Miracle-dz/UniFAR-FTUs huggingface dataset:
Output-Based Event-Triggered Control With Guaranteed ${\cal L}_{\infty}$-Gain and Improved and Decentralized Event-Triggering

Most event-triggered controllers available nowadays are based on static state-feedback controllers. As in many control applications full state measurements are not available for feedback, it is the objective of this paper to propose event-triggered dynamical output-based controllers. The fact that the controller is based on output feedback instead of state feedback does not allow for straightforward extensions of existing event-triggering mechanisms if a minimum time between two subsequent events has to be guaranteed. Furthermore, since sensor and actuator nodes can be physically distributed, centralized event-triggering mechanisms are often prohibitive and, therefore, we will propose a decentralized event-triggering mechanism. This event-triggering mechanism invokes transmission of the outputs in a node when the difference between the current values of the outputs in the node and their previously transmitted values becomes “large” compared to the current values and an additional threshold. For such event-triggering mechanisms, we will study closed-loop stability and L∞-performance and provide bounds on the minimum time between two subsequent events generated by each node, the so-called inter-event time of a node. This enables us to make tradeoffs between closed-loop performance on the one hand and communication load on the other hand, or even between the communication load of individual nodes. In addition, we will model the event-triggered control system using an impulsive model, which truly describes the behavior of the event-triggered control system. As a result, we will be able to guarantee stability and performance for event-triggered controllers with larger minimum inter-event times than the existing results in the literature. We illustrate the developed theory using three numerical examples.
Pituitary Gland: Neuropeptides, Neurotransmitters and Growth Factors

The hypothalamus receives neuronal afferents from numerous sources including inputs from limbic structures, such as the amygdala and hippocampus, and from brainstem regions involved in the regulation of the cardiovascular system and other autonomic functions. These afferents using a vast array of neurotransmitters and neuropeptides influence the activity of the hypothalamic neurons which synthesize and secrete the hypothalamic releasing and release-inhibiting factors into the hypophyseal portal circulatory system. The afferents can modulate the activity of the hypothalamic neurons by forming synapses on the neuronal cell body, on the nerve terminals in the median eminence or both. The chemicals most frequently used as neurotransmitters are the biogenic amines, including the catecholamines (norepinephrine, dopamine and epinephrine), serotonin, acetylcholine and gamma-aminobutyric acid (GABA). The stimulatory influence of norepinephrine, serotonin, and acetylcholine on the secretion of corticotropin (ACTH) in rodents and man will be discussed, whereas GABA exerts an inhibitory effect on the secretion of ACTH in both man and rodents. These effects appear to be mediated by changes in the secretion of the corticotropin-releasing hormone (CRH) and vasopressin into the hypophyseal portal circulation. Numerous neuropeptides appear to alter the secretion of ACTH in the rat. We will discuss the stimulatory actions of neuropeptide Y (NPY), angiotensin II, and peptides of immune cell origin on the secretion of ACTH and CRH. The opioid peptides inhibit the secretion of CRH into the portal blood, however, they exert a potent stimulatory effect on prolactin secretion in the rat and man. We will discuss the receptor subtypes involved in mediating these effects and the interactions of the opioid peptides with the neurotransmitter-containing neurons which project to the hypothalamus. This discussion will focus on the factors which impinge on the releasing factor-containing neurons in the hypothalamus and how they can be studied under in vivo and in vitro conditions.
Improved H.264 video compression based on Cubic Macro-blocks

In the conventional H.264 standard, specified size of Macro-blocks (MBs) is cut from one single frame or field. For every frame, the encoded data are mainly composited with Motion vectors (MVs) and the residuals after Motion Compensation (MC) for all MBs in the frame. However, observing the fact that MVs may keep relatively constant in some videos containing slow changing scenes. This indicates that it is unnecessary to estimate the MVs for every frame, but using the same MVs for several adjacent frames. Consequently, the compression and computational efficiency will be improved significantly. Both concepts of “Virtual Frames” (VF) and Cubic Macro-Blocks (CMB) are introduced to achieve this goal. The residual generated after MC will be processed using 3D-DCT to achieve high compression. Through Matlab simulation, the efficiency of this algorithm is substantiated.
Updating Farmland Satellite Imagery Using High Resolution Aerial Images

This paper presents a new approach for updating farmland satellite imagery by registering it with high resolution aerial images. It is based on Field Boundary Junction (FBJ) as feature for registration. Fields connected to FBJ are grouped together to form FBJ descriptor. Fields are described by sampling Field Boundaries (FB) relative to FBJ locations. Every field gets different description for each FBJ connected to it. It makes FBJ descriptor unique and helps in finding the correct FBJ matches reliably. It is invariant to scaling, in-plane rotation and translation. Experimental results also show its invariance to non rigid transformations, splitting/merging of fields and localization errors in FBs and FBJs.
Parallelizing Compilation Scheme for Reduction of Power Consumption of Chip Multiprocessors

