Miracle-dz/UniFAR-FTUs huggingface dataset:
List of acronyms ADC Analog to Digital Converter CD Compact Disk

In this thesis a new way of implementing a Class D amplifier controller is presented. A Class D amplifier controller is a system that essentially performs Sigma Delta modulation to quantize discrete digital input into a 1 bit Pulse Width modulated signal that is used to drive a power amplifier. The system has internal control loops that perform the necessary noise filtering thus providing quantization noise free modulated output. This system in a digital implementation traditionally follows digital design flow starting from a VHDL description, which can be time consuming for a controller design that has a greater complexity. The approach investigated in this thesis involves modeling of the system in a functional programming language Haskell. In the model, elementary mathematical equations that are used to describe the system are modeled in the form of higher order functions. The Haskell code is then converted to a CλaSH (CAES Language for Synchronous Hardware) code, which is a sub-set of Haskell that is used to describe sequential digital hardware. The conversion involves minor changes to the base Haskell model. With its native compiler, CλaSH is used to generate VHDL code from the Haskell modelled system. Simulations are performed on Haskell and CλaSH models and compared with the simulation of an equivalent Simulink model. The comparison shows that the CλaSH implementation respects the intended functionality of the system.
Mechanical properties of human dentin Part II – Measurement of local characteristics by FIMEC indentation test

The mechanical characteristics of dentin have been investigated on local scale by the instrumented indentation test FIMEC employing a cylindrical punch. The technique permitted to measure in different tooth positions the elastic modulus, yield stress, stress-relaxation and creep. The punch diameter (Φ = 0.5 mm) is much larger than the tubule size thus data are not so largely scattered as in microand nanoindentation tests but, at the same time, is small enough to guarantee a good resolution in mapping the mechanical properties. The results are in good agreement with literature data obtained by means of various experimental techniques. Furthermore, a new algorithm has been developed for analysing the experimental indentation curves in view of the realization of a commercial FIMEC apparatus. KeywordsDentin, instrumented indentation, FIMEC, local mechanical characterization
MOSI: A SMT Microarchitecture Based on VLIW Processors

Simultaneous Multi-Threading(SMT) technique has become the hot spot in architecture research because it can effectively improve processors' throughput with relative smaller cost.On the other hand,Very Long Instruction Word(VLIW) is popular in high performance processor design currently.Obviously,applying SMT technique to VLIW processors is profitable,but the remarkable characteristics of these processors,such as lack of hardware dynamic schedule mechanism,make it difficult to implement.This paper presents a SMT microarchitecture based on VLIW processors,named MOSI(MultiOp Splitting Issue). MOSI dynamically issues instructions in the same MultiOp,and introduces write-back buffer that writes results into registers according to the supposed order of compiler,so it tackles the crucial problem in SMT technique with minimal cost.This paper describes the write-back buffer's detail structure and run-time algorithm,and then shows the hardware models of single thread and overall processor.In the end,the organization of Caches and the preferable thread count(hardware supported) are discussed.The experimental result shows that the dual thread processor based on MOSI microarchitecture improves the total throughput by 40%.
Power Quality Monitoring System Based on DSP

According to three-phase power voltage and current signal acquisition and processing,this paper designed power quality monitor system based on DSP of TMS320F2812.The system takes a Hall sensor system and the A/D converter chip as prior acquisition circuit,digital signal processor(DSP) as data processing circuits,and phase locked loop(PLL)as synchronous sampling hardware circuit.Fast fourier transform algorithm is also adopted as the main treatment.The experiment results prove that the system is of fast response,high accuracy,and real-time processing.
Is Deregulation Necessary ? ReAssessing the Effects of Employment Protection

Using new data, the paper examines the effect of employment protection legislation (EPL) on aggregate and youth unemployment in advanced industrial economies and in Central and Eastern Europe during 1980-2009. The analysis assesses both the direct and indirect effects of EPL on levels of unemployment, as well as the short-term and long-term effects of changes in EPL on changes in unemployment. The results offer no clear support for the argument that EPL is a cause of either aggregate or youth unemployment. While EPL reaches statistical significance at conventional levels in some models, the results are sensitive to small changes in the sample or the use of alternative estimators. The only finding that appears robust concerns the interaction between EPL and the tax wedge, which suggests some scope for reform complementarity in tackling youth labour market problems. On the whole, the analysis suggests that government efforts to tackle unemployment by deregulating EPL alone may well be futile. Word count: 9970
Recognizing Character-directed Utterances in Multi-child Interactions

We address the problem of identifying when a child playing an interactive game in a small group is speaking to an animated or robotic character versus conferring with his friend. This judgment about addressee is critical for turn-taking. We explore a machine learning approach using a Support Vector Machine (SVM) to integrate audio and visual features that we believe can be sensed accurately. We extend the basic model by including a simple form of group information, limited speech recognition, and limited game state to improve classification accuracy. Our results demonstrate high accuracy in detecting when the character is being addressed. This model improves our understanding of children’s group behavior in interacting with an agent.
Mechanisms behind exercise intolerance in Heart Failure with Preserved Ejection Fraction

