Miracle-dz/UniFAR-FTUs huggingface dataset:
On-chip debug support for embedded Systems-on-Chip

This paper presents an on-chip hardware architecture to support application software development for embedded Systems-on-Chips (SoC). This architecture provides debug support for one manufacturer's complete SoC platform. This includes a significant number of 16-bit and 32-bit microcontroller and DSP cores, spanning a multitude of application specific systems ranging from wireless systems to engine controllers. The debug support architecture is modular and can be divided into three main components: i) processor-specific debug resources, ii) a serial communication interface to connect the SoC with a debug host computer system and iii) a number of interconnection links to communicate between the serial communication interface and the processor debug resources. This modular approach allows the debug support architecture to be adapted to almost any system configuration (including multiple processor cores), while keeping the impact on silicon real estate for production devices at a minimum.
Driver behavior event detection for manual annotation by clustering of the driver physiological signals

Naturalistic driving recordings are important for understanding the driver behavior. Driver behavior events of interest in these recordings, such as driver confusion and stress, are important for studying driver behavior and develop the next generation advanced driver assistant systems (ADASs). Unfortunately, such events are rare cases in the naturalistic driving data. Manual annotation is usually required to extract such events from a large data set. This study investigates the idea of using drivers' physiological signals to help with the manual annotation process. The proposed framework uses the unsupervised cluster algorithm, density-based spatial clustering of applications with noise (DBSCAN), to cluster the physiological data into three classes: “Normal”, “Event” and “Noise”. We define three types of driver behavior events of interest in our real-world driving data, and evaluate the recall rate using the data classified in the “Event” cluster. High recall rate at 75% is achieved on average. We also evaluate the reduced effort for the annotator by estimating the viewing time compression rate, which is reduced by half when we set the fast forward rate in non “Event” segment to 5 times of normal speed.
A theory of robust omega-regular software synthesis

A key property for systems subject to uncertainty in their operating environment is robustness: ensuring that unmodeled but bounded disturbances have only a proportionally bounded effect upon the behaviors of the system. Inspired by ideas from robust control and dissipative systems theory, we present a formal definition of robustness as well as algorithmic tools for the design of optimally robust controllers for ω-regular properties on discrete transition systems. Formally, we define metric automata—automata equipped with a metric on states—and strategies on metric automata which guarantee robustness for ω-regular properties. We present fixed-point algorithms to construct optimally robust strategies in polynomial time. In contrast to strategies computed by classical graph theoretic approaches, the strategies computed by our algorithm ensure that the behaviors of the controlled system gracefully degrade under the action of disturbances; the degree of degradation is parameterized by the magnitude of the disturbance. We show an application of our theory to the design of controllers that tolerate infinitely many transient errors provided they occur infrequently enough.
The Future of Natural Gas Supplementary Paper SP 2.3 Role of Technology in Unconventional Gas Resources

Unconventional gas resources play an increasingly important role in supplying low carbon fuel for a growing energy demand. They can be classified into three categories: tight gas, coalbed methane and shale gas. Although there are differences between production behavior and the transport mechanisms governing it, common characteristics of all unconventional resources are: low permeability (less than 1 md); advanced technology is necessary for economic development; and low recovery factors (less than 10%), relative to conventional resources. Technology development has focused on increasing the amount of contact between the reservoir and the wellbore. Advances in directional drilling and hydraulic fracturing have moved low quality, unconventional gas resources to economically viable sources of natural gas. Basic scientific questions regarding transport mechanisms in these reservoirs exist. Research into understanding properties governing flow and interplay between geochemistry, rock fabric and flow will facilitate the development of technologies to reduce uncertainty in assessing the size of the resource, leading to viable science based energy policies. Through improved understanding of the subtleties of the physics governing transport in unconventional gas resources, technologies tailored to the unique production characteristics of each type of resource can be developed to improve recovery efficiency. Environmental concerns surrounding water resources and development footprint can be reduced as an additional benefit of the technologies gains associated with appropriate deployment of technology. Introduction Production performance and recovery from unconventional reservoirs are highly variable between basins and within individual plays. Due to the interdependence of geology, geochemistry, geomechanics and petrophysics on productivity and recovery, an integrated understanding of geologic controls (such as mineralogy, rock textures, depositional environment, present day and paleo stresses) is required for interpreting production behavior and predicting future success. Unconventional gas resources are considered technological plays, where successful economic development of these resources requires advanced technology (such as advanced drilling or massive hydraulic fracture treatments) to improve recovery factors and reduce costs, increasing the economic viability of the resource. This paper reviews the production characteristics of the three categories of unconventional gas resources: tight gas, coalbed methane and gas shale, and the current state of technology application in these plays. A wide range of resource types is included in this definition, making production
Contextual Expectations and Emerging Informational Harms: A Primer on Academic Library Participation in Learning Analytics Initiatives