With the advance of semiconductor technology, chip multiprocessor architectures, or multi core processor architectures have attracted much attention to achieve low power consumption, high effective performance, good cost performance and short hardware/software development period. To this end, parallelizing compilers for chip multiprocessors are expected that allow us to parallelize program effectively and to control the voltage and clock frequency of processors and storages carefully inside an application program. This paper proposes parallelizing compilation scheme with power reduction control under the multigrain parallel processing environment that controls Voltage/Frequency and power supply of each processor core on a chip. In the evaluation, the OSCAR compiler with the proposed scheme achieves 60.7 percent energy reduction for SPEC CFP95 applu without performance degradation on 4 processors, and 85.6 percent energy reduction for SPEC CFP95 tomcatv with real-time deadline constraint on 4 processors, and 86.7 percent energy reduction for SPEC CFP95 swim with the deadline constraint on 4 processors.
A Novel Algorithm Combining Finite State Method and Genetic Algorithm for Solving Crude Oil Scheduling Problem

A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The heuristic returned by the FSM can guide the GA algorithm towards good solutions. The idea behind this is that we can generate promising substructure or partial solution by using FSM. Furthermore, the FSM can guarantee that the entire solution space is uniformly covered. Therefore, the combination of the two algorithms has better global performance than the existing GA or FSM which is operated individually. Finally, a real-life crude oil scheduling problem from the literature is used for conducting simulation. The experimental results validate that the proposed method outperforms the state-of-art GA method.
Perceptions of Trauma Research with a Sample of At-Risk Youth

Growing body of research demon-strates that participants generally report favorable perceptions of participating in trauma research. However, questions remain on the long-term impact of asking at-risk youth about trauma in settings where such questions are unexpected. Perceptions of participation were examined in the current longitudinal study comprising a sample of adolescent girls recruited from the child welfare system to participate in a healthy relationship project. Over a year, teens (n = 180) completed four research sessions during which they were interviewed about interpersonal trauma exposure and trauma-related symptoms. Results indicated that adolescents reported stable, favorable benefit-to-cost ratios over time. Perceptions of research participation and symptom severity did not impact retention.
Bilingual Preschool Children's Participation in Classroom Literacy Activities: "Once upon a Time" and Its Alternatives.

An ethnographic study analyzed and compared children's participation in book reading activi'. :es with their participation in other types of literacy activities. Subjects, 15 bilingual children who were enrolled in a multilingual, multicultural preschool program where English was the common language, were encouraged to maintain their native languages through the presence of native-language tapes, books, and activities. Data included classroom field notes, videotapes, and teacher plans recorded and/or collected over one semester. Results indicated that: (1) the children were not very attentive during the book reading in English that occurred during whole group time; (2) the only children that were being read to in their native languages were the Chinese and Russian children; and (3) the children were actively engaged in other literacy activities, and activities that were not formally designed as literacy activities. Findings underscore the importance of creating opportunities for bilingual children's engagement with print in ways other than English book reading. Children in this classroom with its emphasis on multilingualism demonstrated an emerging awareness of different languages, different conventions of print, and different concepts about print. (Contains 12 references.) (RS) *********. :*********************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. it *********************************************************************** Georgia Earnest Garcia Heriberto Godina University of Illinois @ Urbana-Champaign Contact person: Georgia Earnest Garcia 236A Education 1310 S. Sixth Street Champaign, IL 61820 Tel: 217 333 7048 BILINGUAL PRESCHOOL CHILDREN'S PARTICIPATION IN CLASSROOM LITERACY ACITVTI1ES: 'ONCE UPON A TIME" AND ITS ALTERNATIVES Running head: Bilingual Preschool Children's Literacy Participation PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY TO THE EDUCATIONAL PlEsourict rr INFORMATION CENTER IERICI BEST COPY AVAILABLE U I IMPARTMENT OP EDUCATION Ms, d f ducathshar Paarac one onsoohfnem EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) Thrs document I 130111n fifproduChel of fecifffj hot", fhf p4,1100 0r Of panoviagyl hiphIllihp 'I ' Minor changes have bows made to rmotove raproduCtrOn 00111,11 Points ot veer 0. othmen 111(4 rn INS cloru men( do nol rwcassehly fPfhm officm, OCR( Poillron or frOIrtv
Self-Calibration of Traffic Surveillance Camera using Motion Tracking

