radiographic imaging generally is unremarkable in cases of CTE. Functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), and diffusion tensor imaging (DTI) are advanced MRI-based sequences that have shown promise in detecting early radiographic findings that may be reflective of CTE. Progressive neuronal loss is the histopathological hallmark of this neurodegenerative disease. Strategizing earlier detection techniques is paramount in delivering optimal care to athletes afflicted with CTE.
Reconfigurable pipelined 2-D convolvers for fast digital signal processing

In order to make software applications simpler to write and easier to maintain, a software digital signal-processing library that performs essential signal- and image-processing functions is an important part of every digital signal processor (DSP) developer's toolset. In general, such a library provides high-level interface and mechanisms, therefore, developers only need to know how to use algorithms, not the details of how they work. Complex signal transformations then become function calls, e.g., C-callable functions. Considering the two-dimensional (2-D) convolver function as an example of great significance for DSP's, this paper proposes to replace this software function by an emulation on a field-programmable gate array (FPGA) initially configured by software programming. Therefore, the exploration of the 2-D convolver's design space will provide guidelines for the development of a library of DSP-oriented hardware configurations intended to significantly speed up the performance of general DSP processors. Based on the specific convolver, and considering operators supported in the library as hardware accelerators, a series of tradeoffs for efficiently exploiting the bandwidth between the general-purpose DSP and accelerators are proposed. In terms of implementation, this paper explores the performance and architectural tradeoffs involved in the design of an FPGA-based 2-D convolution coprocessor for the TMS320C40 DSP microprocessor available from Texas Instruments Incorporated. However, the proposed concept is not limited to a particular processor.
Probabilistic N-gram language model for SMS Lingo

This paper presents a pioneering step in designing Bi-Gram based decoder for SMS Lingo. In the last few years, a significant increment in both the computational power and storage capacity of computers, and the availability of large volumes of bilingual data, have made possible for Statistical Machine Translation (SMT) to become an actual and practical technology. This paper employs Bi-Gram Language Model (LM) with a SMT decoder through which a sentence written with short forms in an SMS is translated into long form sentence. Here the results over a development and test set are analyzed and commented. The main objective behind this project is to analyze the improvement in efficiency as the size of bilingual corpus increases.
Object Detection Using a Cascade of Classifiers

Typical object detection systems work by training a classifier on features extracted at different scales of an object. In this paper we investigate the performance of an object detection system in which different classifiers which are trained at various scales of an object are combined and compare the performance with a typical object detection system where a single classifier is trained for all the scales. The notion behind such an approach is that the features extracted over smaller scales give more objectpsilas specific information whereas large scale features provide more contextual information. We trained different classifiers for different scales and combined their output to reach a decision about the existence of an object. Confidence rated Ada-boost is used to train the classifiers. It was found that training a single classifier for all the scales results in superior performance as compared to training different classifiers for each scale and than combining their results. We show our results on objects belonging to three categories in TUDarmstadt and one category in Caltech4.
Turing Test : Contribution , Criticism and Variations

In 1950, Alan Turing proposed an answer to the question Can (or could) a machine think? by replacing it with a precise question Can (or could) a machine pass a certain type of test? In his imitation game, a person acts as an interrogator and interacts with two interlocutors through text message in computerized connection. Success of the program is achieved when, after allotted time for the test, interrogator cannot differentiate between human and machine interlocutors. Turing claimed that behavioral responses in the test demonstrate a machine indistinguishable from a human being. Since then, debates are going on and research is conducted from different perspectives. This paper is motivated by recent findings and developments of Turing Test which finally reveals its contribution in the area of Artificial Intelligence even with criticisms.
Ultra-Wideband Real-Time Dynamic Channel Characterization and System-Level Modeling for Radio Links in Body Area Networks

Reliable on-body wireless network design needs to incorporate the natural body movements. However, existing models are static or pseudo-dynamic models. In this work, the lack of a comprehensive channel model for a moving body is addressed. A dynamic radio channel around the human body is statistically analyzed and modeled. Important parameters of the channel are estimated from measured data and compared with the model prediction. Simulations show that the model can predict the parameters of a system working in a dynamic body area network with 92% accuracy.
Nitrogen load and forest type determine the soil emission of nitrogen oxides (NO and N 2 O)

