Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring R&D Performance-State of the Art

OVERVIEW:Many R&D performance measurement techniques have been developed in response to the unique needs of various organizations. An extensive search of the literature from 1956 to 1995 identified over 90 articles, 12 books and two research reports describing various techniques. Integrated metrics that combine several types of quantitative and qualitative measures were found to be the most effective, but also the most complex and costly to develop and use. The choice of an appropriate R&D measurement metric depends on the user's needs for comprehensiveness of measurement, the type of R&D being measured, the available data, and the amount of effort the user can afford to allocate to it. Guidelines are provided for selecting an appropriate measurement method within these parameters.
A data-driven approach to speech enhancement using Gaussian process

This paper presents a novel data-driven approach to single channel speech enhancement employing Gaussian process (GP). Our approach is based on applying GP regression to estimate the residual gain with the input features being the a priori and a posteriori signal-to-noise ratios (SNRs). The residual gain is deﬁned as the difference between the optimal gain and that obtained from the minimum mean-square error log-spectral amplitude (MMSE-LSA) estimator. Our proposed approach involves a cascaded structure consisting of two stages. At the ﬁrst stage, the gain of the MMSE-LSA estimator is calculated in conjunction with the SNR features. In the second stage, the residual gains are estimated through GP and they are used to further enhance the output of the MMSE-LSA module. Experimental re-sults show that the proposed approach produced better speech quality than not only the MMSE-LSA enhancement module but also the other data-driven technique.
KSR1 multiprocessor: analysis of latency hiding techniques in a sparse solver

This paper analyzes and evaluates some novel latency hiding features of the KSR1 multiprocessor: prefetch and poststore instructions and automatic updates. As a case study, the authors analyze the performance of an iterative sparse solver which generates irregular communications. They show that automatic updates significantly reduce the amount of communication. Although prefetch and poststore instructions reduce the coherence miss ratios, they do not significantly improve the sparse solver performance due to the overhead in executing these instructions. <<ETX>>
Genetic odyssey to generate marked clones in Drosophila mosaics

Significance The phenotypic analysis of mosaic animals has made possible the study of complex biological processes. We review the various tools available to Drosophila researchers today, many of which use the Gal4-upstream activating system and Flippase recognition target systems, as well as the use of fluorescence proteins. Emphasis is on the contributions that our group has made over the years to the development of these methods. Chimaeras, fanciful beasts that drew their force from being composed of parts of disparate animals, have stimulated our collective imagination for centuries. In modern terms, chimaeras are composite animals consisting of genetically distinct cell populations and are called “mosaics” if the different cell types have emerged from the same zygote. Phenotypic studies of chimeric animals formed from invertebrates, amphibians, birds, and mammals have provided many fundamental insights into biological processes, most notably in developmental biology. Many methods for generating both chimaeras and a range of markers for tracing their lineages have been developed over the years. Our laboratory has been intimately involved in the development of methods that facilitate the creation of genetic mosaics in Drosophila. Here, we review our contributions to the development of this field and discuss a number of approaches that will improve further the tool kit for generating mosaic animals.
Online Attendance System

Real-time face detection is one part of the automatic face recognition system and also used in developing an independent research subject. So, there are many approaches to overcome problems in face detection. This paper introduces a new approach in automatic attendance management systems, extended with computer vision algorithms . In our proposed system real time face detection algorithms are used in integration with an existing Learning Management System (LMS), which automatically detects and registers students attending on a lecture. The system represents a supplemental tool for instructors, algorithms used in machine learning are combined with adaptive methods used to track facial changes during a longer period of time. Time consumption is lesser than traditional methods, at the same time being nonintrusive and does not interfere with the regular teaching process. The tool promises to offer accurate results and a more detailed reporting system which shows student activity and attendance in a classroom. Keywords– Computer Vision, Object Tracking, FaceRecognition, Machine Learning and Teaching
Modification in contrast mapping: Reversible watermarking with performance improvement

Reversible watermarking, a special form of information hiding, becomes appealing for certain applications (for example, medical or military data) where reconstruction of original data is essential from the watermarked one after serving the intended purpose. Among various methods, reversible contrast mapping (RCM) is a flexible integer transform for pixel pairs that offers high embedding rate at low mathematical complexity and without requiring additional data compression. Mathematically, RCM may be interpreted as a form of intercept in straight line that controls distortion and leads to retention of structural information of the watermarked image. A simple yet effective modification over previously proposed RCM is suggested here that offers a better trade-off in visual quality-embedding rate-security of the hidden data. Simulation results validate the above claims.
Software simulation of LDPC codes and performance analysis