Academic libraries have begun to consider their role in learning analytics (LA). Some librarians have expressed great optimism about data-driven analytics and the insights such practices may develop with regard to the library’s role in improving learning outcomes or increasing graduation rates. On the face of it, information systems librarians maintain and the informational products (e.g., databases and digital libraries) to which they provide students access hold data that could reveal a unique view into students’ intellectual behaviors. Such data could provide value to LA algorithms and enhance related outcomes, and institutions may seek more involvement from their librarians in aggregating and mining student data. However, these initiatives are not without moral questions. In this chapter, we hold a critical conversation about the distribution of LA benefits, whose interests library LA serves, and how informational injustices accrue to students as library users.
Realistic shading of human skin in real time

The demand for realistic human characters is driven by interactive application developers worldwide. The look of 3D models in real time graphics is efficiently improved by powerful shader techniques. Today a common technique consists of a simple lighting model combined with textures, which have precalculated illumination included. In this paper we will give an overview of the most recent techniques in skin shading. We present a multifaced implementation of shading techniques by efficiently combining various approaches. Therefore we will explain physical and anatomical backgrounds and refer to relevant papers. In our opinion, this work is a valuable reference assist shader developers in their implementations and adaptions on recent and future graphic hardware.
Spatial and temporal analysis of information processing in the ascending tectofugal visual system

Article history: Accepted 13 August 2007 Available online 24 August 2007 Neuronal response onset latency provides important data on the information processing within the central nervous system. In order to enhance the quality of the onset latency estimation, we have developed a ‘double sliding-window’ technique, which combines the advantages of mathematical methods with the reliability of standard statistical processes. This method is based on repetitive series of statistical probes between two virtual time windows. The layout of the significance curve reveals the starting points of changes in neuronal activity in the form of break-points between linear segments. A second-order difference function is applied to determine the position of maximum slope change, which corresponds to the onset of the response. In comparison with Poisson spike-train analysis, the cumulative sum technique and themethod of Falzett et al., this ‘double sliding-window, technique seems to be a more accurate automated procedure to calculate the response onset latency of a broad range of neuronal response characteristics. © 2007 Elsevier B.V. All rights reserved.
Whole body MRI: Improved Lesion Detection and Characterization With Diffusion Weighted Techniques

Diffusion‐weighted imaging (DWI) is an established functional imaging technique that interrogates the delicate balance of water movement at the cellular level. Technological advances enable this technique to be applied to whole‐body MRI. Theory, b‐value selection, common artifacts and target to background for optimized viewing will be reviewed for applications in the neck, chest, abdomen, and pelvis. Whole‐body imaging with DWI allows novel applications of MRI to aid in evaluation of conditions such as multiple myeloma, lymphoma, and skeletal metastases, while the quantitative nature of this technique permits evaluation of response to therapy. Persisting signal at high b‐values from restricted hypercellular tissue and viscous fluid also permits applications of DWI beyond oncologic imaging. DWI, when used in conjunction with routine imaging, can assist in detecting hemorrhagic degradation products, infection/abscess, and inflammation in colitis, while aiding with discrimination of free fluid and empyema, while limiting the need for intravenous contrast. DWI in conjunction with routine anatomic images provides a platform to improve lesion detection and characterization with findings rivaling other combined anatomic and functional imaging techniques, with the added benefit of no ionizing radiation. J. Magn. Reson. Imaging 2013;38:253–268. © 2013 Wiley Periodicals, Inc.
No Easy Choice: Value Dilemmas of Education Reform and Economic Rationalism in Hong Kong

A and policies are intertwined. Values are assumptions and beliefs of what is good and desirable; hence they are important to policy studies on several grounds (Fowler, 2004). Firstly, values define what is important and worthwhile, and they provide general guidelines for action. As such, policies are heavily influenced by values and political ideologies. Many policies can be seen as reflections of values and a variety of policies can be seen as expressions of a certain set of values. Secondly, values shape the way people define and interpret policy problems and possible solutions. There are ideological assumptions and value judgments underlying various policy stances, as is often evident in the language of policy statements. Values are central to policies in terms of defining goals and aims, and recipients (i.e., for what and for whom). To a great extent, they affect the choice of policies and measures adopted. Thirdly, in an increasingly pluralist society beset with controversies and debates, policies often reflect dominant values or ideologies. Even for some seemingly common values, conflicts or an absence of consensus occurs with regard to what a specific value actually denotes and how it can best be achieved, maintained, or elaborated. The view of policy as value laden has implications and consequences for how policy should be analyzed and how philosophical and normative discussions may be relevant to policy studies (e.g., the basic purposes of education and public policy). When viewed in this way, policy analysis should be more than just compiling a technical report (Ball, 1994). Instead, we should focus on its particular ideological configuration. Moving beyond the orthodox, restrictive “technical-positivistic-rational” mode of policy analysis, a return to values analysis or deliberation means that we do not take the value assumptions for granted but call them into question by explicating and revealing their origins and complexity. Because values have a powerful impact on policy development and policy studies, we need to be aware of and acknowledge our own value positions, and subject them to reflection and deliberation. Just like human disposition, value positions may be complex, ambivalent, covert,
Neurobiology of (central) auditory processing disorder and language-based learning disability: Auditory Neuroscience and Diagnosis