Soil emissions of NO and N 2 O were measured continuously at high frequency for more than one year at 15 European forest sites as part of the EU-funded project NOFRETETE. The locations represent different forest types (coniferous/deciduous) and different nitrogen loads. Geographically they range from Finland in the north to Italy in the south and from Hungary in the east to Scotland in the west. The highest NO emissions were observed from coniferous forests, whereas the lowest NO emissions were observed from deciduous forests. The NO emissions from coniferous forests were highly correlated with N-deposition. The site with the highest average annual emission (82 ? g NO-Nm ? 2 h ? 1 ) was a spruce forest in South-Germany (Hoglwald) receiving an annual N-deposition of 2.9 gm ? 2 . NO emissions close to the detection limit were observed from a pine forest in Finland where the N-deposition was 0.2 g N m ? 2 y ? 1 . No significant correlation between N 2 O emission and N-deposition was found. The highest average annual N 2 O emission (20 ? g N 2 O-Nm ? 2 h ? 1 ) was found in an oak forest in the Matra mountains (Hungary) receiving an annual N-deposition of 1.6 gm ? 2 . N 2 O emission was significantly negatively correlated with the C/N ratio. The difference in N-oxide emissions from soils of coniferous and deciduous forests may partly be explained by differences in N-deposition rates and partly by difference in characteristics of the litter layer and soil. NO was mainly derived from nitrification whereas N 2 O was mainly derived from denitrification. In general, soil moisture is lower at coniferous sites (at least during spring time) and the litter layer of coniferous forests is thick and well aerated favouring nitrification and thus release of NO. Conversely, the higher rates of denitrification in deciduous forests due to a compact and moist litter layer lead to N 2 O production and NO consumption in the soil. The two factors soil moisture and soil temperature are often explaining most of the temporal variation within a site. When comparing annual emissions on a regional scale, however, factors such as nitrogen deposition and forest and soil type become much more important.
Discursive institutionalism: understanding policy in context

Discursive institutionalism is an umbrella concept for approaches that concern themselves with the substantive content of ideas and the interactive processes of discourse in institutional context. This chapter shows the relevance of discursive institutionalism to policy studies in a critical vein by considering both the wide range of ideas in discourse and the ways in which “sentient” (thinking and speaking) agents articulate such ideas as policy actors in a “coordinative discourse” of policy construction and as political actors in a “communicative discourse” of political legitimation. The chapter also elaborates on the dual nature of the institutional context by considering not just the external formalized institutions that constrain action but also the structures and constructs of meaning. These help explain not only how agents are able to create and maintain institutions via their “background ideational abilities” but also how they change or maintain institutions via their “foreground discursive abilities” of communication. But although meaning is socially constructed, the chapter builds on the work of Wittgenstein to show that this does not lead to radical relativism because knowledge comes with different kinds of certainty. Finally, it also theorizes about the nature of the power of ideas, in particular through discourse. “Discursive institutionalism” gives a name to the very rich and diverse set of ways of explaining political and social reality that are focused on the substantive content of ideas and the interactive processes of discourse in institutional context. The purpose of this chapter is to offer an account of discursive institutionalism that indicates its relevance to policy studies in a critical vein. The question of how ideas and discourse change in an institutional setting is particularly important in the case of policy ideas, whether they change rapidly in the face of emerging events and opportunities or become institutionalized in policy programs, and whether they become forces resistant to change or form the basis for radical ideational transformation. Discursive 1 Discursive institutionalism represents a fourth ‘new institutionalist’ approach in political science, in contrast to the three older “new institutionalisms”--rational choice, historical, and sociological. Rational choice institutionalism focuses on rational actors who pursue their preferences following a “logic of calculation” within political institutions, defined as structures of incentives. Historical institutionalism details the development of political institutions, described as regularized patterns and routinized practices subject to a “logic of path-dependence. ” Sociological institutionalism concentrates on social agents who act according to a “logic of appropriateness” within political institutions, defined as socially constituted and culturally framed rules and norms. See Schmidt 2010a.
Experimental Research on Personal Awareness and Behavior for Information Security Protection

A virus infection situation can be considered a kind of emergency or disaster. Although such a situation is an area applicable to psychology, there has not yet been any report of specific studies in this field. Furthermore, in the field of information security, even though an individual might intend to take protective action, it is an observable fact that many people do not actually do so. Research on individual behavior and decision making in a virus infection situation is important in developing information security protection. We implemented a virtual game based on collective intelligence to investigate experimentally the awareness that users with infected PCs have of information security. By analyzing the experiment data in combination with questionnaire results, we have investigated why many people do not take appropriate recovery action against virus infection, and also the personal profiles which indicate that people are likely to take such recovery action.
Correlative microscopy for nanomanipulation of sub-cellular structures

