Miracle-dz/UniFAR-FTUs huggingface dataset:
Preprint Scan Test Power Simulation on GPGPUs

The precise estimation of dynamic power consumption, power droop and temperature development during scan test require a very large number of time–aware gate–level logic simulations. Until now, such characterizations have been feasible only for rather small designs or with reduced precision due to the high computational demands. We propose a new, throughput–optimized timing simulator on running on GPGPUs to accelerate these tasks by more than two orders of magnitude and thus providing for the first time precise and comprehensive toggle data for industrial–sized designs and over long scan test operations. Hazards and pulse–filtering are supported for the first time in a GPGPU accelerated simulator, and the system can easily be extended to even more sophisticated delay and power models.
Out and queer: independent school teachers navigating the personal and professional

ion of prejudice that is just kind of a comfortable landing spot. ” And she continues with, “If they [straight community members] don’t know anybody who’s openly gay they’re going to be much more comfortable saying ‘those people’”. Many of my co-researchers pointed to the importance of being out and visible to counteract the
A Novel Data-Driven Control Approach for a Class of Discrete-Time Nonlinear Systems

In this work, a novel data-driven control approach, model-free adaptive control, is presented based on a new dynamic linearization technique for a class of discrete-time single-input and single-output nonlinear systems. The main feature of the approach is that the controller design depends merely on the input and the output measurement data of the controlled plant. The theoretical analysis shows that the approach guarantees the bounded input and bounded output stability and tracking error monotonic convergence. The comparison experiments verify the effectiveness of the proposed approach.
High clonal diversity in threatened peripheral populations of the yellow bird's nest (Hypopitys monotropa; syn. Monotropa hypopitys).

BACKGROUND AND AIMS Peripheral populations of plant species are often characterized by low levels of genetic diversity as a result of genetic drift, restricted gene flow, inbreeding and asexual reproduction. These effects can be exacerbated where range-edge populations are fragmented. The main aim of the present study was to assess the levels of genetic diversity in remnant populations of Hypopitys monotropa (syn. Monotropa hypopitys; yellow bird's nest) at the edge of the species' European range in Northern Ireland, since these remnant populations are small and highly fragmented. METHODS Every plant found through surveys of 21 extant populations was genotyped for eight microsatellite loci to estimate levels and patterns of genetic diversity and clonality. KEY RESULTS Levels of genetic diversity were relatively high in the populations studied, and the incidence of clonal reproduction was generally low, with a mean of only 14·45 % of clonal individuals. Clones were small and highly spatially structured. Levels of inbreeding, however, were high. CONCLUSIONS The observed low levels of clonality suggest that the majority of genets in the populations of H. monotropa studied are fertile and that reproduction is predominantly sexual. As the species is highly self-compatible, it is likely that the high levels of inbreeding observed in the populations in the present study are the result of self-pollination, particularly given the small numbers of individuals in most of the patches. Given this extent of inbreeding, further genetic monitoring would be advisable to ensure that genetic diversity is maintained.
A novel approach to delineating the service area of facilities in a network

Many research questions exist in a variety of network environments in the real world, such as delineating the service area of facilities distributed in a network. In this paper, with respect to the traditional method-the breadth-first search algorithm, a new method based on the shortest path algorithm is proposed to delineate service area. A series of experiments are conducted to compare the computational time between the proposed algorithm and the breadth-first search algorithm and the results demonstrate that, in most cases, the proposed one can save much more computational time, especially when the scale of road network or the impedance of the network center increases.
Improved Generalized Birthday Attack

Let r, B and w be positive integers. Let C be a linear code of length Bw and subspace of F2. The k-regular-decoding problem is to find a nonzero codeword consisting of w length-B blocks with Hamming weight k. This problem was mainly studied after 2002. Not being able to solve this problem is critical for cryptography as it gives a fast attack against FSB, SWIFFT and learning parity with noise. In this paper, the classical methods are used in the same algorithm and
Fail-Safe Signalization and Interlocking Design for a Railway Yard: An Automation Petri Net Approach

The most important issue in railway systems is to provide safe transportation. Since no error can be tolerated in railway systems it is an obligation to use reliable signalization and interlocking systems which have to decide what to do in unexpected situations like switch disruptions or signal light defects. By the rapid development in railway systems more formal methods are needed for modeling such systems. In this study, a sample railway yard is modeled with extended type of Petri Nets (PNs) known as Automation Petri Nets (APNs). The model used in design covers both normal situations and possible failures (such as a switch break down) to avoid calamitous accidents.
Development of rehabilitation support system for lower limbs for recovery and quantitative evaluation of proprioception

