Miracle-dz/UniFAR-FTUs huggingface dataset:
Calculation of worst-case execution time for multicore processors using deterministic execution

Safety critical real time systems need to meet strict timing deadlines. We use a model checking based approach to calculate the WCET, where we apply optimizations to reduce the number of states stored by the model checker. Furthermore, we used deterministic shared memory accesses to further reduce calculation time, memory and number of states needed for calculating WCET. By optimizing the model checking code, we were able to complete benchmarks which otherwise were having state explosion problems. Furthermore, by using deterministic execution, we significantly reduced the calculation time (up to 158×), memory (up to 89×) and states needed (up to 188×) for calculating WCET with a negligible increase (up to 4%) in the calculated WCET for a multicore system with 4 cores. Lastly, unlike other state-of-the-art approaches, that perform binary search to search the WCET by running several iterations, our method calculates WCET in just one iteration. Taking all these optimizations into consideration, the gain in speed was from 1775× to 2471× for 4 threads.
A Shape Command Input Method for Physical Keyboard using Keying Information

The keyboard is mainly used for text input, and has function and shortcut keys to reduce the number of manual operations. However, it is difficult and troublesome for beginners to memorize the relations between the keys and functions. We propose, in this paper, two intuitional input methods on the physical keyboard in addition to the usual texttyping: stroke, which traces a shape on the keyboard, and stamp, which presses a shape on the keyboard. Our system automatically classifies user inputs into texttyping, stroke, or stamp from the keying information, enabling us to seamlessly input those commands without additional devices.
Study on an Assignment Problem with Multi-Mode and Multi-Resource Information Fusing

Traditional assignment problem can not deal with fuzzy and uncertain evaluation data, which hinders the development of assignment problem (AP). With the deep study on subjective evaluation and linguistic model, we presented an improved 2-Tuple model for task assignment with multi-mode and multi-resource information. By using the model, we could standardize and fuse the evaluation data, and then find out the Assignment project. The assumption of assignment in customs risk management proved the effectiveness of the model.
Ambiguity resolution analysis in incremental parsing of natural language

Incremental parsing gains its importance in natural language processing and psycholinguistics because of its cognitive plausibility. Modeling the associated cognitive data structures, and their dynamics, can lead to a better understanding of the human parser. In earlier work, we have introduced a recursive neural network (RNN) capable of performing syntactic ambiguity resolution in incremental parsing. In this paper, we report a systematic analysis of the behavior of the network that allows us to gain important insights about the kind of information that is exploited to resolve different forms of ambiguity. In attachment ambiguities, in which a new phrase can be attached at more than one point in the syntactic left context, we found that learning from examples allows us to predict the location of the attachment point with high accuracy, while the discrimination amongst alternative syntactic structures with the same attachment point is slightly better than making a decision purely based on frequencies. We also introduce several new ideas to enhance the architectural design, obtaining significant improvements of prediction accuracy, up to 25% error reduction on the same dataset used in previous work. Finally, we report large scale experiments on the entire Wall Street Journal section of the Penn Treebank. The best prediction accuracy of the model on this large dataset is 87.6%, a relative error reduction larger than 50% compared to previous results.
BANCO DE PORTUGAL Economic Research Department WAGES AND THE RISK OF DISPLACEMENT

In this paper a simultaneous-equations model of firm closing and wage determination is developed in order to analyse how wages adjust to unfavorable shocks that raise the risk of displacement through firm closing, and to what extent a wage change affects the exit likelihood. The results show that the fear of job loss generates bargaining concessions instead of compensating differentials. A novel result that emerges from this study is that firms with a higher incidence of minimum wage earners are more vulnerable to adverse demand shocks due to their inability to adjust wages downward. In fact, minimum wage restrictions were seen to increase the failure rates. JEL classification : J31; J65
Imaging Key Biomarkers of Tumor Angiogenesis