Nanomanipulation under scanning electron microscopy (SEM) has been demonstrated as an enabling technique for the manipulation and characterization of nanomaterials. We recently developed nanomanipulation techniques for the extraction and identification of DNA contained within sub-nuclear locations of a single cell nucleus. In nanomanipulation of DNA, a key step is target identification through SEM-fluorescence correlative imaging. Existing image correlation techniques often require fiducial marks and/or manual feature selection or data training, which are unsuitable for DNA nanomanipulation. This paper presents an approach for correlating SEM-fluorescence microscopy images, proven effective in processing images taken under poor SEM imaging conditions imposed by the necessity of preserving DNA's biochemical integrity. The performance of the image correlation approach under different imaging conditions was quantitatively evaluated. Compared to manual correlation by skilled operators, the automated correlation approach demonstrated an order of magnitude higher speed. The SEM-fluorescence correlation approach enables targeted nanomanipulation of sub-cellular structures under SEM.
GENDER AND AGE ESTIMATION BASED ON FACIAL IMAGES

In this paper, a fast and efficient gender and age estimation system based on facial images is developed. There are many methods have been proposed in the literature for the age estimation and gender classification. However, all of them have still disadvantage such as not complete reflection about face structure, face texture. This technique applies to both face alignment and recognition and significantly improves three aspects. First, we introduce shape description for face model. Second, the feature extraction phase, two geometric features are evaluated as the ratios of the distances between eyes, noses, and mouths. Finally, we classified the gender and age based on the association of two methods: geometric feature based method and Principal Component Analysis (PCA) method for improving the efficiency of facial feature extraction stage. The face database contains the 13 individual groups. Within a given database, all weight vectors of the persons within the same age group are averaged together. A range of an age estimation result is 15 to 70 years old, and divided into 13 classes with 5 years old range. Experimental results show that better gender classification and age estimation.
Networks and Strategic Options for Innovative Performance in KBEs

This paper explores patterns of network participation and usage by young knowledgeintensive small and medium sized enterprises (SMEs) that exhibit innovative performance. Despite the wealth of literature on industry network activity, demonstrated connections between network participation and firm growth are relatively rare, especially for SMEs. To begin filling this gap, this paper seeks to find distinct trends and options in network usage exhibited by the most innovative knowledge-intensive SMEs. The paper’s thesis is based on data from a survey of 4,004 new European businesses. The analysis demonstrates a disproportionate use by the firms in question of technology, licensing, and R&D partnerships for the purposes of developing new products, contacting customers, and finding distribution channels. These preliminary findings differed from results that included non-technology based firms and firms that have not introduced new products, implying that there are specific network activities that distinctively assist newly-established knowledge intensive companies in functions related to bringing new products to market.
3D MIMO Scheme for Broadcasting Future Digital TV in Single Frequency Networks

A three-dimensional space-time-space block code for future terrestrial digital TV systems is introduced. The code is based on a double-layer structure designed for inter-cell and intra-cell transmissions in single-frequency networks. Without increasing the complexity of the receiver, the proposed code is very efficient to cope with equal and unequal received powers in single-frequency network scenarios.
Actinomycetes: A Source of Lignocellulolytic Enzymes

Lignocellulose is the most abundant biomass on earth. Agricultural, forest, and agroindustrial activities generate tons of lignocellulosic wastes annually, which present readily procurable, economically affordable, and renewable feedstock for various lignocelluloses based applications. Lignocelluloses are the focus of present decade researchers globally, in an attempt to develop technologies based on natural biomass for reducing dependence on expensive and exhaustible substrates. Lignocellulolytic enzymes, that is, cellulases, hemicellulases, and lignolytic enzymes, play very important role in the processing of lignocelluloses which is prerequisite for their utilization in various processes. These enzymes are obtained from microorganisms distributed in both prokaryotic and eukaryotic domains including bacteria, fungi, and actinomycetes. Actinomycetes are an attractive microbial group for production of lignocellulose degrading enzymes. Various studies have evaluated the lignocellulose degrading ability of actinomycetes, which can be potentially implemented in the production of different value added products. This paper is an overview of the diversity of cellulolytic, hemicellulolytic, and lignolytic actinomycetes along with brief discussion of their hydrolytic enzyme systems involved in biomass modification.
Evaluating ‘Quality of Experience’ of mobile applications and services in a Living Lab setting

This short paper frames the importance of the Quality of Experience in the contemporary ICT environment and links it to the shift towards more user-centric approaches in innovation research. The relevance of the Living Labs approach for QoE measurement is discussed. A software tool that is based on a distributed architecture in which monitored Quality of Service (QoS) parameters, context information and subjective QoE perceptions are combined, is briefly described. In combination with other objective and subjective measures and methods, this tool is currently used for the in situ and real-time measurement of QoE of mobile applications and services such as (personalised) mobile video, mobile gaming, . in Living Lab settings.