Miracle-dz/UniFAR-FTUs huggingface dataset:
Noise-robust digit recognition with exemplar-based sparse representations of variable length

This paper introduces an exemplar-based noise-robust digit recognition system in which noisy speech is modeled as a sparse linear combination of clean speech and noise exemplars. Exemplars are rigid long speech units of different lengths, i.e. no warping mechanism is used for exemplar matching to avoid poor time alignments that would otherwise be provoked by the noise and the natural duration distribution of each unit in the training data is preserved. Speech and noise separation is performed by applying non-negative sparse coding using a separate exemplar dictionary for each labeled unit (in this case half-digits) rather than a single dictionary of all units. This approach does not only provide better classification of speech units but also models the temporal structure of speech and noise more accurately. The system performance is evaluated on the AURORA-2 database. The results show that the proposed system performs significantly better than a comparable system using a single dictionary at positive SNR levels.
Antioxidant activities of aqueous extracts from 12 Chinese edible flowers in vitro and in vivo

ABSTRACT The antioxidant function of edible flowers have attracted increasing interest. However, information is lacking on the impact of edible flowers on oxidative injury including hypoxia-re-oxygenation and hyperlipidemia. The antioxidant activities of aqueous extracts from 12 Chinese edible flowers were assessed in four different antioxidant models, including total antioxidant capacity (TAC), oxygen radical absorbance capacity (ORAC), scavenging hydroxyl radical capacity (SHRC) and scavenging superoxide anion radical capacity (SSARC). Subsequently, the potential antioxidant effects on rat cardiac microvascular endothelial cells (rCMEC) treated with hypoxia-re-oxygenation and hyperlipidemia rats induced by high-fat diet were also evaluated. The highest TAC, ORAC, SHRC and SSARC were Lonicera japonica Thunb. , Rosa rugosa Thunb. , Chrysanthemum indicum L. and Rosa rugosa Thunb. , respectively. Most aqueous extracts of edible flowers exhibited good antioxidant effects on injury of rCMEC induced by hypoxia-re-oxygenation. In addition, the aqueous extracts of Lonicera japonica Thunb. , Carthamus tinctorius L. , Magnolia officinalis Rehd. et Wils. , Rosmarinus officinalis L. and Chrysanthemum morifolium Ramat. could suppress the build-up of oxidative stress by increasing serum superoxide dismutase, glutathion peroxidase, and reducing malonaldehyde concentration in hyperlipidemia rats. These findings provided scientific support for screening edible flowers as natural antioxidants and preventative treatments for oxidative stress-related diseases.
Comparing Different Fault Models Using

Fault injection is a widely used method for evaluating dependable systems. The intention of this paper is to compare typical fault models used for fault injection regarding their accuracy in predicting the reliability of the system. For this purpose, we set up an experiment by injecting faults in a VHDL model of the DP32-processor at gate-level, pin-level and at register-transfer level. The experiment has been performed by using the simulation based fault injector VERIFY (VHDL-based Evaluation of Reliability by Injecting Faults efficientlY). The differences in the predicted mean failure rate of the system will be shown and a comparison of system’s behavior after fault injection will be presented. The results demonstrate that faults have to be injected at least at gate-level in order to represent the correct timing behavior of the digital system after the fault has been injected and help the designer of a dependable system to find the weak components.
Allocation of attention and ther performance of venture capitalist

The paper proposes that the involvement of venture capitalists in their investments forms an important medium for transferring knowledge between the venture capitalists and their portfolio companies. The time spent with the venture affects the value of the post-investment activities of the venture capitalist. Consequently, the allocation of attention impacts the performance of the venture capitalist. From these premises, the paper develops an argument for an optimal size of portfolio and the moderating role of syndication. The hypotheses receive support from analyses employing longitudinal data of the leading U.S. venture capital investors. Our results indicate the value of the involvement of the venture capitalists and give guidance for its optimal allocation. Executive summary While the previous research has validated that the venture capitalists provide their investments with more than the capital invested, there has been less attention for the limitations of the value-added post-investments activities. Although the venture capitalist’s attention and time are considered a scarce resource, implying high opportunity cost for involvement in the portfolio companies, little attention in research has been given to how the allocation of this attention among the portfolio companies affect the performance of the venture capitalist. In this paper, we explore the limitations of the venture capitalists’ involvement considering the nature of informational and interpersonal aspects of the venture capitalists assistance and governance. Increasing the size of the portfolio divides the venture capitalist attention with two opposite effects. On one hand, the larger the size of the portfolio, the more venture capitalist has investments that potentially reach desirable outcomes. On the other hand, the larger the size of the portfolio, the less time the venture capitalist has to involve in portfolio companies, and the smaller is the value of this involvement leading to a smaller likelihood of each investment to reach the desired outcome. Examining these factors in detail, we argue that these competing forces lead to an inverted U-shaped relationship between the relative size of the
Mapping the political landscape of Persian Twitter: The case of 2013 presidential election

