Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Multilayer Feedforward Neural Networks in Identification and Control of Wiener Model

The problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feedforward neural network. A two-step procedure is proposed to estimate the linear and nonlinear parts separately. Control of the Wiener model can be achieved by inserting the inverse of the static nonlinearity in the appropriate loop locations. Simulation results illustrate the performance of the proposed method.
Reciprocity in the shadow of threat

This paper considers a partial equilibrium model of conflict where two agents differently evaluate a contested stake. Differently from common contest models, agents have the option of choosing a second instrument to affect the outcome of the conflict. The second instrument is assumed to capture positive investments in ‘conflict management’—labeled as ‘talks’. The focus is on the asymmetry in the evaluation of the stake: whenever the asymmetry in the evaluation of the stake is large there is no room for cooperation and a conflict trap emerges; whenever the degree of asymmetry falls within a critical interval, cooperation seems to emerge only in the presence of a unilateral concession; as the evaluations of the stake converge, only reciprocal concessions can sustain cooperation. Finally the concept of entropy is applied to measure conflict and conflict management.
S Stream Query Optimization

A stream query optimization modifies a stream query to make it faster. Users want stream queries to be fast for several reasons. They want to grasp opportunities or avert risks observable on the input streams before it is too late. They want any views derived from the input streams to be upto-date and not stale. And they want their system to keep up with the rate of input streams without falling behind, which would require shedding load or saving data to disk for later processing. Knowing about stream query optimizations helps developers at all layers. Application developers who know about stream query optimizations can get the most out of the optimizations built into their streaming platform and can supplement them by hand-optimizing their application where necessary. Streaming platform developers can use knowledge about stream query optimizations to make their platform faster by implementing additional optimizations or by generalizing their existing optimizations to apply in more situations. Finally, researchers who invent new optimizations need to know the state-of-the-art optimizations to channel their efforts into the most innovative and impactful direction. The rest of this section introduces some basic concepts and gives a high-level overview and categorization of the most common stream query optimizations. An optimization should be both safe and profitable. An optimization is safe if it can be applied to a stream query without changing what it computes, as determined by the user’s requirements. An optimization is profitable if it makes the stream query faster, as measured by metrics that matter to the user, such as
Nutritional in fl uences on age-related skeletal muscle loss Ailsa

Age-related muscle loss impacts on whole-body metabolism and leads to frailty and sarcopenia, which are risk factors for fractures and mortality. Although nutrients are integral to muscle metabolism the relationship between nutrition and muscle loss has only been extensively investigated for protein and amino acids. The objective of the present paper is to describe other aspects of nutrition and their association with skeletal muscle mass. Mechanisms for muscle loss relate to imbalance in protein turnover with a number of anabolic pathways of which the mechanistic TOR pathway and the IGF-1–Akt–FoxO pathways are the most characterised. In terms of catabolism the ubiquitin proteasome system, apoptosis, autophagy, inflammation, oxidation and insulin resistance are among the major mechanisms proposed. The limited research associating vitamin D, alcohol, dietary acid–base load, dietary fat and anti-oxidant nutrients with age-related muscle loss is described. Vitamin D may be protective for muscle loss; a more alkalinogenic diet and diets higher in the anti-oxidant nutrients vitamin C and vitamin E may also prevent muscle loss. Although present recommendations for prevention of sarcopenia focus on protein, and to some extent on vitamin D, other aspects of the diet including fruits and vegetables should be considered. Clearly, more research into other aspects of nutrition and their role in prevention of muscle loss is required.
Examining Your Data

Data examination is a time-consuming, but necessary, initial step in any analysis that researchers often overlook. Here the researcher evaluates the impact of missing data, identifies outliers, and tests for the assumptions underlying most multivariate techniques. The objective of these data examination tasks is as much to reveal what is not apparent as it is to portray the actual data, because the "hidden" effects are easily overlooked. For example, the biases introduced by nonrandom missing data will never be known unless explicitly identified and remedied by the methods discussed in a later section of this chapter. Moreover, unless the researcher reviews the results on a case-by-case basis, the existence of outliers will not be apparent, even if they substantially affect the results. Violations of the statistical assumption may cause biases or nonsignificance in the results that cannot be distinguished from the true results. Before we discuss a series of empirical tools to aid in data examination, the introductory section of this chapter offers a summary of various graphical techniques available to the researcher as a means of representing data. These techniques provide the researcher with a set of simple yet comprehensive ways to examine both the individual variables and the relationships among them. The graphical techniques are not meant to replace the empirical tools, but rather provide a complementary means of portraying the data and its relationships. As you will see, a histogram can graphically show the shape of a data distribution, just as we can reflect that same distribution with
Robust Speech Command Recognition using Label-Driven Time-Frequency Masking

