Miracle-dz/UniFAR-FTUs huggingface dataset:
BilRC: An Execution Triggered Coarse Grained Reconfigurable Architecture

We present Bilkent reconfigurable computer (BilRC), a new coarse-grained reconfigurable architecture (CGRA) employing an execution-triggering mechanism. A control data flow graph language is presented for mapping the applications to BilRC. The flexibility of the architecture and the computation model are validated by mapping several real-world applications. The same language is also used to map applications to a 90-nm field-programmable gate array (FPGA), giving exactly the same cycle count performance. It is found that BilRC reduces the configuration size about 33 times. It is synthesized with 90-nm technology, and typical applications mapped on BilRC run about 2.5 times faster than those on FPGA. It is found that the cycle counts of the applications for a commercial very long instruction word digital signal processor processor are 1.9 to 15 times higher than that of BilRC. It is also found that BilRC can run the inverse discrete cosine transform algorithm almost 3 times faster than the closest CGRA in terms of cycle count. Although the area required for BilRC processing elements is larger than that of existing CGRAs, this is mainly due to the segmented interconnect architecture of BilRC, which is crucial for supporting a broad range of applications.
Camera rotation estimation using 3D mesh surfaces representation of spherical images

This paper presents a novel rotation estimation approach based on 3D mesh representation of spherical images. Indeed, unit sphere is becoming a natural space for projecting images captured from the central cameras (conventional and non-conventional cameras, as omnidirectional camera) and obtaining the spherical images. The proposed method relies on representing the spherical images into a 3D space based on image intensities. Spherical harmonic coefficients are then calculated for the 3D mesh surfaces and used to estimate an initial rotation between the underlying spherical images in spectral domain. The optimal rotation is then refined through the ICP algorithm. Experimental results, using synthetic and real image dataset, demonstrate the effectiveness of the proposed approach for rotation estimation, as well as its robustness against real conditions and images occlusion. A comparison between the proposed method and competitive ones, is performed.
An Immune-Genetic Algorithm for Dynamic Job-Shop Scheduling

An immune genetic algorithm (IGA) was proposed for dynamic job-shop scheduling. By introducing mechanism of immunity into genetic algorithm, such as injecting vaccines and controlling antibody-concentration, the problems on easy appeared precocity and low searching efficiency were avoided. Taking account of the capacity of machines, the algorithm can deal with the problem of job-shop dynamic scheduling or rescheduling. Also, for lessening calculation time, parameters of IGA were gained by vast tests based on known researches. By appointing a new scheduling-time or releasing the resources of machines, the algorithm ensured the consistency to the rescheduling. At last, one instance was analyzed and realized to show that the result of the scheduling is reliable
Post-Error Adjustments

When our brain detects an error, this process changes how we react on ensuing trials. People show post-error adaptations, potentially to improve their performance in the near future. At least three types of behavioral post-error adjustments have been observed. These are post-error slowing (PES), post-error reduction of interference, and post-error improvement in accuracy (PIA). Apart from these behavioral changes, post-error adaptations have also been observed on a neuronal level with functional magnetic resonance imaging and electroencephalography. Neuronal post-error adaptations comprise activity increase in task-relevant brain areas, activity decrease in distracter-encoding brain areas, activity modulations in the motor system, and mid-frontal theta power increases. Here, we review the current literature with respect to these post-error adjustments, discuss under which circumstances these adjustments can be observed, and whether the different types of adjustments are linked to each other. We also evaluate different approaches for explaining the functional role of PES. In addition, we report reanalyzed and follow-up data from a flanker task and a moving dots interference task showing (1) that PES and PIA are not necessarily correlated, (2) that PES depends on the response–stimulus interval, and (3) that PES is reliable on a within-subject level over periods as long as several months.
Approximating Continuous Functions by ReLU Nets of Minimal Width

This article concerns the expressive power of depth in deep feed-forward neural nets with ReLU activations. Specifically, we answer the following question: for a fixed $d\geq 1,$ what is the minimal width $w$ so that neural nets with ReLU activations, input dimension $d$, hidden layer widths at most $w,$ and arbitrary depth can approximate any continuous function of $d$ variables arbitrarily well. It turns out that this minimal width is exactly equal to $d+1. $ That is, if all the hidden layer widths are bounded by $d$, then even in the infinite depth limit, ReLU nets can only express a very limited class of functions. On the other hand, we show that any continuous function on the $d$-dimensional unit cube can be approximated to arbitrary precision by ReLU nets in which all hidden layers have width exactly $d+1. $ Our construction gives quantitative depth estimates for such an approximation.
Cycles Intersecting Edge-Cuts of Prescribed Sizes