The fallacy of premature designations such as “Iran's Twitter Revolution” can be attributed to the empirical gap in our knowledge about such sociotechnical phenomena in non-Western societies. To fill this gap, we need in-depth analyses of social media use in those contexts and to create detailed maps of online public environments in such societies. This paper aims to present such cartography of the political landscape of Persian Twitter by studying the case of Iran's 2013 presidential election. The objective of this study is twofold: first, to fill the empirical gap in our knowledge about Twitter use in Iran, and second, to develop computational methods for studying Persian Twitter (e.g., effective methods for analyzing Persian text) and identify the best methods for addressing different issues (e.g., topic detection and sentiment analysis). During Iran's 2013 presidential election, three million tweets were collected and analyzed using social network analysis and machine learning. The findings provide a more nuanced view of the political landscape of Persian Twitter and identify patterns in accordance with or in contrast to those identified in the English-speaking Twittersphere around the 2013 presidential election. Persian Twitter was dominated by micro-celebrities, whereas institutional elites dominated English discourse about Iran on Twitter. The results also illustrate that Persian Twitter in 2013 was predominantly in favor of reformists. Finally, this study demonstrates that sentiment analysis toward political name entities can be used efficiently for mapping the political landscape of conversation on Twitter.
Fuzzy-logic based automatic control of hemodynamics

We propose an automatic closed-loop-system for hemodynamic control on the intensive care unit in patients after cardiac surgery. All possible combinations of four standard hemodynamic parameters (mean arterial pressure, on-line cardiac output, central venous pressure and systemic vascular resistance) and four treatment regimens (fluid administration, noradrenaline, dopamine and nitrates) were linked by knowledge-based rules in a fuzzy-logic system. After defuzzification, the loop was closed by integration of automatic control of infusion and syringe pumps. The system proved to be able to observe and handle any cardiocirculatory disturbances in circulatory models and animal experiments. The system remained stable throughout any observation period. Hemodynamic changes and therapeutic interventions were documented in an electronic experimental record. In several attempts for automatic therapy control in the past, failures were mainly due to insufficient computer capacity, inadequate sensors and the lack of appropriate mathematical models. We anticipate an improvement of postoperative patient care by induction of therapies and paperless on-line documentation permitting to spend more time to treat the critically ill.
FE-Based Physical Model of LPMBDCM for Integrated Motor Drive System Analysis

This paper introduces an accurate phase variable model with detailed evaluation of the force ripple for the linear permanent magnet brushless DC motor (LPMBDCM) drive system analysis. The mover position dependent variables of the physical model are obtained from finite element (FE) solutions by the cubic spline interpolation. Considering the effect of the snubber circuits in the power electronic devices, a new M-file S-function based model is proposed, with which the LPMBDCM is directly implemented in Simulink using the state space equations. An integrated LPMBDCM drive system including DC power supply, inverter, LPMBDCM and commutation control is developed. Simulation results show that the FE-based phase variable model is an efficient method to establish an accurate and computationally fast model for the integrated LPMBDCM drive system analysis.
An Efficient Wavelet Based Embedded Color Image Coding Technique using Block-Tree Approach

In this paper, we propose a simple and efficient technique for embedded color image coding. The proposed algorithm exploits inter- and intra-subband correlations of the wavelet transformed luminance (Y) and chrominance (U and V) planes as well as the interdependency among the coefficients of the three-color planes. The coefficients of the three-color planes are linked through the composite spatial orientation trees (CSOT) having root nodes in the Y-plane only. The CSOT is defined for blocks of coefficients rather than a single coefficient. Thus, the proposed algorithm combines the features of both zero-tree and zero-block based algorithm into a single algorithm due to the use of block-tree hierarchical structure. Simulation results show the improved performance of the proposed algorithm over other sate-of-the-art coders such as MPEG-4, color SPIHT (CSPIHT), color SPECK (CPECK), and JPEG-2000.
Design & Implementation of PCI Express BUS Physical layer using VHDL

This paper presents the proposal of the implementation of the Physical Link Layer of PCI-Express, as is defined in PCI Express1.0. The architecture presented here contains the transmission and receiver modules which ensure the reliably conveying of the Transaction Layer Packet (TLP) and Data link Layer Packet(DLLP) between two components using the PCI-Express protocol. This paper explains how the implementation makes the reliably conveying ,through the addition of a start and end bits to each data coming in from the Transaction and Data link Layer in the transmit side, and how the packets are processed in receiver side. The whole architecture will be implemented on Altera or similar FPGAs to indicate that this architecture is a feasible approach. PCI Express bus architecture will be implemented on VHDL platform
Real-time Rendering of 3D Clouds