Speech enhancement driven robust Automatic Speech Recognition (ASR) systems 1 typically require a parallel corpus with noisy and clean speech utterances for 2 training. Moreover, many studies have reported that such front-ends, even though 3 improve speech quality, do not always improve the recognition performance. On the 4 other hand, multi-condition training of ASR systems provides little visualization or 5 interpretability capabilities of how these systems achieve robustness. In this paper, 6 we propose a novel neural architecture with unified enhancement and sequence 7 classification block, that is trained in an end-to-end manner only using noisy speech 8 without having information of clean speech. The enhancement block is a fully 9 convolutional network that is designed to perform Time Frequency (T-F) masking 10 like operation, followed by an LSTM sequence classification block. The T-F 11 masking formulation enables visualization of learned mask and helps us to visualize 12 the T-F points important for classification of a speech command. Experiments 13 performed on Google Speech Command dataset show that our proposed network 14 achieves better results than the baseline model without an enhancement front-end. 15
Does School Integration Generate Peer Effects? Evidence from Boston's Metco Program

Most integration programs transfer students between schools within districts. In this paper, we study Metco, a long-running desegregation program that sends mostly Black students out of the Boston public school district to attend schools in more affluent suburban districts. Metco increases the number of Black students in receiving districts dramatically. Because Metco students have substantially lower test scores than local students, this inflow generates a significant decline in scores, with an especially marked effect on the lower quantiles. This paper investigates the impact of Metco on receiving districts. Aggregate data on schools from districts throughout Massachusetts and micro data from a single large district strongly suggest the impact of Metco is largely a composition effect, since OLS estimates show no impact on average scores in samples of White or non-Metco students. On the other hand, OLS estimates using micro data show some evidence of an effect on the scores of minority 3rd graders in Reading and Language. Instrumental variables estimates for 3rd graders are imprecise but generally in line with OLS. Further analysis shows the negative effects on 3rd graders to be clearly present only for girls. Given the highly localized nature of these results, we conclude that any peer effects from Metco are modest and short-lived.
Analytic network process-based model for selecting an optimal product design solution with zero–one goal programming

Abstract Successive new product development is essential to ensure continual growth of a company. However, any wrong decision-making may cause a catastrophe before the company could benefit from it. Consequently, selecting an appropriate design solution by the product development team or upper management that meets the broad interest of a company has become an important part of new product development. In this paper, we propose a systematic methodology that integrates analytic network process (ANP) and zero–one goal programming (ZOGP) in order to select an optimal product design solution. Before introducing the ANP and ZOGP methods, the fuzzy Delphi method is first adopted to identify the essential factors that have influences on the selection results. Followed by the ANP method, which is used to determine the weights of the proposed product design alternatives, a mathematical ZOGP model is built to incorporate multiple objectives in order to reach the optimal solution. Finally, the MP3 player product design project is used as an empirical example to illustrate the overall decision procedure and to examine the effectiveness of our proposed new model.
Effect of Isomalto-oligosaccharides on Human Fecal Flora

The effect of isomalto-oligosaccharides on human fecal flora was studied. Bifidobacteria and the Bacteroides fragilis group from human intestine could utilize isomalto-oligosaccharides but Escherichia coli and other bacteria could not. After the administration of isomaltooligosaccharides (13.5 g daily for 2 weeks) to healthy adult men and senile persons, the numbers of bifidobacteria in the feces increased. The consistency of feces was improved. These studies may support the usefulness of isomalto-oligosaccharides as components of new healthy foodstuffs for the improvement of the intestinal flora.
Application of Video Scene Semantic Recognition Technology in Smart Video

Video behaviour recognition and semantic recognition understanding are important components of intelligent video analytics. Traditionally, human behaviour recognition has met problems of low recognition efficiencies and poor accuracies. For example, most existing behaviour recognition methods use the video frames obtained by even segmentation and fixed sampling as the input, which may lose important information between sampling intervals, fail to identify the key frames of the video segments and make use of the contextual semantics to understand current behaviour. In order to improve the semantic understanding capacity and efficiency of video segments, this paper adopts a 3-layer semantic recognition approach based on key frame extraction. First, it completes the segmentation for video recognition at the bottom layer, extracts the key frames in the video segments, primarily understands basic semantics of the persons’ identifications, behaviours and environment, and then introduces the primarily acquired information into the middle layer for semantic integration, and through the integration of various semantics, adopts the loss function to learn the latent relationship between different modal semantics, to enhance the integrating capacity and the robustness of the character semantic integration, and finally, by overall fine tuning, semantic recognition and adjusting all the parameters of the network, completes the semantic recognition task of the video scenario. This method enjoys higher recognition accuracies based on certain datasets, capable of effectively recognizing the semantics of characters and behaviours in videos. Through practical testing, the adoption of the algorithm integrating key frame extractions with the video scene semantic recognition has improved the recognition accuracy and effect of the video character semantics.
Structure of efficiency factor at XIII, XIV, XV, and XVI World Championship in basketball