We prove that every cubic bridgeless graph $G$ contains a $2$-factor which intersects all (minimal) edge-cuts of size $3$ or $4$. This generalizes an earlier result of the authors, namely that such a $2$-factor exists provided that $G$ is planar. As a further extension, we show that every graph contains a cycle (a union of edge-disjoint circuits) that intersects all edge-cuts of size $3$ or $4$. Motivated by this result, we introduce the concept of a coverable set of integers and discuss a number of questions, some of which are related to classical problems of graph theory such as Tutte's $4$-flow conjecture and the Dominating Cycle Conjecture.
Low-Cost Hardening of Image Processing Applications Against Soft Errors

Image processing systems are increasingly used in safety-critical applications, and their hardening against soft errors becomes an issue. The authors propose a methodology to identify soft errors as uncritical based on their impact on the system's functionality. The authors call a soft error uncritical if its impact is provably limited to image perturbations during a very short period of time (number of cycles) and the system is guaranteed to recover thereafter. Uncritical errors do not require hardening as their effects are unperceivable for the human user of the system. The authors focus on soft errors in the motion estimation subsystem of MPEG-2 and introduce different definitions of uncritical soft errors in that subsystem. A method is proposed to automatically determine uncritical errors and provide experimental results for various parameters. The concept can be adapted to further systems and enhance existing methods
Information content versus word length in random typing

Recently, it has been claimed that a linear relationship between a measure of information content and word length is expected from word length optimization and it has been shown that this linearity is supported by a strong correlation between information content and word length in many languages (Piantadosi et al 2011 Proc. Nat. Acad. Sci. 108 3825). Here, we study in detail some connections between this measure and standard information theory. The relationship between the measure and word length is studied for the popular random typing process where a text is constructed by pressing keys at random from a keyboard containing letters and a space behaving as a word delimiter. Although this random process does not optimize word lengths according to information content, it exhibits a linear relationship between information content and word length. The exact slope and intercept are presented for three major variants of the random typing process. A strong correlation between information content and word length can simply arise from the units making a word (e.g., letters) and not necessarily from the interplay between a word and its context as proposed by Piantadosi and co-workers. In itself, the linear relation does not entail the results of any optimization process.
A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment

In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment.
Implementation of Context Aware e-Health Environments Based on Social Sensor Networks

In this work, context aware scenarios applied to e-Health and m-Health in the framework of typical households (urban and rural) by means of deploying Social Sensors will be described. Interaction with end-users and social/medical staff is achieved using a multi-signal input/output device, capable of sensing and transmitting environmental, biomedical or activity signals and information with the aid of a combined Bluetooth and Mobile system platform. The devices, which play the role of Social Sensors, are implemented and tested in order to guarantee adequate service levels in terms of multiple signal processing tasks as well as robustness in relation with the use wireless transceivers and channel variability. Initial tests within a Living Lab environment have been performed in order to validate overall system operation. The results obtained show good acceptance of the proposed system both by end users as well as by medical and social staff, increasing interaction, reducing overall response time and social inclusion levels, with a compact and moderate cost solution that can readily be largely deployed.
Chapter 3 Magnetic Resonance Imaging of Brain Function 3 . 1 Introduction to Neuroimaging

The idea of localisation of function within the brain has only been accepted for the last century and a half. In the early 19th century Gall and Spurzheim, were ostracised by the scientific community for their so-called science of phrenology[1]. They suggested that there were twenty-seven separate organs in the brain, governing various moral, sexual and intellectual traits. The importance of each to the individual was determined by feeling the bumps on their skull. The science behind this may have been flawed, but it first introduced the idea of functional localisation within the brain which was developed from the mid 1800’s onwards by clinicians such as Jackson [2] and Broca[3]. Most of the information available on the human brain came from subjects who had sustained major head wounds, or who suffered from various mental disorders[4]. By determining the extent of brain damage, and the nature of the loss of function, it was possible to infer which regions of the brain were responsible for which function.
Universität Des Saarlandes Fachrichtung 6.1 – Mathematik a Tv Flow Based Local Scale Estimate and Its Application to Texture Discrimination a Tv Flow Based Local Scale Estimate and Its Application to Texture Discrimination