(Central) auditory processing disorder (abbreviated here APD) is defined as a deficit in the processing of auditory information, despite normal hearing thresholds, that primarily involves the auditory modality (ASHA, 2005; Jerger & Musiek, 2000). This umbrella definition encompasses a wide variety of perceptual and cognitive manifestations. APD thus cannot be reduced to a single anatomic site or impaired process in the auditory system. The question of whether such a nonspecific definition can really benefit research, diagnosis, and treatment notwithstanding, in this chapter we will focus on the physiologic processes thought to underlie the perception of auditory aspects that fall within the realm of APD. We will review evidence for specific physiologic processes and anatomic sites contributing to normal and abnormal auditory processing. In particular we review studies of the physiology and anatomy of: (1) auditory temporal processing , (2) auditory perception in noise, (3) representation and discrimination of acoustic features and (4) binaural processing. We also present evidence for (5) training-related neural plasticity of these processes where such evidence exists, focusing on training studies aimed at populations with symptoms of APD. The physiologic processes reviewed here with their accompanying perceptual correlates are summarized in Table 4–1. To our knowledge, physiologic and anatomic studies of APD diagnosed populations have been rare. On the other hand, many studies have focused on auditory processing in populations diagnosed with language-based learning disabilities (e.g., specific language impairment [SLI] and
Synthesis and Thermoelectrical Characterization of Lead Chalcogenide Nanowires

Thermoelectricity is the phenomenon of conversion between thermal and electrical energy. Compared with other technologies, thermoelectric (TE) devices offer distinct advantages: they have no moving parts, contain no chlorofluorocarbons, and have a long lifetime of reliable operation. However, current TE materials have found limited commercial application due to their low efficiency. TE efficiency is related to a material-dependent coefficient, Z, and is often expressed as the dimensionless figure-of-merit, ZT, given by ZT= rS 2 T/j, where Tis the absolute temperature, r is the electrical conductivity, S is the Seebeck coefficient, and j is the total thermal conductivity. It becomes difficult to improve ZT beyond a certain point since the material properties S, r, and j are inter-dependent. [1] Presently, simple bulk materials have reached an upper limit of ZTat approximately 1. Hicks and Dresselhaus proposed that conversion of bulk materials to low dimensional materials might significantly enhance TE performance through phonon scattering and electron confinement effects. [2] Dimensional reduction has since been shown to increase boundary scattering of phonons and reduce lattice thermal conductivity, [3] possibly without negatively affecting the electrical conductivity or Seebeck coefficient. The positive effects of low-dimensionality on ZT have already been demonstrated through several theoretical [2,4–6] and experimental [7] investigations, a few of which were based on lead chalcogenide systems. [8,9] Harman et al. achieved an especially high ZTof 2.0 at 300 K with PbSeTe/PbTe quantum dot superlattices. [10] Bulk
An atypical phenotype of macular and peripapillary retinal atrophy caused by a mutation in the RP2 gene

Aims: To determine the molecular basis and describe the phenotype of an atypical retinal dystrophy in a family presenting with bilateral, progressive central visual loss. Methods: Family members were examined. Investigations included Goldman perimetry, electrophysiology, and autofluorescence imaging. Candidate gene screening was performed using SSCP and sequence analysis. The proband’s lymphoblastoid cells were examined for protein expression. Results: Fundal examination of the proband, his mother, and brother revealed peripapillary and macular atrophy. Autosomal dominant retinal dystrophy was suspected, but less severe disease in the mother led to screening for mutations in X linked genes. A 4 bp microdeletion in exon 3 of the RP2 gene, segregating with disease, was identified. No RP2 protein expression was detected. Conclusion: The distinct phenotype in this family, caused by this frameshifting mutation in RP2, broadens the phenotypic spectrum of X linked retinitis pigmentosa. The absence of RP2 protein suggests that loss of protein function and not novel gain of function could account for the atypical phenotype. A definitive diagnosis of X linked retinitis pigmentosa permits appropriate genetic counselling with important implications for other family members. Clinicians should have a low threshold for screening RP2 in families with retinal dystrophy, including posterior retinal disease, not immediately suggestive of X linked inheritance.
Non-Genomic Actions of the Androgen Receptor in Prostate Cancer