Correspondence: stefan.meier@student.maastrichtuniversity. nl Abstract Heart failure with preserved ejection fraction (HFpEF) is becoming one of the most prevalent cardiovascular disorders in elderly and growing out of proportion in comparison to heart failure with reduced ejection fraction (HFrEF). The pathophysiological mechanism behind HFpEF is still largely unclear and due to this lack of knowledge there has yet to be found an optimal treatment. The predominant feature of HFpEF is exercise intolerance and with this a reduction in quality of life. Previously, research has focused on a central cardiac mechanism and the development of exercise intolerance. The decrease in exercise tolerance was primarily due to a poor cardiac output. However, research has recently shown that exercise intolerance is not primarily due to a central cardiac mechanism but due to a peripheral mechanism. This peripheral mechanism primarily focusses on the muscle adaptations in HFpEF, which largely accounts for the decrease in peak VO2 and thus exercise intolerance. Moreover, exercise training seems an effective treatment for improvements in exercise tolerance in HFpEF patients even in the absence of changes in the central cardiac mechanism. Pharmaceutical research also established findings that suggest improvement in exercise tolerance due to alterations in the peripheral mechanism. This introduces a paradigm shift to focus more on the peripheral mechanism associated with exercise intolerance in HFpEF and new possibilities for effective treatments.
A State-Based Approach to Information Flow Analysis

Confidentiality is an important security requirement in many secure systems. However, access control mechanisms can’t completely make sure that confidential information never leaks out, because the mechanisms cannot prevent hidden information flow and confidential information can stealthily leak out. The authors outline a state-based approach to deciding whether hidden information flows exist. The main idea of the approach is to model secure systems as finite automata, and analyze the properties of information flow by studying the characteristic of the finite automata. Compared with the past works, the research is completely based on automaton model. Security policies in actual secure systems are usually described in automaton model or action rules convenient to be transformed into automaton model. Thus the results are more suitable to be directly used in actual systems. In addition, subsequent research following the works, such as eliminating hidden information flow, can easily go on.
PAI-1 4 G / 5 G polymorphism and coronary artery disease risk : a meta-analysis

Many epidemiologic studies have investigated the plasminogen activator inhibitor-1 (PAI-1) gene 4G/5G polymorphism and this association with coronary artery disease (CAD). But definite conclusions can not be drawn. Related studies were identified from PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure (CNKI), and Chinese Biology Medicine (CBM) till 10 August 2014. Pooled ORs and 95% CIs were used to assess the strength of the associations. A total of 53 studies including 20921 CAD cases and 18434 controls were included. Significantly elevated CAD risk was found in overall analysis (OR = 1.13, 95% CI: 1.05-1.21, P = 0.0009). In the subgroup analysis by races, significantly increased risk was found in Caucasians (OR = 1.11, 95% CI: 1.03-1.20, P = 0.005) and Asians (OR = 1.20, 95% CI: 1.01-1.42, P = 0.04). In the subgroup analysis by gender, significant association was found in males (OR = 1.15, 95% CI: 1.06-1.25, P = 0.0008), but was not found in females (OR = 1.05, 95% CI: 0.92-1.20, P = 0.47). In the subgroup analysis by age, young populations showed increased CAD risk (OR = 1.19, 95% CI: 1.02-1.37, P = 0.02), but old populations did not show this association (OR = 1.01, 95% CI: 0.82-1.24, P = 0.93). This meta-analysis provides the evidence that PAI-1 4G/5G polymorphism may contribute to the CAD development.
Digit image frequency correlation method and its application

A new digit image frequency correlation method was presented,where the carrier was the gray displacement.There was no interference light source needed and the test could be carried on under the nature illumination,so the demand for the environment was low compare with the traditional laser speckle method.The calculation speed was more quicker and there was no inference from the rigid body rotation compare with the DMC method.The test system is simple and the sensitivity is adjustable.The procedure of image acquirement and analysis are finished by computer automatically.As the ability of digit image processing of the computer is utilized sufficiently,the ability of against the disturbance is increased greatly.So DFC is the technique which is suitable the application in industry very much and would have a bright future.
HIGH-RESOLUTION LAND DATA ASSIMILATION IN THE NCAR/ATEC 1.5 REAL-TIME FDDA AND FORECASTING SYSTEM