In this paper we will analyze the influence of using Low Density Parity Check LDPC codes in different channels environment. The performances of LDPC codes are estimated in several scenarios. The simulation software gives us the possibilities to choose between different communications channels according to the encoding matrix used. Also we can adjust a number of parameters, thing that help to find the optimal solution depending on the decoding error rate or Bit Error Ratio (BER). Optimal combinations between parameters, the encoding matrix and structures design are obtained, related to required performance or Signal Noise Ratio (SNR) ranges. The sets of parameters and criteria introduced are discussed as the simulation results, also.
Biological Efficacy of Streptomyces sp. Strain BN1 against the Cereal Head Blight Pathogen Fusarium graminearum

Fusarium head blight (FHB) caused by the filamentous fungus Fusarium graminearum is one of the most severe diseases threatening the production of small grains. Infected grains are often contaminated with mycotoxins such as zearalenone and trichothecences. During survey of contamination by FHB in rice grains, we found a bacterial isolate, designated as BN1, antagonistic to F. graminearum. The strain BN1 had branching vegetative hyphae and spores, and its aerial hyphae often had long, straight filaments bearing spores. The 16S rRNA gene of BN1 had 100% sequence identity with those found in several Streptomyces species. Phylogenetic analysis of ITS regions showed that BN1 grouped with S. sampsonii with 77% bootstrap value, suggesting that BN1 was not a known Streptomyces species. In addition, the efficacy of the BN1 strain against F. graminearum strains was tested both in vitro and in vivo. Wheat seedling length was significantly decreased by F. graminearum infection. However, this effect was mitigated when wheat seeds were treated with BN1 spore suspension prior to F. graminearum infection. BN1 also significantly decreased FHB severity when it was sprayed onto wheat heads, whereas BN1 was not effective when wheat heads were point inoculated. These results suggest that spraying of BN1 spores onto wheat heads during the wheat flowering season can be efficient for plant protection. Mechanistic studies on the antagonistic effect of BN1 against F. graminearum remain to be analyzed.
Knowledge circulations in inter-para/professional practice: a sociomaterial enquiry

In studies of professional learning, the rise of sociomaterial accounts draw attention to the political importance of nonhuman as well as human actors, the material as well as discursive, as inter-related in knowing and action. Of particular relevance to the issue of inter-professional work in health services, some researchers have argued that multiple worlds – not just multiple worldviews – are produced through socio-material processes. This article focuses on the complex activities involved in combining the multiple worlds of different professions with what some term para-professions. Such arrangements may not be recognised as inter-professional by their practitioners, with problematic consequences for care. The case is emergency mental health care, involving paramedics, police, hospital admissions staff, psychiatric nurses and A&E consultants. A sociomaterial analysis is used to trace how knowledge and practice circulates (or doesn’t) within and across different material worlds of practitioners, and the ontological politics produced at their boundaries.
Finding Exact and Approximate Block Structures for ILU Preconditioning

Sparse matrices which arise in many applications often possess a block structure that can be exploited in iterative and direct solution methods. These block-matrices have as their entries small dense blocks with constant or variable dimensions. Block versions of incomplete LU factorizations which have been developed to take advantage of such structures give rise to a class of preconditioners that are among the most effective available. This paper presents general techniques for automatically determining block structures in sparse matrices. A standard "graph compression" algorithm used in direct sparse matrix methods is considered along with two other algorithms which are also capable of unraveling approximate block structures.
OBDD–based Set Implementations

Storing huge amount of data in a memory has always been one of the main challenges of software development process. Using an approach for saving data that is not efficient enough may result in consumption of huge amount of memory and time. One of the examples of such applications where the amount of used memory and time is one of the crucial properties of the system is Points-to analysis. Points-to analysis computes reference information which is an essential input to different client applications, e.g., static garbage collection or metric analysis. This type of information is the basis for many different analysis and transformations. One of the challenges of implementing high-precise analysis is increasing of memory consumption. The possible solution is to store context-sensitive points-to analysis information in a compact, non-redundant way that will make it efficient enough to perform on benchmarks of significant sizes. Ordered-Binary Decision Diagrams (OBDDs) have been shown very useful for representing large sets of objects and solving memory consuming problems. OBDD is a data structure for showing Boolean functions by directed acyclic graph with a set of manipulation algorithms. The use of OBDD-based sets as a mean to store points-to analysis results can lead to memory reduction in the analysis phase. This thesis is focused on implementation of OBDDs for capturing and manipulating different amount of sets of objects that could represent points-to analysis information. Additionally, we compare OBDDs with a yet another implementation known as BitSet where each set of objects is represented as a vector of bits. The goal of this thesis was to show that OBDDs can also be quite effective for storing and manipulating of points-to analysis information of large programs. However, the results are not that impressive as it was expected after theoretical investigation. Acknowledgement First, we would like to offer sincerest gratitude to our supervisors, PhD student Antonina Danylenko and Dr. Jonas Lundberg for providing this interesting topic and helping us throughout this thesis. We would never have been able to finish our thesis without their guidance. We also appreciate help of Mathias Hedenborg during this thesis. We would like to thank our parents for supporting us towards this journey.
MOEA/D-GO for Fragmented Antenna Design