Abstract The visual realism of a computer graphics simulation of outdoor scenery is greatly enhanced by a realistic display of clouds. In this paper, we present an algorithm based on Gardner's work that can render perspectively-correct 3D clouds in real time on current graphics hardware. The use of 3D ellipsoids as primitives permits even close-ups without the viewer noticing the approximation. We describe an implementation using OpenGL.
Efficient score normalization for speaker recognition

Score normalization is an important component in most speech classification tasks including speaker recognition. State-of-the-art scoring approaches use both T-norm and Z-norm. This paper addresses the following goals: better understanding of existing score normalization methods, reducing the need for explicit score normalization, and improving the computational efficiency of score normalization. In addition, the importance of score normalization for speaker identification is demonstrated, and accuracy is improved considerably using various normalization techniques.
Gender and leadership in higher educational institutions : exploring perceptions and practices in University of Cape Coast, Ghana

The purpose of this study is to examine the level of female participation in leadership activities in the University of Cape Coast (UCC). Leadership is experienced at various levels within the university - student, staff, committee and management levels in the university. However, the positions are mainly held by men. This study examined the institutional structures and cultural factors responsible for the dearth of women in leadership and why it is necessary to have more women vigorously involved in the decision-making in the university. Few women reaching the top have managed it successfully because of the exposure to various forms of institutional and cultural barriers. This state of affairs works against the effective utilization of human resources in the university. Ensuring that all individuals irrespective of their gender are equally motivated to participate in the decision-making process holds the potential for maximising the human resources within the university. In this study, the barriers to female participation in leadership have been explored. A qualitative research design guided the study. Twenty semi-structured interviews, participant observation and the use of unobtrusive observation were the main data collection techniques adopted. For data analysis, 'open and axial' coding approaches based on the inductive and deductive reasoning were utilised. A significant outcome of the study includes the fact that very few women are in head of departments and deanship positions. Women are almost absent in the top administrative echelon. Females occupy only designated 'vice/deputy' positions in students and staff unions. However, few academic women who have reached the top have managed successfully. The study concludes by expressing the view that women in UCC face several challenges which impede their progress towards leadership aspirations. These include institutional structures and culturally entrenched norms. Based on these findings and conclusions, a number of recommendations have been made to improve the chances of women in both academic and administrative departments to break the glass-ceiling and advance into leadership positions. These include the following: (1) the need for professional development opportunities for women to enable them to pursue postgraduate programmes after which they could be employed as administrators or academics, and (2) the institutionalization of policies in support of the reservation of quotas for women in some leadership positions, including chairing some of the sub-committees of the Governing Council and the Academic Board to ensure fair participation of women in critical decision-making levels in the university.
Security Impacts of Virtualization on a Network Testbed

Modern virtualization technologies provides an optimal use of underused hardware resources by sharing them among virtual machines hosted on the same physical machine. These technologies hence have been broadly adopted in many areas, such as server consolidation, virtualized network test beds, etc. A large-scale network test bed is considered one of the useful tools for evaluating or verifying advanced networking technologies. To construct a network test bed that matches as much as a real setup, the test bed should meet requirements of isolation, fidelity, repeatability, scalability, containment and extensibility. Among these requirements, scalability can be realized by the modern virtualization technology, whereas vulnerability and security weakness brought along with virtualization can also be harmful to the other requirements of a network test bed, like isolation and fidelity. This paper reviews the modern virtualization technologies, their resource management mechanisms, and the known attacks of these virtualization technologies. Then, we discuss the requirements of existing network test beds and the security impacts when introducing such modern virtualization technologies into a network test bed.
Detection of Myers-Briggs Type Indicator via Text Based Computer-Mediated Communication

In this paper various algorithms for detecting Myers-Briggs Type Indicator based on brief samples of an individual’s text communication from the web site Twitter are explored. These algorithms are trained using almost sevenhundred-thousand tweets from four-thousand-six-hundred unique users who have indicated their MBTI results. Keywords-MBTI; Myers-Briggs; Twitter; NLP; Naïve Bayes
Doubly special relativity and quantum gravity phenomenology

