Miracle-dz/UniFAR-FTUs huggingface dataset:
Inference Driven Metric Learning for Graph Construction

Graph-based semi-supervised learning (SSL) methods usually consist of two stages: in the first stage, a graph is constructed from the set of input instances; and in the second stage, the available label information along with the constructed graph is used to assign labels to the unlabeled instances. Most of the previously proposed graph construction methods are unsupervised in nature, as they ignore the label information already present in the SSL setting in which they operate. In this paper, we explore how available labeled instances can be used to construct a better graph which is tailored to the current classification task. To achieve this goal, we evaluate effectiveness of various supervised metric learning algorithms during graph construction. Additionally, we propose a new metric learning framework: Inference Driven Metric Learning (IDML), which extends existing supervised metric learning algorithms to exploit widely available unlabeled data during the metric learning step itself. We provide extensive empirical evidence demonstrating that inference over graph constructed using IDML learned metric can lead to significant reduction in classification error, compared to inference over graphs constructed using existing techniques. Finally, we demonstrate how active learning can be successfully incorporated within the the IDML framework to reduce the amount of supervision necessary during graph construction. Appearing in the Fourth North East Student Colloquium on Artificial Intelligence, Amherst, MA, 2010. Copyright 2010 by the author(s)/owner(s).
The Centre Acknowledges Financial Support from the Leverhulme Trust under Programme Grant F114/bf Centre for Research on Globalisation and Labour Markets Trade Liberalisation and Technology Choice Trade Liberalisation and Technology Choice

Acknowledgements The authors gratefully acknowledge financial support from The Leverhulme Trust under Programme Grant F114/BF. They are also grateful for comments from two referees and participants in a workshop at the University of Nottingham. Abstract This paper considers the links between trade liberalisation and technology choice in the non-liberalising country. Trade-liberalisation-induced changes in relative product prices have direct effects on equilibrium relative factor returns. The consequent changes in relative input costs may also lead producers to switch to alternative technologies, which will in turn induce a further indirect change in relative factor returns. Will this indirect affect exacerbate or ameliorate the direct effect on relative factor returns? We find that this depends on the relative cost savings across sectors and factor cost shares.
Process Discovery Using Classification Tree Hidden Semi-Markov Model

Various and ubiquitous information systems are being used in monitoring, exchanging, and collecting information. These systems are generating massive amount of event sequence logs that may help us understand underlying phenomenon. By analyzing these logs, we can learn process models that describe system procedures, predict the development of the system, or check whether the changes are expected. In this paper, we consider a novel technique that models these sequences of events in temporal-probabilistic manners. Specifically, we propose a probabilistic process model that combines hidden semi-Markov model and classification trees learning. Our experimental result shows that the proposed approach can answer a kind of question-"what are the most frequent sequence of system dynamics relevant to a given sequence of observable events? ". For example, "Given a series of medical treatments, what are the most relevant patients' health condition pattern changes at different times? ".
Colour Contrast Enhancement Method by Scaling the DC Coefficients in CIE-LAB Colour Space

Colour and brightness of the captured images from low cost digital cameras are usually different from the colour and brightness of the original scene. Many factors are responsible for the low contrast images such as non uniform illumination, large or small exposure of some specific regions, and the unwanted movements of camera users. Due to these reasons the captured image to looks annoying to human visual system. Thus, contrast enhancement methods are required for improving the visual appearance of the colour images. In this paper the performance of contrast limited adaptive histogram equalization (CLAHE) method is compared with method of DC coefficient scaling in the compressed DCT domain for enhancing the contrast of colour images. In addition, as a modification DC coefficient scaling is also implemented in the CIE-Lab colour space. The contrast is only enhanced in L component and keeping the colour information preserved. This improves the entropy of standard method. For comparing the performance along with SNR and entropy the absolute standard deviation difference is also used as parameters. The methods are tested on various true colour images from different environment. General Terms Image processing, Image enhancement, Colour spaces
Title : Heritable capture of heterochromatin dynamics in 1 Saccharomyces cerevisiae 2 3 Authors :

34 Heterochromatin exerts a heritable form of eukaryotic gene repression and 35 contributes to chromosome segregation fidelity and genome stability. However, to date 36 there has been no quantitative evaluation of the stability of heterochromatic gene 37 repression. We designed a genetic strategy to capture transient losses of gene silencing in 38 Saccharomyces as permanent, heritable changes in genotype and phenotype. This 39 approach revealed rare transcription within heterochromatin that occurred in 40 approximately 1/1000 cell divisions. In concordance with multiple lines of evidence 41 suggesting these events were rare and transient, single-molecule RNA FISH showed that 42 transcription was limited. The ability to monitor fluctuations in heterochromatic 43 repression uncovered previously unappreciated roles for Sir1, a silencing establishment 44 factor, in the maintenance and/or inheritance of silencing. In addition, we identified the 45 sirtuin Hst3 and its histone target as contributors to the stability of the silenced state. 46 These approaches revealed dynamics of a heterochromatin function that have been 47 heretofore inaccessible.
Analysis of video transmission over lossy channels