In this paper, a hybrid multiobjective evolutionary algorithm, MOEA/D-GO (Multiobjective Evolutionary Algorithm Based on Decomposition combined with Enhanced Genetic Operators), is proposed for fragment-type antenna design. It combines the ability and e-ciency of MOEA/D to deal with multiobjective optimization problems with the speciflc character of two-dimensional chromosome coding of genetic algorithm. And enhanced genetic operators are also introduced to generate new individuals. Numerical results of a set of six multiobjective 0/1 knapsack problems show that MOEA/D- GO with weighted sum decomposition approach outperforms original MOEA/D and MOEA/D-PR (MOEA/D combined with Path- Relinking operator). Then it's applied to optimize a CPW-fed monopole antenna to achieve band-notch characteristic. Both numerical and test results show that MOEA/D-GO is promising for solving multiobjective optimization problems about fragmented antenna.
1 A Compliant exoskeleton for multi-planar upper limb physiotherapy and training

In general, treatment of full or partial loss of fu nction in the upper limb due to injury relies on extremely labour intensive physiotherapy procedures . Although mechanical assistive device exist for li mbs this is rare for the upper body. In this paper we p r sent a seven degree of motion prototype upper arm training/physiotherapy (exoskeleton) system. The t otal weight of the uncompensated orthosis is less t han 2kg. This low mass is primarily due to the use of a new range of pneumatic Muscle Actuators (pMA) as power source for the system. This type of actuator , which has also an excellent power/weight ratio, m eets the need for safety, simplicity and lightness. The work presented focuses on the physiotherapy and tra ining control architecture used to make the system a mult i-functionality facility which permits the executio n of physiotherapy and training regimes under isokinetic , isotonic and training mode operation.
An Adaptive Grey Fuzzy PID Controller With Variable Prediction Horizon

The concept of grey system theory, which has a certain prediction capability, offers an alternative approach for various kinds of conventional control methods, such as PID control and fuzzy control. For instance, grey PID type fuzzy controller designed in this paper, can predict the future output values of the system accurately. However, the forecasting step-size of the grey controller determines the forecasting value. When the step-size of the grey controller is large, it will cause over compensation, resulting in a slow system response. Conversely, a smaller step-size will make the system respond faster but cause larger overshoots. In order to obtain a better controller performance, another fuzzy controller is designed for changing the step-size of the grey controller. The value of the forecasting step-size is optimized according to the values of error and the derivative of the error. Moreover, the output of the grey controller is uptaded using the prediction error for better controller performance. It is clear that the proposed adaptive PID type fuzzy controller is effective in controlling such a non-linear system by changing the prediction horizon adaptively for real-time working.
Years of Wireless Ad Hoc Networking Research : What about Humanitarian and Disaster Relief Solutions ? What are we still missing ?

In the event of a disaster, the communication infrastructure can be partially or totally destroyed, or rendered unavailable due to high congestion. However, during such crisis situations, there is an acute need for information exchange for both rescue organizations and victims. Temporary communication solutions are thus of utmost importance until the infrastructure is restored. In this paper, we start by reviewing communication solutions – stemming from 30 years of research on ad hoc, mesh and delaytolerant networks – able to uphold communications during disasters when the communication infrastructure is destroyed, overloaded or not existing in the first place. We present how these solutions can be applied and summarize the advantages and disadvantages of each unique approach. In a second part, we present, Twimight, a Twitter application relying on delay-tolerant opportunistic communications to spread tweets and sensor data in an epidemic fashion. Twimight is an open source Twitter client for Android phones featured with a “disaster mode”, which users enable upon losing connectivity. In the disaster mode, tweets are not sent to the Twitter server but stored on the phone, carried around as people move, and forwarded opportunistically when in proximity with other phones. Eventually, we demonstrate how opportunistic technologies such as Twimight can be of great value right after a disaster by enabling the self-organization of victims and a better coordination with first rescue organizations. We discuss the main challenges to overcome and provide directions for future research both non-technical (e.g. user adoption of technology) and technical (e.g. security and data privacy).
Study of magnetic field measurement technique based on grey theory & fuzzy logic

The conventional magnetic field measuring method with equal interval, which will result in sampling points distribute sparsely when magnetic field changes drastically while densely when magnetic field changes slightly, can not meet the measurement requirements of radar klystron. By analyzing the control model of sampling position, a new measurement method based on grey theory and fuzzy logic is proposed. It can adjust the measurement position dynamically according to the change trend of magnetic field intensity. Experiments show that this method can achieve better measurement control effects in application.
Manipulation of pH Shift to Enhance the Growth and Antibiotic Activity of Xenorhabdus nematophila