Without doubts the most challenging problem of high energy physics is to complete the unfinished revolution that started with the formulation of general relativity and quantum mechanics in the first decades of twenties century. For many years however quantum gravity has been associated only with strong gravitational field regime in the vicinity of space-time singularities, e.g., with effects taking place just after (or before) the big bang or inside black holes. This state of affairs made it impossible to have any reasonable hope to test quantum gravitational effects in a foreseeable future. It was estimated that a particle accelerator in which we could test Planck scale scattering should be of the size of Earth orbit. The status of quantum gravity phenomenology changed substantially with the observation1, 2 that there is a hope that one may observe imprints of quantum gravity in experiments that already are or soon will be within the reach of current observational technologies. Most notably one expects that we may see traces of quantum gravity in kinematics of ultra-high energy cosmic rays scaterrings (violation of the GZK bound), as well as in the time-of-flight experiments. It should be stressed that this new quantum gravity phenomenology paradigm concerns minute effects of quantum gravity that are present already in the flat space limit. Moreover these effects are of the kinematical and not dynamical origin, namely they concern interaction of test particles with flat space-time solution of quantum gravity, which is assumed to lead to a theory that is somehow different from the standard Special Relativity.
A review of statistical and cognitive learning for sentence processing

In the research field of natural language processing (NLP), sentence stands a very prominent position in text processing. The procedure of sentence processing acquires technologies at a higher level, such as computing the meaning of a sentence based on analysis of meanings of its individual words. This paper reviews several typical research works for statistical learning, highlights relevant cognitive concepts and models, introduces a cognitive sentence parser based on Simple Recurrent Networks (SRNs), and concludes that further research should be implemented with more cognitive models.
Identifying overly strong conditions in refactoring implementations

Each refactoring implementation must check a number of conditions to guarantee behavior preservation. However, specifying and checking them are difficult. Sometimes refactoring tool developers may define overly strong conditions that prevent useful behavior-preserving transformations to be performed. We propose an approach for identifying overly strong conditions in refactoring implementations. We automatically generate a number of programs as test inputs for refactoring implementations. Then, we apply the same refactoring to each test input using two different implementations, and compare both results. We use Safe Refactor to evaluate whether a transformation preserves behavior. We evaluated our approach in 10 kinds of refactorings for Java implemented by three tools: Eclipse and Netbeans, and the JastAdd Refactoring Tool (JRRT). In a sample of 42,774 transformations, we identified 17 and 7 kinds of overly strong conditions in Eclipse and JRRT, respectively.
MPEG-7 compliant generalized structure descriptor for still image indexing

This paper proposes a generalized structure descriptor (GSD), that offers an MPEG-7 compliant template for the introduction of a large class of local image content descriptors. The standard MPEG-7 color structure descriptor (CSD) is a particular case of the proposed GSD. The GSD descriptor embed color and spatial distribution information, allowing a compact description of color and texture to be used in content-based image retrieval. We will present several particular cases of spatial image structure description. Experiments show that the proposed descriptors can be successfully used for color texture and general image recognition and retrieval.
Analysis of Seismic Activity using the Growing SOM for the Identification of Time Dependent Patterns

The growing self organizing map (GSOM), a variant of the self organizing map, is a dynamic feature map model used for knowledge discovery in high dimensional datasets. It has been used mainly to identify hidden patterns in static data in an unsupervised manner. Several extensions to the GSOM that enable dynamic data analysis have been proposed. In this paper we discuss such an extension and its capabilities in discovering time variant patterns in datasets of seismic activity. The results obtained by processing clusters generated by the GSOM using the data skeleton model and spread factor extensions, emphasize the usability of the GSOM in dynamic data analysis.
Fe b 20 05 Decompactification and the g – Theorem

We give a precise description of the decompactification limit of a family of worldsheet sigma models using 2d renormalization group (RG) methods. We adapt Affleck and Ludwig’s g-theorem from boundary conformal field theory (CFT) to critical string theory, where the worldsheet theory has vanishing central charge and the fixed points can include noncompact CFTs. It has been conjectured that an analog of the boundary entropy, g, that is lowered under relevant RG flows of the bulk CFT is the bosonic vacuum degeneracy, gcl. We point out in this paper that gcl counts the number of relevant bulk operators, or closed string tachyons, and that their contribution to the string free energy is unambiguously normalized: the choice of Weyl invariant worldsheet regulator is unique. Thus, unlike a generic 2d field theory, the relevant operators make a universal contribution to the string free energy. We give an example of an integrable relevant flow terminating in a noncompact infrared (IR) fixed point. Our example taken from the closed oriented type II superstring thermal ensemble demonstrates that gcl is indeed lowered, and that the contribution to the string free energy from relevant operators is universal at all points along the flow. The IR fixed point is the noncompact supersymmetric type II vacuum with a continuous spectrum of scaling dimensions.