Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvements in Image Segmentation by Applying Hopfield Neural Networks

Hundreds of algorithms for different aspects of image segmentation have been developed. In this paper goals of using segmentation in video and multimedia systems are considered. Thus direction of improvements is towards forming masks and matte signals. The idea is to spread locally dominant segment in already segmented image. This problem is set as optimization problem and solution can be achieved by Hopfield neural network. Presented results are obtained applied to color detected segmentation, performed by mean shift algorithm
Scalable OCS-based intra/inter data center network with optical ToR switches

Optically switched networks have potential for high scalability, low power-consumption and increased bandwidth capacity and are considered a promising solution to overcome the bottlenecks in traditional Data Center Networks (DCNs) powered by electronic switches. Even though the major share of power consumption occurs in the edge tier, most of the proposals for future DCNs have concentrated on optical switching in the core layer but designing an optical network that can interconnect a warehouse scale data center is still not fully feasible. In this paper, we propose an optical Top of Rack (ToR) switch that can substantially minimise energy consumption and can be interconnected within the DCN through a mega optical space switch (OSS), based on a non-blocking Clos network, which can satisfy future scalability demands. This architecture can connect servers through a combination of optical cross-connects and WDM rings and establish optical connections between servers in multiple DCNs in a metro area.
A UML Profile for Automated Behavior Processes in ODP Enterprise Language

ODP system is determined by the collection of all the possible actions in which the system (acting as an object), or any of its constituent objects, might take part, together with a set of constraints on when these actions can occur. In order to specify the executable behavior of a system and to make the processes of the enterprise executable and controllable, the Reference Model for ODP RM-ODP can be used as a meta-model for behavioral specifications. In the enterprise language the behavior is specified in terms of roles, processes, policies, and the relationships between these concepts. Firstly, we give the description and specification of the behavior by the activity diagrams. Secondly, we define the mapping from the concepts of behavior enterprise language to BPEL concepts and we present the syntax and the structure of a BPEL Behavior process. Then we generate the corresponding BPEL and computational files to implement the specified process.
VHDL Implementation of AES-128

Security has become an increasingly important feature with the growth of electronic communication. The Symmetric in which the same key value is used in both the encryption and decryption calculations are becoming more popular. The AES algorithm is capable of using cryptographic keys of 128, 192, and 256 bits to encrypt and decrypt data in blocks of 128 bits. This standard is based on the Rijndael algorithm. In this project our main concern is to implement all modules of this algorithm on hardware.This methodology uses VHDL implementation of all the modules in terms of Delay
SURFACE at Syracuse University SURFACE at Syracuse University

We propose the sharp identifiable bounds of the distribution functions of potential outcomes using a panel with fixed T. We allow for the possibility that the statistical randomization of treatment assignments is not achieved until unobserved heterogeneity is properly controlled for. We use certain stationarity assumptions to obtain the bounds. Dynamics in the treatment decisions is allowed as long as the stationarity assumptions are satisfied. In particular, we present an example where our assumptions are satisfied and the treatment decision of the present time may depend on the treatments and the observed outcomes of the past. As an empirical illustration we study the effect of smoking during pregnancy on infant birth weights. We found that for the group of switchers the birth weight with smoking is first order stochastically dominated by that with non-smoking.
Estimation of Galactic Model Parameters in High Latitudes with SDSS

Abstract We estimated the Galactic model parameters for a set of 36 high-latitude fields included in the currently available Data Release 5 (DR 5) of the Sloan Digital Sky Survey (SDSS), to explore their possible variation with the Galactic longitude. The thick disc scaleheight moves from ∼550 pc at 120 < l < 150° to ∼720 pc at 250 < l < 290°, while the thin disc scaleheight is as large as ∼195 pc in the anticenter direction and ∼15% lower at |l| < 30°. Finally, the axis ratio (c/a) of the halo changes from a mean value of ∼0.55 in the two first quadrants of the Galaxy to ∼0.70 at 190 < l < 300°. For the halo, the reason for the dependence of the model parameters on the Galactic longitude arises from the well known asymmetric structure of this component. However, the variation of the model parameters of the thin and thick discs with Galactic longitude originates from the gravitational effect of the Galactic long bar. Moreover, the excess of stars in quadrant I (quadrant III) over quadrant IV (quadrant II) is in agreement with this scenario.
Rendering cubic curves and surfaces with integer adaptive forward differencing