In the past four years, the National Center for Atmospheric Research (NCAR) and the Army Test and Evaluation Command (ATEC) have been developing a multiscale (with grid sizes of 0.5–45 km), rapidly cycling (at time intervals of 1–12 hours), real-time four-dimensional data assimilation and forecasting (RTFDDA) system. The RTFDDA system is based on the PSU-NCAR MM5 model (Dudhia 1993; Grell et al. 1994) and uses continuous data assimilation that employs the forecast model with Newtonian relaxation terms. The details of the system design, model and observational data used can be found in Cram et al. (2001) and Liu et al. (2002). For more information on the ATEC RTFDDA project please refer to the RAP/ATEC web page at http://www.4dwx. org/atec. The atmospheric model is coupled to the Noah land surface model (Chen et al. 1996). One of the latest additions to the RTFDDA system is the development and implementation of a high resolution land-surface data assimilation (HRLDAS) system that provides a continuous analysis of the land-surface state for each of the model domains. This paper describes the implementation of such a system and the validation of the mesososcale model analysis and forecasts with and without the use of assimilated land surface conditions.
Complex Neural Fuzzy Prediction Using Multi-Swarm Continuous Ant Colony Optimization

Prediction of time series is one of major research subjects in data science. This paper proposes a novel approach to the problem of multiple-target prediction. The proposed approach is mainly composed of three parts: the complex neuro-fuzzy system (CNFS) built by using complex fuzzy sets, the two-stage feature selection method for multiple targets, and the hybrid machine learning method that uses the multi-swarm continuous ant colony optimization (MCACO) and the recursive least squares estimation (RLSE). The CNFS predictive model is responsible for prediction after training. During the training of the model, the parameters are updated by the MCACO method and the RLSE method where the two methods work cooperatively to become one machine learning procedure. For the predictive model, complex fuzzy sets (CFSs) are with complex-valued membership degrees within the unit disk of the complex plane, useful to the non-linear mapping ability of the CNFS model for multiple target prediction. This CFS property is contrast to real-valued membership degrees in the unit interval [0,1] of traditional fuzzy sets. The two-stage feature selection applies to select significant features to be the inputs to the model for multiple target prediction. Experiments using real world data sets obtained from stock markets for the prediction of multiple targets have been conducted. With the results and performance comparison, the proposed approach has shown outstanding performance over other compared methods.
Entrepreneurial Development The Impact of Mentorship in the Entrepreneurial Life-Cycle Process

A sustainable development of entrepreneurship will not be possible in such a complex and challenging environment as today’s society, without the attainment of effective learning and business support capabilities (Williams, 1998). One such support is obtained through having experienced entrepreneurs mentor less experienced entrepreneurs, transferring knowledge (Clutterbuck, 2004) and facilitating learning (Sullivan, 2000). As Leonard Bisk (2002) and Sullivan (2000) among other researchers (Deakins et al. 1997) stress, there is a need to look beyond the start-up process of a firm and the use of mentorship in this early phase, and focus more on how entrepreneurs who have been in business for a while can benefit from a mentor program, an area referred to as “the nature of timing and support” (Sullivan, 2000, p. 163). The purpose of this thesis is to explore how an experienced entrepreneur, a mentor, can help a less experienced entrepreneur, an adept, achieve entrepreneurial development during and throughout different phases of the entrepreneurial life cycle, in the most efficient manner. An entrepreneurial life cycle can be divided into several phases, which can be used in order to examine the entrepreneur’s development process within different time periods of running a firm. Start-up support generally involves providing entrepreneurs with the crucial “tools” for survival, such as basic financial support, bookkeeping and marketing (Sullivan, 2000). Mature entrepreneurs generally request psychological benefits, such as reassurance and improved confidence as they wonder whether or not their experiences are normal and how they should be interpreted (Megginson et al. 2006). There are two types of directive mentoring styles, coaching and counseling, and two types of non directive mentoring, counseling and networking. The main objective with our research in this thesis was to explore how entrepreneurs’ development throughout and during different phases was affected by active participation in a mentor program. To gather information we used a qualitative method, in which we interviewed ten entrepreneurs who were currently active in a mentor program, or had been active within the last 12 months. The empirical findings were later analyzed in the light of the frame of references and the authors own viewpoint, by conducting a within case/cross case comparisons. The results indicate that a mentor can best help an entrepreneur achieve entrepreneurial development by providing non directive support, enabling the entrepreneur to draw his or her own conclusions and stimulate self reliance. This support is best delivered after the start-up and conception phase, the first phase of the life-cycle.
Certain Improvements in Optimization Techniques for Grid Scheduling