Proprioception should be necessary for the trunk balance and skillful movement. However, proprioception deteriorates due to aging and spinal cord injury. Training for the recovery of proprioception is required because of the ADL and prevention of overturning. We have developed a new rehabilitation support system for “sensory training”. The purpose of this study is to perform clinical trials with 2 patients by using our system and discuss the results of clinical trials by analyzing the experimental data. In our system, video games are prepared as test programs for the proposed system. The measurements are performed one time before the operation and once or more until subjects are discharged from the hospital after the operation. In experiments, as the comparison studies, conventional quantitative evaluation tests, namely gravicorder test and 10 meter walking test are performed. As a result, this system plays a role of helping the patient with deteriorated proprioception to control lower limb as useful training tool based on the vision information feedback.
Dissecting Bufferbloat: measurement and per-application breakdown of queueing delay

We propose a passive methodology to estimate the queueing delay incurred by TCP traffic, and additionally leverage DPI classification to breakdown the delay across different applications. Ultimately, we correlate the queueing delay to the performance perceived by the users of that applications, depending on their delay-sensitivity. We implement our methodology in Tstat, and make it available as open source software to the community. We validate and tune the tool, and run a preliminary measurement campaign based on a real ISP traffic trace, showing interesting yet partly counter-intuitive results.
A Context-Aware Delayed Agglomeration Framework for Electron Microscopy Segmentation

Electron Microscopy (EM) image (or volume) segmentation has become significantly important in recent years as an instrument for connectomics. This paper proposes a novel agglomerative framework for EM segmentation. In particular, given an over-segmented image or volume, we propose a novel framework for accurately clustering regions of the same neuron. Unlike existing agglomerative methods, the proposed context-aware algorithm divides superpixels (over-segmented regions) of different biological entities into different subsets and agglomerates them separately. In addition, this paper describes a “delayed” scheme for agglomerative clustering that postpones some of the merge decisions, pertaining to newly formed bodies, in order to generate a more confident boundary prediction. We report significant improvements attained by the proposed approach in segmentation accuracy over existing standard methods on 2D and 3D datasets.
perturbation in mice for cholesterol metabolism during dietary folate Gene-environment interactions reveal a homeostatic role

You might find this additional info useful. 24 times a year (twice monthly) by the American Physiological Society, 9650 Rockville Pike, Bethesda MD systems with techniques linking genes and pathways to physiology, from prokaryotes to eukaryotes. It is published publishes results of a wide variety of studies from human and from informative model Physiological Genomics
English and Chinese bilingual topic aspect classification: Exploring similarity measures, optimal LSA dimensions, and centroid correction of translated training examples

This paper explores topic aspect (i.e., subtopic or facet) classification for collections that contain more than one language (in this case, English and Chinese), and investigates several key technical issues that may affect the classification effectiveness. The evaluation model assumes a bilingual user who has found some documents on a topic and identified a few passages in each language on specific aspects of that topic that are of interest. Additional passages are then automatically labeled using a k-Nearest-Neighbor classifier and local (i.e., result set) Latent Semantic Analysis (LSA). Experiments show that when few manually annotated passages are available in either language, a classification system trained using passages from both languages can often achieve higher effectiveness than a similar system trained using passages from just one language. Using this experimental framework, this paper answers three technical research questions: whether the normalized cosine similarity measure is better than the more common unnormalized cosine similarity measure (yes), whether the number of retained LSA dimensions (which was heuristically chosen) is appropriate (yes), and whether partial corrections of the translated training examples in the LSA space can yield an improvement over no correction (no).
An abstract framework for ontology evaluation

Ontologies are agreement of the conceptualisation of concepts in a context that can be shared or reused and thus in consequence it aids in interoperability. The evaluation of ontology aims either for assessment of the ontology or is to grade the accessible ontologies with intent to decide on the appropriate among available alternatives for reuse purposes. The literature has immense contents related to this area, but diversified. Furthermore, an abstract framework for ontology evaluation was also not found in review. Accordingly, the present study was intended to devise such framework. The presented framework in this study was an outcome of comprehensive analysis of the approaches, perspectives or dimensions, metrics and other related aspects of ontology evaluation. The contribution of this work is to exhibit the said area in a concise manner, and a general ontology evaluation paradigm.
Illness Perception and Depressive Symptoms among Persons with Type 2 Diabetes Mellitus: An Analytical Cross-Sectional Study in Clinical Settings in Nepal