A theoretical analysis of the overall mean squared error (MSE) in hybrid video coding is presented for the case of error prone transmission. Our model covers the complete transmission system including the rate-distortion performance of the video encoder, forward error correction, interleaving, and the effect of error concealment and interframe error propagation at the video decoder. The channel model used is a 2-state Markov model describing burst errors on the symbol level. Reed-Solomon codes are used for forward error correction. Extensive simulation results using an H.263 video codec are provided for verification. Using the model, the optimal tradeoff between INTRA and INTER coding as well as the optimal channel code rate can be determined for given channel parameters by minimizing the expected MSE at the decoder. The main focus of this paper is to show the accuracy of the derived analytical model and its applicability to the analysis and optimization of an entire video transmission system.
Optimization of migration downtime of virtual machines in cloud

Virtualization technology, being the most effective solution to the resource management of cloud computing, excels in it is virtual machine real-time migration technology. One key issue of live migration of virtual machine is how to quickly and transparently migrate virtual machines to meet Service Level Agreements (S LAs). In this paper an improved time-series based precopy approach technique is proposed. With the time-series prediction technique, frequently updated dirty pages (high dirty pages) are identified more precisely, and transmit them in the last round of iteration, in order to reduce unnecessary, repeated transmission of dirty pages. Doing so can significantly reduce the total migration time.
Automatic Expression Recognition Technique Using 2-D DCT and Eigen Vectors Based Neural Network

Facial expression recognition has attracted much attention in recent years becau se of its importance in realizing highly intelligent human-machine interfaces. In this paper, we propose a new facial expression recognition technique that utilizes the 2 -D DCT of full size facial images and eigenvectors based feed forward neu ral network. The neu ral network is designated to separate group of facial expressions with members "happy", "surprise", "anger", "shock", "disgust" and "sadness". This work is the first trial to use feed forward neural network, eigenvectors and 2-D DCT simultaneously within a single recognition task. To demonstrate the capability of the proposed recognition technique, we use two databases, including a recently constructed one, which contain 2 -D front face images of 120 men and 80 women, respectively. Experimental results reveal that the new technique outperforms, on the whole, the simple vector matching and K-means based vector matching techniques and two recently developed methods u sing fixed size and constructive neu ral networks. The mean recognition rates of the new technique have been found as high as 98.5% and 95.8% for these two databases, respectively, which are the best results among those obtained for the same databases.
How to implement effective prediction and forwarding for fusable dynamic multicore architectures

Dynamic multicore architectures, that fuse and split cores at run time, potentially offer a level of performance/energy agility that static multicore designs cannot achieve. Conventional ISAs, however, have scalability limits to fusion. EDGE-based designs offer greater scalability but to date have been performance limited by significant microarchitectural bottlenecks. This paper addresses these issues and makes three major contributions. First, it proposes Iterative Path Prediction to address low next block prediction accuracy and low speculation rates. It achieves close to taken/not-taken prediction accuracy for multi-exit instruction blocks while also speculating the predicated execution path within the block. Second, the paper proposes Exposed Operand Broadcasts to address the overhead of operand delivery for high fanout instructions by exposing a small number of broadcast operands in the ISA. Third, we present a scalable composable architecture called T3 that uses these mechanisms and show it can operate across a wide range of power and performance spectrum by increasing energy efficiency and performance significantly. Compared to previous EDGE designs, T3 improves energy efficiency by about 2x and performance by up to 50%.
Design and implementation of software-managed caches for multicores with local memory

Heterogeneous multicores, such as Cell BE processors and GPGPUs, typically do not have caches for their accelerator cores because coherence traffic, cache misses, and latencies from different types of memory accesses add overhead and adversely affect instruction scheduling. Instead, the accelerator cores have internal local memory to place their code and data. Programmers of such heterogeneous multicore architectures must explicitly manage data transfers between the local memory of a core and the globally shared main memory. This is a tedious and errorprone programming task. A software-managed cache (SMC), implemented in local memory, can be programmed to automatically handle data transfers at runtime, thus simplifying the task of the programmer. In this paper, we propose a new software-managed cache design, called extended set-index cache (ESC). It has the benefits of both set-associative and fully associative caches. Its tag search speed is comparable to the set-associative cache and its miss rate is comparable to the fully associative cache. We examine various line replacement policies for SMCs, and discuss their trade-offs. In addition, we propose adaptive execution strategies that select the optimal cache line size and replacement policy for each program region at runtime. To evaluate the effectiveness of our approach, we implement the ESC and other SMC designs on the Cell BE architecture, and measure their performance with 8 OpenMP applications. The evaluation results show that the ESC outperforms other SMC designs. The results also show that our adaptive execution strategies work well with the ESC. In fact, our approach is applicable to all cores with access to both local and global memory in a multicore architecture.
Analysis of Optimizations of Angluin ’ s L ∗ Machine Learning Algorithm