Androgen receptor (AR) is a validated drug target for prostate cancer based on its role in proliferation, survival, and metastases of prostate cancer cells. Unfortunately, despite recent improvements to androgen deprivation therapy and the advent of better antiandrogens with a superior affinity for the AR ligand-binding domain (LBD), most patients with recurrent disease will eventually develop lethal metastatic castration-resistant prostate cancer (CRPC). Expression of constitutively active AR splice variants that lack the LBD contribute toward therapeutic resistance by bypassing androgen blockade and antiandrogens. In the canonical pathway, binding of androgen to AR LBD triggers the release of AR from molecular chaperones which enable conformational changes and protein–protein interactions to facilitate its nuclear translocation where it regulates the expression of target genes. However, preceding AR function in the nucleus, initial binding of androgen to AR LBD in the cytoplasm may already initiate signal transduction pathways to modulate cellular proliferation and migration. In this article, we review the significance of signal transduction pathways activated by rapid, non-genomic signaling of the AR during the progression to metastatic CRPC and put into perspective the implications for current and novel therapies that target different domains of AR.
Edge Halo Reduction for Projections onto Convex Sets Super Resolution Image Reconstruction

In this paper, we propose three improvements in the quality of high-resolution image for super-resolution reconstruction method based on projections onto convex sets (POCS). In order to improve the blur edge caused by bilinear interpolation, the wavelet bi-cubic interpolation is proposed to obtain the initial image estimation for reconstruction algorithm based on POCS. The point spread function (PSF) with edge-preserving property is proposed to reduce the amount of edge Halo in reconstruction result. The length-variable relaxation projection parameter, obtained by the correlation between low-resolution observation frames and reference frame, is adopted to reduce motion estimate error. Experiment results show that the proposed algorithm effectively reduces the amount of edge halo and obviously improves the quality of reconstructed high-resolution image.
Fully automated multi-label image annotation by convolutional neural network and adaptive thresholding

This paper presents a fully automated and flexible ConvNet-based classifier for multi-label image annotation. The classifier alleviates hierarchical representation of image from a convolutional neural network, and adaptive thresholding technique on the ranked list of label scores. The method can annotate images with arbitrary number of labels that the classifier finds fit, as opposed to common methods which only assign a fixed number of those. Experiments show state-of-the-art on classification accuracy and competitive annotation performance across 2 intrinsically different data-sets, Corel5K and MSRCv2. Although the proposed method shows some limitation in learning label semantics, empirical study indicates that it was due to the established drawback of univariate loss function, which the classifier optimised, in multi-label classification. It, therefore, opens for number of directions to improve the performance, while still retains the merits of the proposed method.
Analytical Modeling of Robotic Tape Libraries Using Stochastic Automata

This paper presents results of preliminary work concerning the analytical modeling of a robotic tape library using stochastic automata. This model is a rst approximation which we use to test the eeciency and accuracy of stochastic automata networks as a modeling tool. The eeects of interactive get and put requests, migration, and purging at online and nearline layers of a tertiary storage device are investigated. The discussion in this paper sheds further light to the merits and limitations of stochastic automata networks as a modeling methodology for evaluating the performance of complex real life applications.
Convergence analysis of a modified Armijo rule step-size LMF algorithm

In this work, we make use of the Armijo rule for the selection of the learning rate to introduce the Armijo rule learning rate least mean fourth (ALRLMF) algorithm. The algorithm is derived by incorporating the modified version of the Armijo rule line search to the class of stochastic gradient algorithm that minimizes the mean fourth error. The convergence behavior of the algorithm is analyzed and bounds guaranteeing convergence are explicitly derived. Finally, simulation results presented in a system identification scenario are found to corroborate the theoretical findings.
Optimal Receiver Design for Diffusive Molecular Communication With Flow and Additive Noise

In this paper, we perform receiver design for a diffusive molecular communication environment. Our model includes flow in any direction, sources of information molecules in addition to the transmitter, and enzymes in the propagation environment to mitigate intersymbol interference. We characterize the mutual information between receiver observations to show how often independent observations can be made. We derive the maximum likelihood sequence detector to provide a lower bound on the bit error probability. We propose the family of weighted sum detectors for more practical implementation and derive their expected bit error probability. Under certain conditions, the performance of the optimal weighted sum detector is shown to be equivalent to a matched filter. Receiver simulation results show the tradeoff in detector complexity versus achievable bit error probability, and that a slow flow in any direction can improve the performance of a weighted sum detector.