Background. This study aimed to assess the relationship between illness perception and depressive symptoms among persons with diabetes. Method. This was an analytical cross-sectional study conducted among 379 type 2 diabetic patients from three major clinical settings of Kathmandu, Nepal. Results. The prevalence of depressive symptoms was 44.1% (95% CI: 39.1, 49.1). Females (p < 0.01), homemakers (p < 0.01), 61–70 age group (p = 0.01), those without formal education (p < 0.01), and people with lower social status (p < 0.01) had significantly higher proportion of depressive symptoms than the others. Multivariable analysis identified age (β = 0.036, p = 0.016), mode of treatment (β = 0.9, p = 0.047), no formal educational level (β = 1.959, p = 0.01), emotional representation (β = 0.214, p < 0.001), identity (β = 0.196, p < 0.001), illness coherence (β = −0.109, p = 0.007), and consequences (β = 0.093, p = 0.049) as significant predictors of depressive symptoms. Conclusion. Our study demonstrated a strong relationship between illness perception and depressive symptoms among diabetic patients. Study finding indicated that persons living with diabetes in Nepal need comprehensive diabetes education program for changing poor illness perception, which ultimately helps to prevent development of depressive symptoms.
The revised Dimensions of Mastery Questionnaire (DMQ 18) for infants and preschool children with and without risks or delays in Hungary, Taiwan, and the US

Mastery motivation is an important concept in child development shown by persistence and affect when attempting to solve challenging problems. The Revised Dimensions of Mastery Questionnaire (DMQ 18) provides a parent or caregiver rating of a young child’s responses to challenge. This paper describes and compares parent’s DMQ 18 ratings of 503 children aged 6months to 5-years in samples from Hungary, Taiwan, and the US who were developing typically, were at-risk due to prematurity, or were developmentally delayed. Good reliability and validity were found for the persistence scales. There were modest correlations between age and the positive DMQ scales in Hungary but not Taiwan. There were few gender differences, and few parent education correlations with DMQ ratings by either parents or teachers. However, parents of infants born preterm rated them lower on gross motor persistence and competence; and parents rated children with developmental delay much lower than children developing typically. Hungarian parents rated their children higher on gross motor persistence and competence but lower on shame than parents from Taiwan. Most of the results are consistent with but extend those in the literature. Implications for the use of DMQ 18 are discussed.
Linear spectral random mixture analysis for hyperspectral imagery

Independent component analysis (ICA) has shown success in blind source separation and channel equalization. Its applications to remotely sensed images have been investigated in recent years. Linear spectral mixture analysis (LSMA) has been widely used for subpixel detection and mixed pixel classification. It models an image pixel as a linear mixture of materials present in an image where the material abundance fractions are assumed to be unknown and nonrandom parameters. This paper considers an application of ICA to the LSMA, referred to as ICA-based linear spectral random mixture analysis (LSRMA), which describes an image pixel as a random source resulting from a random composition of multiple spectral signatures of distinct materials in the image. It differs from the LSMA in that the abundance fractions of the material spectral signatures in the LSRMA are now considered to be unknown but random independent signal sources. Two major advantages result from the LSRMA. First, it does not require prior knowledge of the materials to be used in the linear mixture model, as required for the LSMA. Second, and most importantly, the LSRMA models the abundance fraction of each material spectral signature as an independent random signal source so that the spectral variability of materials can be described by their corresponding abundance fractions and captured more effectively in a stochastic manner.
The Effects of Filtering Malicious Traffic under DoS Attacks

Denial-of-Service (DoS) attacks typically generate huge amount of adverse traffic to a target server and make the server unavailable for services. Several works had put lots of efforts to find novel and effective techniques to detect and prevent such attacks. However, most studies were conducted using offline data or via simulation. Only a few studies address the issues of server survivability when under DoS attacks and perform real experiments to measure the effectiveness of filtering such malicious traffic since capturing and analyzing real attacking traffic on the fly would be an enormous task. This paper proposes a model to measure the effectiveness of filtering malicious traffic while actual attacks aim at a target server. The model performs a simple anomaly detection using the rates of input traffic which is classified into normal, suspicious and malicious traffic based on the pre-defined threshold values. If the input traffic is regarded as suspicious or malicious, the model will substantially drop part of the input traffic to an acceptable level so that only the small amount of traffic is allowed to pass and reach the target server. As a result, the server survives the attacks. We implemented the proposed model in Snort In-line on which we modified the traffic analysis module for classifying input traffic. We also added a new traffic control module for dropping malicious traffic. In the experiments, we generated real attacks on a web server with various attacking rates and filtering rates, and measured the timeout of the target server while a normal client periodically accessed the server. The timeout of the server indicates the server survivability and in turn tells us the effectiveness of filtering rates applied. The experimental results show that if the filtering rate is higher, the server will have the longer timeout. In addition, if the attacking rate is higher, the server will crash faster, or have the shorter timeout. In conclusion, the proposed work shows the effectiveness of traffic filtering to the survivability of a target server.
A framework for interactive GPU-supported rendering and styling of virtual hair