Simovic S, Matkovic B, Mijanovic M, Kocic M, Vojvodic M. Structure of efficiency factor at XIII, XIV, XV, and XVI World Championship in basketball. J. Hum. Sport Exerc. Vol. 7, No. 2, pp. 527-543, 2012. Applying the method of main components by Hotelling and the method of rotation of the main components, i.e. Varimax rotations by Keiser, the latent structure of basketball efficiency was established. It was based on the fourteen manifest indicators of efficiency. Our findings refer to the sample comprised of the game-winning teams at the World Championships: in Greece, 62 basketball teams; the USA, 62 basketball teams; Japan, 80 basketball teams; and Turkey, 80 basketball teams. Factorization was performed on the entire sample of all game-winning teams, that is 284, as well as on the single game winners at the championships in Greece, USA, Japan, and Turkey. There was the total of four factor analyses and within each of them five to seven latent dimensions, i.e. factors based on the fourteen manifest efficiency parameters were extracted. Katell method of landslide indicates a clear elbow between the third and fourth component. These first three latent dimensions in all four factor analysis exhibit the stability of factors and high saturation on the side of the manifest variables. The factors have been defined as: general offensive efficiency factor, three-points shot factor and free throw factor. Having the variables that account for the total number of attempted and made shots dominant within the structure of these factors, it can be concluded that general latent structure of basketball efficiency is indeed explained by means of shot efficiency. These findings confirm both empirical and theoretical speculations of basketball experts, i.e. the overall basketball efficiency is primarily dependent on the shot efficiency, what seems entirely logical. Key words: LATENT STRUCTURE, FACTOR ANALYSIS, WINNER, SHOT
Sensitivity of formaldehyde (HCHO) column measurements from a geostationary satellite to aerosol temporal variation in East Asia

We examine upcoming geostationary satellite observations of formaldehyde 15 (HCHO) columns in East Asia and the retrieval sensitivity to the temporal variation of air mass factor (AMF) considering the presence of aerosols. Observation system simulation experiments (OSSE) were conducted using a combination of a global 3-D chemical transport model (GEOS-Chem), a radiative transfer model (VLIDORT), and a HCHO retrieval algorithm developed for Geostationary Environment Monitoring Spectrometer (GEMS), 20 which will be launched in 2019. Application of the retrieval algorithm to simulated hourly radiances yields the retrieved HCHO column concentrations, which are then compared with the GEOS-Chem HCHO columns as a true value for the evaluation of the retrieval algorithm. In order to examine the retrieval sensitivity to the temporal variation of AMF, we compare the retrieved HCHO columns using monthly versus hourly AMF values and find that the HCHO 25 vertical columns with hourly AMF are in better agreement with the true values, relative to those with monthly AMF. The differences between hourly and monthly AMF range from - 0.70 to 0.73 in absolute value and are mainly caused by temporal changes of aerosol chemical composition: scattering aerosol enhances AMF, whereas absorbing aerosol reduces it. The temporal variations of AMF caused by aerosols increase and decrease HCHO VCDs by 84% 30 and 34%, respectively, compared to HCHO VCDs using monthly AMF. We apply our
A Picture of Present Ubicomp Research Exploring Publications from Important Events in the Field

In this work we use a dataset of papers published in top conferences focused on ubiquitous computing (ubicomp) to provide an overview and analysis of recent ubiquitous computing research performed internationally and in Brazil. The contributions of this study are twofold. First, we extracted useful information from our dataset such as representativeness of authors and institutions, and the formation of communities. Second, we analyzed all papers published between 2010 and 2011 in all top international conferences, creating a taxonomy of recent ubicomp research performed internationally. Afterthat we mapped SBCUP papers (Brazilian ubicomp conference) according to this taxonomy, which enables the comparison of international and national research. This study is useful to guide novices in the field and it also provides experienced researchers with facts enabling the discussion of ubicomp research. Key words: Ubiquitous computing, scientific network, collaboration network, Pervasive, Percom, Ubicomp, SBCUP, taxonomy, characterization.
An Evaluation of Earthquake Hazard Parameters in and Around Ağrı, Eastern Anatolia, Turkey