For most compute environments, adaptive forward differencing is much more efficient when performed using integer arithmetic than when using floating point. Previously low precision integer methods suffered from serious precision problems due to the error accumulation inherent to forward differencing techniques. This paper proposes several different techniques for implementing adaptive forward differencing using integer arithmetic, and provides an error analysis of forward differencing which is useful as a guide for integer AFD implementation. The proposed technique using 32 bit integer values is capable of rendering curves having more than 4K forward steps with an accumulated error of less than one pixel and no overflow problems. A hybrid algorithm employing integer AFD is proposed for rendering antialiased, texture-mapped bicubic surfaces.
Approaches to Brain Stress Testing: BOLD Magnetic Resonance Imaging with Computer-Controlled Delivery of Carbon Dioxide

Background An impaired vascular response in the brain regionally may indicate reduced vascular reserve and vulnerability to ischemic injury. Changing the carbon dioxide (CO2) tension in arterial blood is commonly used as a cerebral vasoactive stimulus to assess the cerebral vascular response, changing cerebral blood flow (CBF) by up to 5–11 percent/mmHg in normal adults. Here we describe two approaches to generating the CO2 challenge using a computer-controlled gas blender to administer: i) a square wave change in CO2 and, ii) a ramp stimulus, consisting of a continuously graded change in CO2 over a range. Responses were assessed regionally by blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI). Methodology/Principal Findings We studied 8 patients with known cerebrovascular disease (carotid stenosis or occlusion) and 2 healthy subjects. The square wave stimulus was used to study the dynamics of the vascular response, while the ramp stimulus assessed the steady-state response to CO2. Cerebrovascular reactivity (CVR) maps were registered by color coding and overlaid on the anatomical scans generated with 3 Tesla MRI to assess the corresponding BOLD signal change/mmHg change in CO2, voxel-by-voxel. Using a fractal temporal approach, detrended fluctuation analysis (DFA) maps of the processed raw BOLD signal per voxel over the same CO2 range were generated. Regions of BOLD signal decrease with increased CO2 (coded blue) were seen in all of these high-risk patients, indicating regions of impaired CVR. All patients also demonstrated regions of altered signal structure on DFA maps (Hurst exponents less than 0.5; coded blue) indicative of anti-persistent noise. While ‘blue’ CVR maps remained essentially stable over the time of analysis, ‘blue’ DFA maps improved. Conclusions/Significance This combined dual stimulus and dual analysis approach may be complementary in identifying vulnerable brain regions and thus constitute a regional as well as global brain stress test.
Learning Ranking Function via Relevance Propagation 1

In this paper, we propose a novel ranking function learning framework based on relevance propagation. The propagation process is used to propagate the relevance scores from labeled documents to other unlabeled ones so that more training data are available to learn the ranking function. It is realized by the manifold ranking algorithm, which has been proved to be very effective in content-based image retrieval. We investigate two kinds of propagation schemes: intra-query propagation, which confines the propagation within the documents returned by a single query, and inter-query propagation, which allows the propagation across the documents returned by multiple queries. Inter-query propagation scheme is proved to be more effective but less efficient since the number of documents that need to be processed are huge. Thus, the intra-query propagation scheme is practically more useful and adopted in this paper. The proposed framework has two main advantages. On one hand, it can effectively utilize the unlabeled data to proliferate the training set. On the other hand, the relevance propagation process is totally independent on the learning algorithms. This property lends the framework remarkable flexibility to leverage any state-of-the-art ranking function learning algorithm. Any improvement made to either propagation or learning can improve the overall performance. Experimental results on commercial search engine data show that the framework attains a significant improvement over existing ranking function learning algorithms.
Model selection for CART regression trees