The interactive styling and rendering of virtual hair is essential for creating realistic looking human avatars for use in computer games, virtual worlds, and movie special effects. Hair models can contain tens of thousands of hair strands and hence it is important to develop techniques to modify the hair in a realistic fashion and to render it at interactive frame rates. In this paper we present a GPU-based framework for styling and rendering of virtual hair. We use wisps to represent basic units of hair strands and present an improved statistical model for hair wisp generation which allows the creation of smooth and fringy styles. Fast modelling is achieved by using create, edit, delete and copy and paste operations for key strands representing wisp. The styling process is simplified by using a local coordinate system for hair strands in order to define preferred styling (brushing) directions. Fast photo-realistic rendering is achieved by using the latest GPU functionalities for both the light reflection calculation and the shadow generation of hair strands. We also propose a new method for real-time anti-aliasing using GPU programming.
The Design of Everyday Things: Revised and Expanded Edition

It's not surprisingly when entering this site to get the book. One of the popular books now is the the design of everyday things revised and expanded edition. You may be confused because you can't find the book in the book store around your city. Commonly, the popular book will be sold quickly. And when you have found the store to buy the book, it will be so hurt when you run out of it. This is why, searching for this popular book in this website will give you benefit. You will not run out of this book.
Incremental partition recombination for efficient tracking of multiple dialog states

For spoken dialog systems, tracking a distribution over multiple dialog states has been shown to add robustness to speech recognition errors. To retain tractability, past work has suggested tracking dialog states in groups called partitions. While promising, current techniques are limited to incorporating a small number of ASR N-Best hypotheses. This paper overcomes this limitation by incrementally recombining partitions during the update. Experiments with a database of 300,000 AT&T staff show better whole-dialog accuracy than existing approaches. In addition, our implementation, which is available to the research community [1], views partitions as programmatic objects - an accessible formulation for commercial application developers.
An improvement of trace scheduling for global microcode compaction

Fisher's trace scheduling procedure for global compaction has proven to be able to produce significant reduction in execution time of compacted microcode, however extra space may be sometimes required during bookkeeping, and the efficacy of compaction of microprogram loop is lower than that of hand compaction. This paper introduces an improved trace scheduling compaction algorithm to mitigate the drawbacks mentioned above. The improved algorithm is based on a modified menu of moving microoperations, an improved trace scheduling algorithm, and a special loop compaction algorithm. Preliminary tests indicate that this global compaction algorithm gives shorter execution time and less space requirement in comparison with Fisher's algorithm.
Walking, Cycling and Driving to Work in the English and Welsh 2011 Census: Trends, Socio-Economic Patterning and Relevance to Travel Behaviour in General

Objectives Increasing walking and cycling, and reducing motorised transport, are health and environmental priorities. This paper examines levels and trends in the use of different commute modes in England and Wales, both overall and with respect to small-area deprivation. It also investigates whether commute modal share can serve as a proxy for travel behaviour more generally. Methods 23.7 million adult commuters reported their usual main mode of travelling to work in the 2011 census in England and Wales; similar data were available for 1971–2001. Indices of Multiple Deprivation were used to characterise socio-economic patterning. The National Travel Survey (2002–2010) was used to examine correlations between commute modal share and modal share of total travel time. These correlations were calculated across 150 non-overlapping populations defined by region, year band and income. Results Among commuters in 2011, 67.1% used private motorised transport as their usual main commute mode (−1.8 percentage-point change since 2001); 17.8% used public transport (+1.8% change); 10.9% walked (−0.1% change); and 3.1% cycled (+0.1% change). Walking and, to a marginal extent, cycling were more common among those from deprived areas, but these gradients had flattened over the previous decade to the point of having essentially disappeared for cycling. In the National Travel Survey, commute modal share and total modal share were reasonably highly correlated for private motorised transport (r = 0.94), public transport (r = 0.96), walking (r = 0.88 excluding London) and cycling (r = 0.77). Conclusions England and Wales remain car-dependent, but the trends are slightly more encouraging. Unlike many health behaviours, it is more common for socio-economically disadvantaged groups to commute using physically active modes. This association is, however, weakening and may soon reverse for cycling. At a population level, commute modal share provides a reasonable proxy for broader travel patterns, enhancing the value of the census in characterising background trends and evaluating interventions.
Shrinking Gradient Descent Algorithms For Total Variation based Image Denoising 1

In this paper, we make some observations on the chambolle’s algorithm and projected gradient (GP) algorithm for the dual model of total variation denoising problems and propose a shrinking gradient descent algorithm (SGDA). We consider two frameworks, SGDA-1 and SGDA-2, according to the choice of shrinkage factor and step length. Global convergence analysis of these two frameworks are present. Numerical experiments indicate the new algorithms perform well in gray and color image denoising problems and the efficiency of SGDA is very competitive to chambolle’s algorithm and GP.