Grid computing is a computing framework based on large-scale resource sharing to run grid enabled applications. The grid system’s efficiency and quality of service depends upon core functions such as resources discovery and scheduling. The system attempts to optimize scheduling to enhance system performance and also aims to use resources efficiently. This work proposes implementation of a hybrid optimization algorithm based on Memetic and Fish School optimization module, for optimal grid scheduling in a network grid. The proposed Memetic Fish Swarm Optimization (MFSO) scheme incorporates local search techniques in the standard Fish Swarm Optimization algorithm, resulting in an efficient and effective optimization method. The proposed approach aims to dynamically create an optimal schedule to finish jobs within minimum time duration. [N. Krishnamoorthy and R. Asokan. Certain Improvements in Optimization Techniques for Grid Scheduling. Life Sci J 2013;10(7s):568-572]. (ISSN: 1097-8135). http://www.lifesciencesite. com. 89
Prognostic Factors for 12 Month Major Molecular Response for Patients with Chronic Myeloid Leukemia

Chronic Myeloid Leukemia is a kind of blood cancer with around 1 incidence per 100 000 persons/year. After the development of an effective treatment, imatinib, in the late 1990:s, the survival percentage has increased drastically. The high survival has turned the attention to different kinds of treatment responses, which in turn are good prognostic factors to future health status. In this thesis, the focus is on whether or not the patient has achieved a so called major molecular response after 12 month, or not. More precisely, the aim is to find prognostic factors to the 12 month response. In order to find prognostic factors for this binary response variable, a multivariate logistic regression analysis is conducted, with the goal of finding a parsimonious logistic model that describes the data. The analysis is done from a merged dataset from three earlier studies. The prognostic factors in the final model are treatment, 3 month response, and enlarged spleen. However, the residual analysis indicates that the model is incomplete, implying that further research needs to be done.
4 An Examination of the Bias in the NCEP GFS , CFS Simulations Associated with the Marine Stratus Clouds

Recently, a new operational coupled climate forecast system (CFS) has been developed and implemented at the NOAA National Centers for Environmental Prediction (NCEP) for seasonal climate prediction (Wang et al. 2005). Diagnoses based on retrospective forecast indicate that the CFS performs significantly better than the previous NCEP coupled model in the forecast of ENSO-related variability. Systematic errors, however, exist in the CFS model climatology compared to the observations (Saha et al. 2005).
Design principles and domains of knowledge for the professionalization of teachers and facilitators-Two examples from the DZLM for upper secondary teachers -

The DZLM (German Centre for Mathematics Teacher education) is a joint research and development institution of seven German universities to set new standards and prototypes for the professionalization of mathematics teachers. The programmes are developed through research-based design principles, and models for domains of teachers’ and facilitators’ knowledge and competences. In the following, we will elaborate on DZLM’s models and principles by presenting two exemplary courses to implement the new national standards for upper secondary level teachers: one focussing the use of digital tools for teaching and learning mathematics, and one focussing on probability and statistics as a new subject for most teachers.
Usefulness of Kelly clamp crushing technique during hepatic resection

Introduction. Recently, there are various kinds of parenchymal transection methods. The aim of this study is to evaluate the usefulness of the Kelly clamp crushing technique compared to ultrasonic dissector during hepatic resection. Materials and methods. Comparisons between 10 ultrasonic dissector group and 10 Kelly clamp crushing technique group were performed by using nine items (transaction time, right lobe volume, perioperative transfusion, total bilirubin (TB), aspartate aminotransferase (AST), alanine aminotransferase (ALT), hospital stay, postoperative morbidity, in-hospital mortality). Results. The mean transection time in the Kelly clamp crushing technique group was 27915.5 mins (range 15 60) and was 4897.1 mins (range 35 60) in the ultrasonic dissector group (pB0.05), and no patients received transfusion in both groups. Conclusions. Since the Kelly clamp crushing technique shortens operative time and there is no significant difference in blood loss and in results of liver function tests compared to using the ultrasonic dissector, we propose that the Kelly clamp crushing technique should be considered as a standard method of liver resection.
Number : WUCSE-2006-27 2006-0101 Fast Packet Classification Using Bloom Filters

While the problem of general packet classification has received a great deal of attention from researchers over the last ten years, there is still no really satisfactory solution. Ternary Content Addressable Memory (TCAM), although widely used in practice, is both expensive and consumes a lot of power. Algorithmic solutions, which rely on commodity memory chips, are relatively inexpensive and power-efficient, but have not been able to match the generality and performance of TCAMs. In this paper we propose a new approach to packet classification, which combines architectural and algorithmic techniques. Our starting point is the well-known crossproducting algorithm, which is fast but has significant memory overhead due to the extra rules needed to represent the crossproducts. We show how to modify the crossproduct method in a way that drastically reduces the memory required, without compromising on performance. We avoid unnecessary accesses to off-chip memory by filtering off-chip accesses using on-chip Bloom filters. For packets that match p rules in a rule set, our algorithm requires just 4 + p + ǫ independent memory accesses on average, to return all matching rules, where ǫ á 1 is a Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Fast Packet Classification Using Bloom Filters Sarang Dharmapurikar Haoyu Song Jonathan Turner John W. Lockwood