Angiogenesis is a fundamental requirement for tumor growth and therefore it is a primary target for anti-cancer therapy. Molecular imaging of angiogenesis may provide novel opportunities for early diagnostic and for image-guided optimization and management of therapeutic regimens. Here we reviewed the advances in targeted imaging of key biomarkers of tumor angiogenesis, integrins and receptors for vascular endothelial growth factor (VEGF). Tracers for targeted imaging of these biomarkers in different imaging modalities are now reasonably well-developed and PET tracers for integrin imaging are currently in clinical trials. Molecular imaging of longitudinal responses to anti-angiogenic therapy in model tumor systems revealed a complex pattern of changes in targeted tracer accumulation in tumor, which reflects drug-induced tumor regression followed by vascular rebound. Further work will define the competitiveness of targeted imaging of key angiogenesis markers for early diagnostic and image-guided therapy.
Airfield runway inspection using 3 dimensional GPR

The subsurface conditions under an airfield runway has been mapped using 3-dimensional CPR. This paper contains a case story from an airfield survey where full 3-dimensional data acquisition has been performed. The results from the migrated GPR images show details such as cables, drainage pipes and cavities which would have been difficult to detect using traditional 2-dimensional GPR profiling.
A Comparison of Adaline and MLP Neural Network based Predictors in SIR Estimation in Mobile DS/CDMA Systems

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required. Keywords—Power control, neural networks, DS/CDMA mobile communication systems.
Performance enhancement of IEEE802.11n wireless LAN using irregular LDPCC

The need for flexible network structures has created a successful Wireless Local Area Network (WLAN) market, promising to replace many wired LANs in the near future. The latest draft of IEEE 802.11n offers the potential of throughputs beyond 200 Mbps, based on physical layer data rates up to 600 Mbps. IEEE 802.11n standard adopts low density parity check coding as optional coding scheme to offer higher reliability in PHY level. LDPC may end up as the standard scheme in a host of sectors including communications, broadcasting and even hard disk drives. This paper presents LDPC efficient encoder and decoder then the performance of LDPC based on IEEE 802.11n standard is studied. Different modulation and coding schemes were compared to get the best choice.
An Environment for Morphosyntactic Processing of UnrestrictedSpanish

We present in this paper a fast, broad-coverage, accurate morphological analyzer for Spanish words, MACO+, which is an extended and improved version of that described in (Acebo et al., 1994). The earlier version had two main aws: it was not transportable, and it was too slow to enable massive text processing. The presented system not only overcomes those two aws, but also ooers improved coverage and accuracy. We also present two general part-of-speech taggers, which can be used to disambiguate the output of the morphological analyzer. All modules run in any Unix/Linux machine as a pipeline process and they may also be used inside the GATE environment for NLP (Cunningham et al., 1996). The system is currently being used to annotate the LexEsp corpus, a 5.5 million word corpus of Spanish, in a bootstrapping reening procedure. Initial evaluation and results are reported.
Prediction of Protein Structural Class Based on Gapped-Dipeptides and a Recursive Feature Selection Approach

The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM) profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE). These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.
Conservation and Evolution of Cis-Regulatory Systems in Ascomycete Fungi

Relatively little is known about the mechanisms through which gene expression regulation evolves. To investigate this, we systematically explored the conservation of regulatory networks in fungi by examining the cis-regulatory elements that govern the expression of coregulated genes. We first identified groups of coregulated Saccharomyces cerevisiae genes enriched for genes with known upstream or downstream cis-regulatory sequences. Reasoning that many of these gene groups are coregulated in related species as well, we performed similar analyses on orthologs of coregulated S. cerevisiae genes in 13 other ascomycete species. We find that many species-specific gene groups are enriched for the same flanking regulatory sequences as those found in the orthologous gene groups from S. cerevisiae, indicating that those regulatory systems have been conserved in multiple ascomycete species. In addition to these clear cases of regulatory conservation, we find examples of cis-element evolution that suggest multiple modes of regulatory diversification, including alterations in transcription factor-binding specificity, incorporation of new gene targets into an existing regulatory system, and cooption of regulatory systems to control a different set of genes. We investigated one example in greater detail by measuring the in vitro activity of the S. cerevisiae transcription factor Rpn4p and its orthologs from Candida albicans and Neurospora crassa. Our results suggest that the DNA binding specificity of these proteins has coevolved with the sequences found upstream of the Rpn4p target genes and suggest that Rpn4p has a different function in N. crassa.
Extremes of information combining