The performance of the classification and regression trees (CART) pruning algorithm and the final discrete selection by test sample as a functional estimation procedure are considered. The validation of the pruning procedure applied to Gaussian and bounded regression is of primary interest. On the one hand, the paper shows that the complexity penalty used in the pruning algorithm is valid in both cases and, on the other hand, that, conditionally to the construction of the maximal tree, the final selection does not alter dramatically the estimation accuracy of the regression function. In both cases, the risk bounds that are proved, obtained by using the penalized model selection, validate the CART algorithm which is used in many applications such as meteorology, biology, medicine, pollution monitoring, or image coding.
Integrating Biological Data Sources and Data Analysis Tools through Mediators (available online only)

We present an architecture for XML-based mediators systems and a framework for helping systems developers in the construction of mediator-services to integrate heterogeneous data sources. A unique feature of our architecture is its capability to manage user’s software tools and algorithms, modelled as Extended Value Added Services (EVASs), an integrated in the data flow. The mediator offers a view of the system as a single data source where EVASs are readily available for enhancing query processing. A web-based graphic interface has been developed to allow dynamic and flexible EVASs inter-connection, thus creating complex distributed bioinformatics machines. The feasibility and usefulness of our ideas have been validated by the development of a mediator system (BioBroker) and also by a diverse set of applications aimed at combining gene expression data with genomic, sequence-based and structural information, so as to provide a general, transparent and powerful solution, that integrating data analysis tools and algorithms goes beyond traditional gene expression data clustering mediators developed so far.
Statistical learning models of sensory processing and implications of biological constraints

Author(s): Dodds, Eric McVoy | Advisor(s): DeWeese, Michael R | Abstract: Despite progress in understanding the organization and function of neural sensory systems, fundamental questions remain about how organisms convert visual, auditory, and other sensory input into useful representations to understand the world and guide behavior. An important and fruitful line of work models the brain as an unsupervised statistical learner, examining how a sensory system may optimize for efficient representation of the natural environment or for explicit representation of useful structure in that environment. This dissertation explores efficient coding and sparse coding models of the visual and auditory systems, the data these systems process, and how these models are affected by the constraints imposed by implementation in biological neural systems. First, I show that both natural images and natural sounds have statistical structure amenable to a sparse coding model but that the sparse structure of these two types of natural data also differ in interesting ways that may be relevant to extending the success of sparse coding in describing primary visual cortex (V1) to analogous regions of the auditory system. I also discuss how a related model may shed light on how the neurons in these sensory systems are organized in space based on coding for related stimulus properties. Second, I show that a sparse coding model with biological constraints requires its inputs to be whitened in order to learn sparse features using synapse-local learning rules. This observation provides a novel explanation for the separation of sparse coding and spatial decorrelation into, respectively, V1 simple cells and preceding areas including retina. Third and finally, I turn back to the auditory system and extend existing work on efficient coding in the cochlea to account for the requirement of causality, i.e., determining a code without knowledge of the future of a signal.
Norcantharidin Facilitates LPS-Mediated Immune Responses by Up-Regulation of AKT/NF-κB Signaling in Macrophages