This paper presents a local region based scale measure, which exploits properties of a certain type of nonlinear diffusion, the so-called total variation (TV) flow. During the signal evolution by means of TV flow, pixels change their value with a speed that is inversely proportional to the size of the region they belong to. From this evolution speed one can derive a local scale estimate based on regions instead of derivative filters. Main motivation for such a scale measure is its application to texture discrimination, in particular the construction of an alternative to Gabor filters. When the scale estimate is combined with the components of the structure tensor, which provides orientation information, it yields a texture feature space of only four dimensions. Like Gabor features , this sparse feature space discriminates textures by means of their orientation and scale, yet the representation of orientation and scale is less redundant. The quality of the feature space containing the new scale measure is evaluated in texture segmentation experiments by comparing results to those achieved with Gabor filters. It turns out that one can gain a total speedup of factor 2 without loosing any quality concerning the discrimination of textures.
Joint power allocation and subcarrier assignment for two-way OFDM multi-relay system

In this paper, we investigate a joint resource allocation problem for two-way OFDM multi-relay network, where two transceivers exchange OFDM signal with the help of multiple relays. Considering a constraint on the total transmit power consumed in the whole network, the assignment of subcarriers to multiple relays and power allocation at both transceivers as well as relays are jointly optimized to maximize the sum-rate. The maximization problem turns out a mixed integer programming problem, which can be asymptotically solved through Lagrange dual decomposition approach. Further, we propose a suboptimal algorithm to trade off performance for complexity. Finally, simulation results are provided to demonstrate the performance gain of the proposed algorithms.
Modelling the Forming Limit during Cross‐Rolling of Seamless Pipes Using a Modified Continuum Damage Mechanics Approach

For the production of seamless pipes it is necessary to pierce a round solid billet in the first forming operation. In the subsequent processing steps the hollow is elongated at the push bench and annealed. The seamless pipe gets its final dimension in the stretch reducing mill. For a realistic description of material failure during hot forming using Forge®2008, the validation of the finite element model was the first step in this study. Since the used damage variable is of dimensionless type, special focus was laid on the correct calculation of the deformation path during piercing. It could be shown that a correct calculation of the geometry and the resulting forces is possible using the developed model. After a summary of previous studies this work focuses on the piercing operation in order to picture a real piercing process using damage mechanics. A modified continuum damage mechanics approach is presented, which enables the reduction of the damage parameter at negative stress triaxialities. This is obvious since a decrease of pores and cavities at hot forming conditions and negative triaxialities, e.g. cogging, is generally observed.
A Full-Sky Hα Template for Microwave Foreground Prediction

A full-sky Hα map with 6′ (FWHM) resolution is presented. This map is a composite of the Virginia Tech Spectral line Survey (VTSS) in the north and the Southern H-Alpha Sky Survey Atlas (SHASSA) in the south. The Wisconsin H-Alpha Mapper (WHAM) survey provides a stable zero point over 3/4 of the sky on a 1° scale. This composite map can be used to provide limits on thermal bremsstrahlung (free-free emission) from ionized gas known to contaminate microwave-background data. The map is available on the World Wide Web for public use.
THE ORIGIN OF SORGHUM BICOLOR. II. DISTRIBUTION AND DOMESTICATION

The complex species Sorghum bicolor (Linn.) Moench (Gramineae) includes all cultivated sorghums as well as a group of semiwild plants mostly associated with them as weeds. The extent of morphological variation within S. bicolor is so tremendous that Snowden (1936, 1955) subdivided this complex into 28 cultivated and 24 related wild “species. ” However, lack of genetic barriers between these taxa indicates that they all belong to a single species (de Wet, 1967). Very little is known about the antiquity of sorghum (Doggett, 1965). This crop is absent from the ancient tombs of Egypt and from excavated early farming sites in the Near East. Although Hrozny (1913) suggested that the word “Dohan” in the Hebrew text of the book of Ezekiel (Chapter IV, verse 9 ) may refer to sorghum, it is more likely that this millet was Setaria or Panicum. Even in modern Turkish, “darri or durra” (Arabic “dochan”) means only millet and requires an adjective to define the kind of millet. Conclusive archeological evidence of prehistoric sorghum cultivation is absent. The often cited carved reliefs of sorghum on a limestone slab which formed part of the palace of Sennacherib a t Ninevah (Piedallu, 1923) most likely does not depict sorghum, but the common reed Phragmites communis (Hall, 1928, plates 3 0 and 33) . As archeological data and historical records of early sorghum cultivation are almost completely lacking, conclusions on the
RAIN: Social Role-Aware Information Diffusion