The earthquake hazard parameters of a and b of Gutenberg-Richter relationships, return periods, expected maximum magnitudes in the next 100 years and probabilities for the earthquakes for certain magnitude values are computed using the earthquakes occurred between 1900 and 2014 years in and around Agri. The relation of LogN=4.73-0.68M is calculated for the studied area. The mapping of b values show that the regions in the east and southeast of Agri, east of Horasan and around Patnos where low b values are computed have high stress levels and capacity to occur large earthquakes in the future. It is found that earthquakes larger than 5.5 may be occurred in the regions where b values lower than 0.8 have been observed in the next 100 years. The return periods for magnitudes between 5.0 and 7.3 are estimated between 5 and 176 years in the studied area. The probabilities of an earthquake with M =6.0, 6.5 and 7.0 in the next 100 years are computed 99%, 86% and 59%, respectively. The largest earthquake occurred in the studied area is 7.3 and its probability to occur is 43% in the next 100 years. The faults around Agri are seismically active and have potential to an earthquake larger than 6.0. Since the sediment basin of Agri is very young and alluvial layer is tick, there is very high hazard on the buildings and human’s life in Agri.
Applying Bytecode Level Automatic Exploit Generation to Embedded Systems

Finding vulnerabilities in software is a difﬁcult task, typically undertaken by experts. Developers have little of the required knowledge to ﬁnd complex vulnerabilities in their software products before release. Automation of vulnerability discovery and proof of concept exploit generation is key to enable developers to check and ﬁx software vulnerabilities in the development process. Research in this ﬁeld is currently directed at automatically generating exploits for software developed for general purpose computers. Embedded systems occupy a signiﬁcant portion of the market and lack typical security features found on general purpose computers. In this report, we implement automatic exploit generation for embedded systems ﬁrmwares, by extending an existing dynamic analysis framework called Avatar. We discuss several techniques to discover vulnerabilities and generate exploits, and evaluate our solution by generating exploits for three vulnerable ﬁrmwares written for a popular ARM Cortex-M3 microcontroller.
TANDEM: matching proteins with tandem mass spectra.

SUMMARY Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching. AVAILABILITY The source code and binaries for this software are available at http://www.proteome. ca/opensource.html, for Windows, Linux and Macintosh OSX. The source code is made available under the Artistic License, from the authors.
CONSTRUCTING A FA FOR HARDWARE HASTENING FOR DSP

CS representation continues to be broadly accustomed to design fast arithmetic circuits because of its natural benefit of getting rid of the big carry-propagation chains. Hardware acceleration continues to be demonstrated a very promising implementation technique for digital signal processing (DSP) domain. However, research activities have proven the arithmetic optimizations at greater abstraction levels compared to structural circuit one considerably effect on the data path performance. Instead of adopting a monolithic application-specific integrated circuit design approach, within this brief, we present a manuscript accelerator architecture composed of flexible computational models that offer the execution of a big group of operation templates present in DSP popcorn kernels. Extensive experimental evaluations reveal that the suggested accelerator architecture provides average gains as high as 61.91% in area-delay product and 54.43% in energy consumption in comparison using the condition-of-art flexible data paths. We differentiate from previous creates flexible accelerators by enabling computations to become strongly carried out with carry-save (CS) formatted data. Advanced arithmetic design concepts, i.e., recoding techniques, are employed enabling CS optimizations to become carried out inside a bigger scope compared to previous approaches.
Salient Region Detection by Integrating Intrinsic and Extrinsic Cues without Prior Information

In recent years, independence on prior information and the efficient integration of multiple visual cues have become an important topic in salient region detection. A salient region detection framework that integrates intrinsic and extrinsic visual cues was proposed in this study to remove the limitations of prior information. First, salient prior map was generated using statistical texture representations and by classifying superpixels into three classes of background, salient regions, and unknown regions. Second, the final saliency map was computed by integrating multi-channel color features and color contrast saliency factors based on self-generating salient prior map. Finally, the experiment was conducted on popular benchmark datasets, namely, Microsoft Research Asia (MSRA) and Extended Complex Scene Saliency Dataset (ECCSD), using two standard criteria: precision-recall rate and F-measure rate. Results demonstrate that the proposed method is more competitive than methods based on prior information, such as dense and sparse reconstruction (DSR), absorbing Markov chain (MC), and robust background detection (RBD). The proposed method achieves an 8% reduction in computing complexity compared with DSR. Compared with the learning-based method without prior information, the performance of the proposed method resembles that of discriminative regional feature integration (DRFI) and its complexity is reduced by 70%. This study provides a novel method to improve the performance of salient region detection and to avoid prior information.