Extreme densities for information combining are found for two important channel models: the binary-input symmetric parallel broadcast channel and the parity-constrained-input symmetric parallel channels. Following, upper and lower mutual information thresholds are stated for per-bit maximum a posteriori probability (MAP) decoding and low-density parity-check (LDPC) code ensembles.
Learning to Pay Attention to What Matters : The Conditioning Circuit

This study proposes an alternative to the conditioning circuit as discussed in Gross-berg and Levine (1987). This new version builds on recent work on selective attention (LaBerge, 1995), fear conditioning (Weinberger, 1995) and adaptive timing (Grossberg & Merrill, 1992), and addresses some of the shortcomings in Grossberg and Levine (1987), such as: self-priming, weight transport and the habituation mechanism of short-term memory. The performance of the present implementation is analyzed on two classical conditioning paradigms: simple acquisition and blocking. Comparisons between the present model and Grossberg and Levine (1987) are also drawn.
THE EXPLORATION OF HOMOPHOBIA WITHIN INSTITUTIONAL SETTINGS: EXPLORATION OF HOMOPHOBIA IN SCHOOLS

ABSTRACT THE EXPLORATION OF HOMOPHOBIA WITHIN INSTITUTIONAL SETTINGS: EXPLORATION OF HOMOPHOBIA IN SCHOOLS Paul S. Heffner Andrea Doyle This researcher examines the effects of homophobia in the school setting on self-identified LGBTQ high school students. Current research argues that LGBTQ students are particularly vulnerable to harassment and oppression within school systems but are unclear as to the ultimate consequences for these students. To explore the effects of homophobia, this dissertation analyzed data collected from surveys completed anonymously by voluntary student participants. Data collected includes participants’ perceptions of oppression as well as participants’ perceived views on high school experiences such as social, academic, and atrisk functioning. Anonymous surveys were collected and resulted in a final sample size of 67. A factor analysis was applied to determine correlations between identified experiences of oppression and behaviors, attitudes, and emotional regulation. Results indicated a correlation between perceptions by participants that school staff are not responsive to oppressive behaviors and higher instances of substance use and higher instances of risk taking behaviors. Further results indicated that participants that reported higher levels of substance use also reported perceptions of physical or verbal harassment.
What We Know and Would Like to Know about CDKL5 and Its Involvement in Epileptic Encephalopathy

In the last few years, the X-linked serine/threonine kinase cyclin-dependent kinase-like 5 (CDKL5) has been associated with early-onset epileptic encephalopathies characterized by the manifestation of intractable epilepsy within the first weeks of life, severe developmental delay, profound hypotonia, and often the presence of some Rett-syndrome-like features. The association of CDKL5 with neurodevelopmental disorders and its high expression levels in the maturing brain underscore the importance of this kinase for proper brain development. However, our present knowledge of CDKL5 functions is still rather limited. The picture that emerges from the molecular and cellular studies suggests that CDKL5 functions are important for regulating both neuronal morphology through cytoplasmic signaling pathways and activity-dependent gene expression in the nuclear compartment. This paper surveys the current state of CDKL5 research with emphasis on the clinical symptoms associated with mutations in CDKL5, the different mechanisms regulating its functions, and the connected molecular pathways. Finally, based on the available data we speculate that CDKL5 might play a role in neuronal plasticity and we adduce and discuss some possible arguments supporting this hypothesis.
THE RELATIONSHIP BETWEEN TURKISH EFL STATE SCHOOL TEACHERS' CULTURAL INTELLIGENCE AND THEIR PROFESSIONAL WELL-BEING