To evaluate the effects of pH control strategy on cell growth and the production of antibiotic (cyclo(2-Me-BABA-Gly)) by Xenorhabdus nematophila and enhance the antibiotic activity. The effects of uncontrolled- (different initial pH) and controlled-pH (different constant pH and pH-shift) operations on cell growth and antibiotic activity of X. nematophila YL00I were examined. Experiments showed that the optimal initial pH for cell growth and antibiotic production of X. nematophila YL001 occurred at 7.0. Under different constant pH, a pH level of 7.5 was found to be optimal for biomass and antibiotic activity at 23.71 g/L and 100.0 U/mL, respectively. Based on the kinetic information relating to the different constant pH effects on the fermentation of X. nematophila YL001, a two-stage pH control strategy in which pH 6.5 was maintained for the first 24 h, and then switched to 7.5 after 24 h, was established to improve biomass production and antibiotic activity. By applying this pH-shift strategy, the maximal antibiotic activity and productivity were significantly improved and reaching 185.0 U/mL and 4.41 U/mL/h, respectively, compared to values obtained from constant pH operation (100.0 U/mL and 1.39 U/mL/h).
A comparison of methods for clustering electrophysiological multineuron recordings

Techniques for the automatic clustering of extracellular multineuron recordings from the nervous system are compared for efficiency and accuracy. Selected waveforms were combined with noise to form test data with known classifications. After identical preprocessing using a Schmitt trigger threshold detector, the K-means, template matching and ART2 algorithms were applied to the same data. Measurements of the efficiency and utility of the three algorithms are presented using both the raw waveforms and the weightings of the first two principal components. Additionally, all three algorithms were tested with data obtained from electrophysiological experiments.
LOW BIT RATE VIDEO QUALITY ASSESSMENT BASED ON PERCEPTUAL CHARACTERISTICS

Peak signal-to-noise ratio (PSNR) is not a good measure of perceived picture quality, especially at low bit rates of coding. This paper proposes a new approach for computing perceptual distortion for visual signal in order to provide an objective measure for perceptual quality at low bit rate coding in typically mobile communications. The regions with three major perceptually disturbing artefacts, namely, damaged edge, blockiness and ringing, are detected as the basis of assessment. The correlation of the metric with human perception has been demonstrated with low bit rate CIF test data.
NON-RECTANGULAR EMBEDDED PROGRAMMABLE LOGIC CORES

ii List of Figures and Tables . vi Acknowledgments. ix Overview and Introduction . 1 1.1 Motivation. 1 1.2 Research Goals. 6 1.3 Organization of This Thesis . 7 Background and Previous Work . 9 2.1 EPLC Architecture . 9 2.1.1 Logic Resources. 11 2.1.2 Routing Resources. 14 Routing Between Logic Blocks. 15 Routing Inside Logic Blocks . 17 2.2 CAD for EPLC’s. 17 2.2.1 Placement. 19 2.2.2 Routing. 22 2.3 Focus and Contributions of This Thesis . 25 A Specification Method for Non-Rectangular EPLC’s. 27
Malware Message Analysis through Binary Traces

—Many malware trigger their malicious behaviors only if they detect some particular conditions from the environment. Under normal conditions these behaviors are hidden deeply under obfuscated codes, but they may be activated at any time by a Command and Control (C and C) server. However, connections to the C and C are not completely stealthy. We propose to analyse the way messages are operated by malware to characterize their behavior.
Admission control for variable bit rate traffic using variable service interval in IEEE 802.11e WLANs

The IEEE 802.11 working group is currently working on the standard IEEE 802.11e and introduces the hybrid coordination function (HCF) to provide better QoS support to real-time traffic. A reference design of simple scheduling and admission control algorithm is proposed in a TGe consensus proposal. However, this scheduling and admission control unit only consider the mean data rate and mean packet size. The rate and packet size variation are not taken into account. Thus, it is only efficient to CBR traffic and the packet loss rate of VBR traffic may be very high. In W. F. Fan et al. (Aug. 2004), we analyzed the packet loss rate of the reference scheme and proposed a new method to determine the effective TXOP duration for admission control so that the packet loss rate of VBR flows can be guaranteed. In both reference and our proposed scheme, all stations use fixed schedule service interval (SI) which is the minimum of all maximum service interval of all admitted flows. Thus, maximum packet delay of all stations is limited by the most stringent SI and some traffic with larger delay bound may be over-guaranteed. Also, the efficiency of the admission control scheme in W. F. Fan et al. (Aug. 2004), becomes lower than that of the reference one. In this paper, we extend our admission control scheme by using variable service interval to improve the efficiency about 20% - 30% and avoid over guarantee on packet delay. Also, the packet loss rate of VBR traffic can be guaranteed