This paper provides the results of a study conducted on various versions and optimizations of Angluin’s L∗ learning algorithm. Tests were done on randomly generated DFAs and prefix-closed DFAs using both the original algorithm, and an optimized version under several different conditions. Results were analyzed in terms of queries and counter examples used, as well as overall run time. The optimized algorithm consistently outperforms the original in terms of queries and run time, and even outdoes an optimization made specifically for prefixclosed machines presented in a previous study.
Genome-wide profiling of genetic variation in Agrobacterium-transformed rice plants

中文概要目 的揭示转基因水稻全基因组遗传变异的特征与频率。 创新点通过单核苷酸分辨率揭示了农杆菌介导法转化水 稻植株全基因组水平遗传变异的类型和频率以 及外源DNA 的整合模式。 方 法应用Illumina Hiseq2000 高通量测序技术测定了 5 个T0 代转基因水稻株系的基因组序列。 结合生 物信息学分析和聚合酶链反应(PCR)扩增, 以 及Sanger 测序, 我们检测和验证单核苷酸多态 性(SNP)和Indel 变化类型和数量, 转移DNA (T-DNA) 及其载体骨架序列和转座子整合位点 及特征, 大片段的结构变异等遗传变异。 结 论结果表明, 农杆菌介导的水稻遗传转化, 除T-DNA 整合到水稻基因组外, 还存在载体骨架整合现 象; 每个转基因水稻基因组的变异(SNP 和小片 段的缺失插入)数目为338–1774, 与报道的组 培过程中产生的变异类似; 转基因水稻基因组仅 存在Tos17 转座子数量的变化, 未检测到其他转 座子数目和位置的变化。
Pose-Robust 3D Facial Landmark Estimation from a Single 2D Image

An algorithm is presented that estimates 3D facial landmark coordinates and occlusion state from a single 2D image. Unlike previous approaches, we divide the 3D cascaded shape regression problem into a set of viewpoint domains, which helps avoid problems in the optimization, such as local minima at test time, and averaging conflicting gradient directions in the domain maps during training. These problems are especially important to address in the 3D case, where a wider range of head poses is expected. Parametric shape models are used and are shown to have several desirable qualities compared to the recent trend of modeling shape nonparametrically. Results show quantitatively that our approach is significantly more accurate than recent work.
The Bees Algorithm for the Vehicle Routing Problem

In this thesis we present a new algorithm for the Vehicle Routing Problem called the Enhanced Bees Algorithm. It is adapted from a fairly recent algorithm, the Bees Algorithm, which was developed for continuous optimisation problems. We show that the results obtained by the Enhanced Bees Algorithm are competitive with the best meta-heuristics available for the Vehicle Routing Problem (within 0.5% of the optimal solution for common benchmark problems). We show that the algorithm has good runtime performance, producing results within 2% of the optimal solution within 60 seconds, making it suitable for use within real world dispatch scenarios.
Diffusion Approximation for an Overloaded X Model Via an Averaging Principle

In previous papers we developed a deterministic fluid approximation for an overloaded Markovian queueing system having two customer classes and two service pools, known in the call-center literature as the X model. The system uses the fixed-queue-ratio-withthresholds (FQR-T) control, which we proposed in a recent paper as a way for one service system to help another in face of an unexpected overload. Under FQR-T, customers are served by their own service pool until a threshold is exceeded. Then, one-way sharing is activated with customers from one class allowed to be served in both pools. The control aims to keep the two queues at a pre-specified fixed ratio. We supported the fluid approximation by establishing a manyserver heavy-traffic functional weak law of large numbers (FWLLN) involving an averaging principle. In this paper we develop a refined diffusion approximation for the same model based on a many-server heavy-traffic functional central limit theorem (FCLT).
Common Variation in ISL1 Confers Genetic Susceptibility for Human Congenital Heart Disease