Norcantharidin (NCTD), a demethylated analog of cantharidin, is a common used clinical drug to inhibit proliferation and metastasis of cancer cells. But the role of NCTD in modulating immune responses remains unknown. Here, we investigated the function and mechanism of NCTD in regulation of TLR4 associated immune response in macrophages. We evaluated the influence of NCTD on host defense against invaded pathogens by acute peritonitis mouse model, ELISA, Q-PCR, nitrite quantification, phagocytosis assay and gelatin zymography assay. Our data showed that the survival and the serum concentrations of IL-6 and TNF-α were all enhanced by NCTD significantly in peritonitis mouse model. Accordingly, LPS-induced cytokine, nitric oxide and MMP-9 production as well as the phagocytosis of bacteria were all up-regulated by NCTD in a dose dependent manner in both RAW264.7 cells and bone marrow-derived macrophages (BMMs). Then we further analyzed TLR4 associated signaling pathway by Western blot, Immunofluorescence and EMSA in the presence or absence of LPS. The phosphorylation of AKT and p65 at serine 536 but not serine 468 was enhanced obviously by NCTD in a dose dependent manner, whereas the degradation of IκBα was little effected. Consequently, the nuclear translocation and DNA binding ability of NF-κB was also increased by NCTD obviously in RAW264.7 cells. Our results demonstrated that NCTD could facilitate LPS-mediated immune response through promoting the phosphorylation of AKT/p65 and transcriptional activity of NF-κB, thus reprofiling the traditional anti-tumor drug NCTD as a novel immune regulator in promoting host defense against bacterial infection.
Social and Immigration-Specific Differences in the Development of Reading Comprehension: A Longitudinal Analysis of Primary School Students in Germany

According to the theory of social reproduction, parents’ cultural habits, activities, and goods have large impacts on children’s skills, knowledge, competencies, and educational attainment (Bourdieu, 1974; Bourdieu & Passeron, 1977). The cultural mobility model is less restrictive and less unidirectional than the theory of social reproduction. According to the cultural mobility model, students from lower social classes, in particular, can promote their school performance if they invest in cultural activities, thus attenuating the relation between their parents’ class position and their own school success (Aschaffenburg & Maas, 1997; DiMaggio, 1982). In recent times, the school performance of students from immigrant families has been the focus of attention. Cultural capital is often context specific
ITS1 Copy Number Varies among Batrachochytrium dendrobatidis Strains: Implications for qPCR Estimates of Infection Intensity from Field-Collected Amphibian Skin Swabs

Genomic studies of the amphibian-killing fungus (Batrachochytrium dendrobatidis, [Bd]) identified three highly divergent genetic lineages, only one of which has a global distribution. Bd strains within these linages show variable genomic content due to differential loss of heterozygosity and recombination. The current quantitative polymerase chain reaction (qPCR) protocol to detect the fungus from amphibian skin swabs targets the intergenic transcribed spacer 1 (ITS1) region using a TaqMan fluorescent probe specific to Bd. We investigated the consequences of genomic differences in the quantification of ITS1 from eight distinct Bd strains, including representatives from North America, South America, the Caribbean, and Australia. To test for potential differences in amplification, we compared qPCR standards made from Bd zoospore counts for each strain, and showed that they differ significantly in amplification rates. To test potential mechanisms leading to strain differences in qPCR reaction parameters (slope and y-intercept), we: a) compared standard curves from the same strains made from extracted Bd genomic DNA in equimolar solutions, b) quantified the number of ITS1 copies per zoospore using a standard curve made from PCR-amplicons of the ITS1 region, and c) cloned and sequenced PCR-amplified ITS1 regions from these same strains to verify the presence of the probe site in all haplotypes. We found high strain variability in ITS1 copy number, ranging from 10 to 144 copies per single zoospore. Our results indicate that genome size might explain strain differences in ITS1 copy number, but not ITS1 sequence variation because the probe-binding site and primers were conserved across all haplotypes. For standards constructed from uncharacterized Bd strains, we recommend the use of single ITS1 PCR-amplicons as the absolute standard in conjunction with current quantitative assays to inform on copy number variation and provide universal estimates of pathogen zoospore loads from field-caught amphibians.
Gradient Adaptive Lattice Algorithm Suitable for Fixed Point Implementation