Information diffusion, which studies how information is propagated in social networks, has attracted considerable research effort recently. However, most existing approaches do not distinguish social roles that nodes may play in the diffusion process. In this paper, we study the interplay between users' social roles and their influence on information diffusion. We propose a Role-Aware INformation diffusion model (RAIN) that integrates social role recognition and diffusion modeling into a unified framework. We develop a Gibbs-sampling based algorithm to learn the proposed model using historical diffusion data. The proposed model can be applied to different scenarios. For instance, at the micro-level, the proposed model can be used to predict whether an individual user will repost a specific message; while at the macro-level, we can use the model to predict the scale and the duration of a diffusion process. We evaluate the proposed model on a real social media data set. Our model performs much better in both micro- and macro-level prediction than several alternative methods.
Checking memory safety of level 1 safety-critical Java programs using static-analysis without annotations

Safety-Critical Java (SCJ) has been designed specifically to ring performance and reliability to the development of safety-critical Java programs. SCJ introduces a novel programming paradigm based on missions and handlers, and has been designed to ease certification. One of the distinguishing features of SCJ is its memory model, which is defined as a hierarchical structure of scoped-based memory areas. Unlike in Java programs, memory management is an important concern under the control of the programmer in SCJ; it is not sufficient to write a program that conforms to the specification as memory safety may still be broken. By using static analysis techniques, it is possible to identify errors in programs before they are executed. Analysing at the source-code level allows for a precise analysis that abstracts away from machine details and unnecessary program details. As the SCJ paradigm is different to that of Java, it is not possible to apply existing tools and techniques for Java programs to SCJ. This thesis describes a new static-checking technique for a comprehensive subset of SCJ programs (comparable to Ravenscar Ada) that automatically checks for memory-safety violations at the source-code level without the need for user-added annotations. An abstract language (SCJ-mSafe) is used to describe the aspects of SCJ programs required to check memory safety, and a set of inference rules define what it means for each aspect to be memory safe. By using a points-to environment and automatically-generated method properties, it is possible to produce a model of the execution of an SCJ program that can identify possible memory-safety violations at each point in the execution. The whole process has been automated with tool support and compared against other techniques. A worst-case analysis is performed that can give false negatives.
The aspartyl protease DDI2 activates Nrf1 to compensate for proteasome dysfunction

In response to proteasome dysfunction, mammalian cells upregulate proteasome gene expression by activating Nrf1. Nrf1 is an endoplasmic reticulum-resident transcription factor that is continually retrotranslocated and degraded by the proteasome. Upon proteasome inhibition, Nrf1 escapes degradation and is cleaved to become active. However, the processing enzyme for Nrf1 remains obscure. Here we show that the aspartyl protease DNA-damage inducible 1 homolog 2 (DDI2) is required to cleave and activate Nrf1. Deletion of DDI2 reduced the cleaved form of Nrf1 and increased the full-length cytosolic form of Nrf1, resulting in poor upregulation of proteasomes in response to proteasome inhibition. These defects were restored by adding back wild-type DDI2 but not protease-defective DDI2. Our results provide a clue for blocking compensatory proteasome synthesis to improve cancer therapies targeting proteasomes. DOI: http://dx.doi. org/10.7554/eLife.18357. 001
Electrospinning technology applied in zeolitic imidazolate framework membrane synthesis

For the first time, an electrospinning technique has been introduced into the synthesis of supported microporous membranes. This new approach is suitable for various substrates, especially tubes, with the possibility of large-area processing. We can precisely control the thickness of the seed layer and obtain a continuous and uniform seed coating on the support surface. The zeolite imidazolate framework-8 was selected as a candidate to demonstrate the effectiveness of this method, by which, defect-free and well-intergrown ZIF-8 membranes have been successfully synthesized. Single gas permeance of H2, N2, CH4, CO2 and binary mixtures experiments for H2–CO2, H2–CH4, H2–N2 were carried out. The results indicated that the ZIF-8 membrane prepared through this new approach had better H2 selectivity and gas permeability.