A statistical and computer vision approach using tracked moving vehicle shapes for auto-calibrating traffic surveillance cameras is presented. Vanishing point of the traffic direction is picked up from linear regression of all tracked vehicle points. Preliminary straightening model is then built to help collect statistics of the typical vehicle class traveling in each particular scene. Analysis on this class eventually helps to compute the complete calibration parameters. Results obtained from the validation step against traditional methods in different traffic locations demonstrate its desirable accuracy with much more flexibility and reliability.
Density induced p-norm support vector machine for binary classification

This paper presents a new version of support vector machine (SVM) named density induced p-norm SVM (0 <; p <; 1), DPSVM for shot. Our DPSVM introduces the density degrees into the standard p-norm SVM. It extracts the relative density degrees for the training examples and takes these degrees as relative margins for corresponding training examples. Our DPSVM not only inherits good performance of p-norm SVM which can realize feature selection and classification simultaneously, but also improves the performance of p-norm SVM. The numerical experiments results show that our DPSVM is more effective than some usual methods in feature selection and classification.
In vitro Transcription of Double-stranded RNA by Virion-associated RNA Polymerases of Viruses from Gaeumannomyces graminis

Summary Several double-stranded (ds) RNA Gaeumannomyces graminis viruses in groups I and II, but none in group III, have been shown to possess virion-associated RNA polymerase activity. The products of polymerase reaction were full-length single-stranded (ss) RNA transcripts of one of the strands of each of the dsRNA genome segments. Synthesis of ssRNA in vitro continued for up to 48 h during which, on average, up to eight full-length transcripts were produced per dsRNA molecule, i.e. reinitiation of transcription occurred in the in vitro system. In reactions containing [3H]UTP, label was also incorporated into all the dsRNA genome segments, reaching a maximum after 8 h. Examination of transcribing particles by electron microscopy revealed the presence of particles showing the release of looped ssRNA molecules, both ends of which were attached to the particle, as well as particles with one or two linear RNA strands attached. The modal length of the single linear RNA strands was within the range expected for full-length transcripts of the genome dsRNA segments.
Extending the SPOT-VEGETATION NDVI Time Series (1998–2006) Back in Time With NOAA-AVHRR Data (1985–1998) for Southern Africa

A new consistent long-term normalized difference vegetation index (NDVI) time series at a 1-km2 resolution for Southern Africa that is based on the data from Satellite Pour l'Observation de la Terre VEGETATION (VGT) (1998-2006) and the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (AVHRR) (1985-1998) has been produced for vegetation-dynamics monitoring purposes. This paper presents the evaluation of the newly processed AVHRR data set, as well as the integration of this data set with the VGT archive. First, the AVHRR processing chain and the resulting AVHRR data set have been investigated with respect to calibration accuracy, cloud masking, and atmospheric and geometric correction. Second, different calibration approaches, spectral response (SR) functions, spatial resolutions, overpass times, and geometries of observation for the VGT and AVHRR data sets have been compared for a common observation period. The application of published correction functions accounting for the SR differences for both sensors considerably improved the consistency between both data sets. An r2 of 0.85 is obtained between paired samples of the NDVI from the VGT and the newly processed AVHRR archive. After the application of the correction functions, the slope of the regression line between the two NDVI data sets was much closer to the 1:1 line. The performance of the correction functions differed among vegetation types. The largest reduction in the root-mean-square error between the NDVI of both sensors is obtained from areas with higher biomass. Large parts of the remaining variability are suggested to be attributed to the bidirectional reflectance distribution function effects, as demonstrated by the intersensor NDVI time-series variability versus the intrasensor NDVI time-series variability.
Location of the Maximum on Unimodal Surfaces

Pinning down the maximum of a function in one or more variable is a basic computing problem. Without further a priori information regarding the nature of the function, of course, the problem is not feasible for computation. Thus if the function is permitted to oscillate infinitely often then no number of evaluations can give information regarding its maximum. J. Kiefer, in his paper, treats the one-dimensional problem and shows that the correct a priori assumption regarding the function is that of “unimodality. ” He then gives the complete and exact optimal procedure within this framework. In this paper is given what the author believes is the correct a priori background for functions of several variables. (This is analogous to unimodality in one dimension.) However, there is not obtained the exactness of Kiefer's result, but rather the determination of the correct procedures to within “order of magnitude. ”
Triggering algorithm based on inevitable collision states for autonomous emergency braking (AEB) in motorcycle-to-car crashes

This study presents a triggering algorithm for a collaborative, motorcycle-to-car collision avoidance system that slows down the car without input of the driver when the collision becomes imminent. The algorithm is based on the concept of inevitable state collisions. Example applications of the proposed algorithm were obtained via 2D computer simulations representing a data set of real crashes occurred in Italy, Sweden and Australia. Results indicated that the proposed method can apply to typical crash scenarios.
Selective Gene Expression in Magnocellular Neurons in Rat Supraoptic Nucleus