The lattice-based implementations of the gradient adaptive algorithms offer improved convergence rate capabilities, especially for high correlated inputs. In the classical gradient adaptive lattice (GAL) algorithm a division operation per stage is used, which significant grows the computational complexity in a fixed-point implementation context. In this paper, an approximate version of the GAL algorithm is proposed. This algorithm replaces the division operation by three multiplication operations and one addition operation. The simulation results prove that this algorithm keeps the rate of convergence and the good numerical properties of the classical GAL algorithm.
Praktikanz als Zieldimension anwendungsorientierter Forschung

Zusammenfassung: Anwendungsorientierte Forschung sieht sich mit der doppelten Herausforderung konfrontiert, dass Innovationen nicht nur entwickelt, sondern auch implementiert, also erfolgreich zur Anwendung gebracht werden sollen. Die Technikakzeptanzforschung und beteiligungsorientierten Ansätze konzentrieren sich in diesem Zusammenhang primär auf Aspekte der Akzeptanz durch die Anwender_innen, der Bedienungsfreundlichkeit der Systeme und der Innovationsförderlichkeit der organisatorischen Rahmenbedingungen.
Updating an Existing Social Network Snapshot via a Limited API

We study the problem of graph tracking with limited information. In this paper, we focus on updating a social network snapshot. Say we have an existing partial snapshot of a network G1. Over time G1 becomes out of date. We want to update G1 through a public API, restricted by the number of API calls allowed. Periodically recrawling every node in the snapshot is prohibitively expensive. We propose a scheme where we exploit indegrees and outdegrees to discover changes to the graph. We probe the graph and verify edges when there is ambiguity. We propose a novel strategy designed for limited information that can be adapted to different levels of staleness. We evaluate our strategy against recrawling on real datasets and show that it saves an order of magnitude of API calls while introducing minimal errors.
How to Automatically and Accurately Sandbox Microsoft IIS

Comparing the system call sequence of a network application against a sandboxing policy is a popular approach to detecting control-hijacking attack, in which the attacker exploits such software vulnerabilities as buffer overflow to take over the control of a victim application and possibly the underlying machine. The long-standing technical barrier to the acceptance of this system call monitoring approach is how to derive accurate sandboxing policies for Windows applications whose source code is unavailable. In fact, many commercial computer security companies take advantage of this fact and fashion a business model in which their users have to pay a subscription fee to receive periodic updates on the application sandboxing policies, much like anti-virus signatures. This paper describes the design, implementation and evaluation of a sandboxing system called BASS that can automatically extract a highly accurate application-specific sandboxing policy from a Win32/X86 binary, and enforce the extracted policy at run time with low performance overhead. BASS is built on a binary interpretation and analysis infrastructure called BIRD, which can handle application binaries with dynamically linked libraries, exception handlers and multi-threading, and has been shown to work correctly for a large number of commercially distributed Windows-based network applications, including IIS and Apache. The throughput and latency penalty of BASS for all the applications we have tested except one is under 8%
Spectrum sensing based on the detection of fourth-order cyclic features

Recent years have shown a growing interest in the concept of cognitive radios (CR), able to access portions of the electromagnetic spectrum in an opportunistic operating way. Such systems require efficient detectors able to work in low signal-to-noise ratio (SNR) environments, with little or no information about the signals they are trying to detect. Energy detectors are wildly used to perform such blind detection tasks, but quickly reach the so-called SNR wall below which detection becomes impossible. Cyclostationarity detectors are an interesting alternative to energy detectors, as they exploit hidden periodicities present in man-made signals, but absent in noise. Such detectors use quadratic transformations of the signals to extract the hidden sine-waves. While most of the literature focuses on the second-order transformations of the signals, we investigate the potential of higher-order transformations of the signals. Using the theory of higher-order cyclostationarity (HOCS), we derive a fourth-order detector that performs similarly to the secondorder ones, while being less complex. Performance comparisons between fourth-order, second-order and energy detectors have been performed through simulations to demonstrate the interest of the fourth-order detector.