Cultural intelligence is described as the ability of a person to behave adequately in culturally diverse environments. It involves comprehending the effects of cultural background on the attitudes of people for auspicious participation in any social setting. Cultural intelligence may be positively and significantly correlated with professional well-being among English as foreign language (EFL) teachers. So, the present study sought to investigate the correlation between Turkish EFL state school teachers' cultural intelligence and their professional well-being. A sample including 120 EFL state school teachers completed two questionnaires: (1) Cultural Intelligence Scale developed by Cultural Intelligence Center (2005); and (2) the Scale of Teacher Perception of Professional Well-Being developed by Yildirim, Arastaman and Dasci (2016). The results of the study indicated significant correlations between Turkish EFL state school teachers' cultural intelligence and their professional well-being. This study may help English Language Teaching (ELT) departments to implement materials to their curriculum for aiding EFL teachers in terms of developing cultural intelligence. Furthermore, this paper makes a unique contribution to the area of cultural intelligence by identifying whether there is a relationship between cultural intelligence and professional well-being.
On Intra Prediction for Screen Content Video Coding

Screen content coding (SCC) is becoming increasingly important in various applications, such as desktop sharing, video conferencing, and remote education. When compared to natural camera- captured content, screen content has different characteristics, in particular sharper edges. In this paper, we propose a novel intra prediction scheme for screen content video. In the proposed scheme, bilinear interpolation in angular intra prediction in HEVC is selectively replaced by nearest-neighbor intra prediction to preserve the sharp edges in screen content video. We present three different variants of the proposed nearest neighbor prediction algorithm: two implicit methods where both the encoder, and the decoder derive whether to perform nearest neighbor prediction or not based on either (a) the sum of the absolute difference, or (b) the difference between the boundary pixels from which prediction is performed; and another variant where Rate-Distortion-Optimization (RDO) search is performed at the encoder to decide whether or not to use the nearest neighbor interpolation, and explicitly signaled to the decoder. We also discuss the various underlying trade-offs in terms of the complexity of the three variants. All the three proposed variants provide significant gains over HEVC, and simulation results show that average gains of 3.3% BD-bitrate in Intra-frame coding are achieved by the RDO variant for screen content video. To the best of our knowledge, this is the first paper that 1) points out current HEVC intra prediction scheme with bilinear interpolation does not work efficiently for screen content video and 2) uses different filters adaptively in the HEVC intra prediction interpolation.
Computational Metalexicography in Practice – Corpus-based support for the revision of a commercial dictionary

Computational Metalexicography in Practice { Corpus-based support for the revision of a commercial dictionary Abstract In a cooperation between dictionary publishers and computational linguists, raw material for the revision of the German part of a bilingual German ! English dictionary (Langenscheidts Handww orterbuch Englisch, Neubearbeitung 1991) was produced. In a case study, the entries for headwords with the initial letter \p", then, { between August 1997 and March 1998 { the full dictionary were systematically checked against a 300 million word German newspaper corpus from the late 80s and early 90s. The objective was to nd evidence to support updates of the lemma inventory of the dictionary and to enhance the example and collocation coverage. The data production from the corpora is automatic, the (manual, interactive) lexicographic procedures remain unchanged. To this end, standard corpus pre-processing (tokenizing, tagging, lemmatization) and a hierarchical set of query templates for collocation extraction were used. The dictionary was transformed into a speciic data format (similar to database entries), and the examples contained in the articles were prepared for automatic querying. The results are of metalexicographic interest: they show the potential of reened macrostructural selection procedures, help to improve the documentation of readings through examples, and, generally, provide an example of the use of standard computational linguistic techniques for dictionary revision. The auxiliary resources constructed from the corpora in the same process { a verb frequency lexicon for German and a collection of noun-verb collocation candidates are useful and relevant in their own right. Similarly, the tools used are mostly generic and thus reusable outside the speciic context discussed here.
Development of energy management and warning system for resident: An energy saving solution

This paper is proposing the household energy management and warning system for energy saving solution. The overall control scheme is mainly governed by a dsPIC33 microcontroller. There are four subsystems to be concerned (i) air-condition's inverter control, (ii) fluorescence brightness control, (iii) power switching control (for general loads such as television, radio, fan, etc.), (iv) household electricity usage warning system. This whole system can monitor the power usage and display through a LCD monitor. Then, it can warn the users through LED bulbs when the power usage is getting close to the monthly prescribed energy usage levels. An experiment conducted by installing this system in an apartment room has shown a satisfactory result in reducing power usage level.