Congenital heart disease (CHD) is the most common birth abnormality and the etiology is unknown in the overwhelming majority of cases. ISLET1 (ISL1) is a transcription factor that marks cardiac progenitor cells and generates diverse multipotent cardiovascular cell lineages. The fundamental role of ISL1 in cardiac morphogenesis makes this an exceptional candidate gene to consider as a cause of complex congenital heart disease. We evaluated whether genetic variation in ISL1 fits the common variant–common disease hypothesis. A 2-stage case-control study examined 27 polymorphisms mapping to the ISL1 locus in 300 patients with complex congenital heart disease and 2,201 healthy pediatric controls. Eight genic and flanking ISL1 SNPs were significantly associated with complex congenital heart disease. A replication study analyzed these candidate SNPs in 1,044 new cases and 3,934 independent controls and confirmed that genetic variation in ISL1 is associated with risk of non-syndromic congenital heart disease. Our results demonstrate that two different ISL1 haplotypes contribute to risk of CHD in white and black/African American populations.
Lesion evidence for the critical role of the intraparietal sulcus in spatial attention.

Based on lesion mapping studies, the inferior parietal lobule and temporoparietal junction are considered the critical parietal regions for spatial-attentional deficits. Lesion evidence for a key role of the intraparietal sulcus, a region featuring prominently in non-human primate studies and human functional imaging studies of the intact brain, is still lacking, probably due to the exceptional nature of isolated intraparietal sulcus lesions. We combined behavioural testing and functional imaging in two patients with a focal intraparietal sulcus lesion sparing the inferior parietal lobule and temporoparietal junction to examine the critical contribution of the intraparietal sulcus to spatial attention. Case H.H. had a focal ischaemic lesion (1.8 cm3) that was confined to the posterior segment of the left intraparietal sulcus, whereas Case N.V. had a partially reversible lesion of the middle segment of the right intraparietal sulcus extending into the superior parietal lobule (13.8 cm3). The performance of these cases was contrasted with five cases with a classical inferior parietal lesion, as well as with a group of 31 age-matched controls. In the behavioural study, the patients performed an orientation discrimination task on a peripheral target (eccentricity 7.6°) that was preceded by a central spatial cue. We manipulated both the cue validity (17% trials with an invalid spatial cue) and the presence of a competing distracter in the visual field contralateral to the target (17% double stimulation trials). The ability of the patients with an intraparietal sulcus lesion to reorient their spatial focus of attention and to select between competing stimuli was impaired for contralesional targets compared with controls, similarly to what we saw in the inferior parietal group. Furthermore, we could observe that the deficit in Case N.V. resolved with regression of the lesion. To further evaluate the correspondence between spatial-attentional deficits and the intraparietal sulcus lesions, we ascertained the functional integrity of the inferior parietal lobule and temporoparietal junction in Case H.H. using event-related functional magnetic resonance imaging with the same task as in the behavioural study. The intraparietal sulcus lesion of this patient did not affect the task-related activation of the inferior parietal lobule or temporoparietal junction. Additionally, a resting-state functional magnetic resonance imaging study in Case H.H. and 62 controls revealed that the lesion in Case H.H. did not affect the topology of the ventral attention network nor the strength of its main inter- and intrahemispheric connections. Our findings demonstrate that the human superior parietal cortex critically contributes to spatially selective attention.
The Effect of Exertion on Heart Rate and Rating of Perceived Exertion in Acutely Concussed Individuals

Objective Research suggests that one physiological effect of concussion is a disruption in regulation of autonomic nervous system control that affects the balance between parasympathetic and sympathetic output. While changes in heart rate after concussion have been observed, the nature of the heart rate change during progressive exercise has not been well evaluated in acutely symptomatic patients. Additionally, little is known about the relationship between HR and RPE in this population. Methods We compared changes in heart rate and perceived effort during graded treadmill exertion in recently concussed patients to elucidate the effect of brain injury on cardiovascular response to exercise. Resting HR, HR on exercise initiation, and changes in HR and RPE during the Buffalo Concussion Treadmill Test (BCTT) were compared on two test visits: When patients were symptomatic (acute) and after recovery. Results were compared with the test-retest results obtained from a control group consisting of healthy, non-concussed individuals. Results Patients had a significantly lower HR at onset of exercise when acutely concussed as compared to when recovered and reported greater perceived exertion at every exercise intensity level when symptomatic, despite exercising at lower workloads, than when recovered. Sympathetic response to increased exertion was not affected by concussion - HR increased in response to exercise at a comparable rate in both tests. These differences observed in response to exercise between the first BCTT and follow-up evaluation in initially concussed patients were not present in non-concussed individuals. Conclusion Our results suggest that during the acute phase after concussion, acutely concussed patients demonstrated an impaired ability to shift from parasympathetic to sympathetic control over heart rate at the onset of exercise. Changes in the autonomic nervous system after concussion may be more complex than previously reported. Continued evaluation of autonomic regulatory effects in the acute phase after concussion is warranted.