Oxytocin- and vasopressin-producing magnocellular neurons (MCNs) of the hypothalamo-neurohypophysial system are the only neuronal phenotypes present in the rat supraoptic nucleus (SON). Laser microdissection of the SON, extraction and T7-based amplification of its RNAs, and analysis of the resulting cDNAs by hybridization on a 35, 319 element DNA microarray have provided a detailed composite view of the gene expression profile of the MCNs. The genes expressed in the SON were compared with those expressed in a reference tissue consisting of total hypothalamus, and this “expression ratio” indicated which genes were preferentially expressed in the SON. Of the 26,000 unique genes on the array, 1385 were found to be expressed in the SON at levels more than two times greater than in the hypothalamus as a whole. Of these, 123 were expressed ≥3.4-fold higher in the SON versus hypothalamus. Most of these preferentially expressed genes were not previously known to be expressed in the MCNs. Quantitative and double-label in situ hybridization histochemistry was used selectively to confirm a number of these microarray observations and to evaluate the osmotic regulation and cell-specific expression of these genes, respectively.
A representation for crossing set families with applications to submodular flow problems

A representation for intersecting and crossing families of sets is presented. Its size for a family on n elements is O(nz), compared to O(G) for previous representations. Efficient algorithms to construct the representation are given. For example on a network of n vertices and m edges, the representation of all minimum cuts uses O(mlog (G/m)) space; it is constructed in O(nm log (nz/m)) time (this is the best-known time for finding one minimum cut). The representation is used to improve several submodular flow algorithms. For example a minimum-cost dijoin can be found in time O(nzm); as a result a minimum-cost planar feedback arc set can be found in time O(G). The previous bestknown time bounds for these two problems are a factor n larger. The representation is based on a separator theorem for intersecting families.
Specification-based class testing: a case study

The paper contains a case study demonstrating a complete process for specification based class testing. The process starts with an abstract specification written in Object-Z and concludes by exercising an implementation with test cases and evaluating the results. The test cases are derived using the Test Template Framework for each individual operation. They are analysed to generate a finite state machine that can execute test sequences within the ClassBench framework. An oracle is also derived from the Object-Z specification. The case study demonstrates how a formal specification contributes to the development of practical tests that can be executed by a testing tool. It also shows how a test oracle can be derived from a specification and used by the same testing tool to evaluate test results.
The future of binocular rivalry research

Binocular rivalry is often considered an experimental window on the neural processes of consciousness. We propose three distinct approaches to exploit this window. First, one may look through the window, using binocular rivalry as a passive tool to dissociate unaltered sensory input from wavering perceptual output. Second, the mechanisms underlying binocular rivalry may yield detailed knowledge of the neuronal underpinnings of binocular vision and increase the value of rivalry as a tool to study consciousness. Finally, smart experimental manipulations allow experimenters to ‘reach through the window’ and interact with mechanisms of conscious visual perception. Within this distinction, we discuss the major open questions in binocular rivalry research and examine how recent technological developments may be incorporated in future studies
Key Determinants of Success to Achieve Sustainable Competitive Advantage (SCA)

The purpose of this study is to detect the relationship among sustainable competitive advantage (SCA) and key factors affecting it, such as knowledge based view (KBV), resource based view (RBV), dynamic capability (DC) and core competencies (CC). A quantitative methodology is adopted to develop a model, and hypotheses are stated to examine the proposed relationship between the components of banking industry. A highly structured questionnaire is developed and distributed among a sample of 150 managers, specialists and consultants of bank. With a response rate of 81.3 percent, 122 questionnaires are returned; the number of valid and usable questionnaires was 101. The content validity and Cronbach's alpha was used to determine validity and reliability of questionnaire, respectively. Structural equation modeling is used to test the stated hypotheses and its model. A positive relation is found among KBV, RBV, DC, CC and SCA of Mellat Bank.
New results on the capacity of M-ary PPM ultra-wideband systems

In this paper, some new results on the capacity of a typical M-ary pulse position modulation (M-PPM) time hopping (TH) ultra-wideband (UWB) systems are presented. Previous results using a "pure PPM model" are proven to exaggerate the real capacity of a UWB system. Based on an extended model containing correlator and soft decision decoding, the capacity is evaluated in the single-user case and in the case of a system with asynchronous multiple user interference (MUI) when the inputs are equiprobable. It is found that only when bit- signal-to-noise ratio (bit-SNR) is high enough, larger M leads to higher capacity; and for a specific M, the optimal values of PPM time offset parameter T/sub d/, which maximizes the capacity, are independent of bit-SNR. The influence of MUI on capacity is detrimental, especially in the case of high bit-SNR.