Miracle-dz/UniFAR-FTUs huggingface dataset:
An adaptive edge detection algorithm based on gray-scale morphology

The method of image edge detection algorithm based on the traditional mathematical morphology has good ability to filter noise. But the method of using single form and single scale form element to edge the image has pertinence so the generality is weak. An algorithm of adaptive grayscale image edge detection based on multi-scale and multi-form is proposed in this paper. The image is processed with different shapes and dimensions of structural elements, and the adaptively weights are calculated according to information entropy. And we build a series-parallel form of edge detector. At last, we can get the final edge image after the fusion of each result from single element according to the series-parallel edge detector. The results of simulation show that compared with several conventional edge detection algorithms, the proposed algorithm can not only filter most of noise but also retain good edge details.
Noise Mitigation for Target Tracking in Wireless Acoustic Sensor Networks

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.
Linear GaN MMIC Combined Power Amplifiers for 7-GHz Microwave Backhaul

This paper presents the design of two combined linear power amplifiers for 7-GHz microwave backhaul, realized in 0.25- μm GaN on SiC monolithic technology. Both modules are based on a combined class-AB structure conceived for maximum back-off efficiency and reduced phase distortion, which are important requirements in backhaul systems. Different second harmonic loads are exploited in the two power amplifiers, leading to different performance in terms of output power, bandwidth and efficiency. The two stages exhibit a saturated output power in excess of 35 and 36 dBm on 16% and 26% of fractional bandwidth, respectively; moreover, the measured average efficiency in the presence of modulated signals with 7.4-dB peak-to-average power ratio is 18% and 25%. Simulations and experimental results demonstrate that the second-harmonic load has little influence on the linearity of the proposed amplifiers. Compliance with the spectrum emission mask defined for the targeted application has been achieved through low-order polynomial digital predistortion, thus demonstrating the high linearity of the stages. A comparison with a Doherty amplifier realized in the same technology and for the same application shows that the two proposed stages need a simpler predistorter to achieve the linearity required by standard specifications.
Situation-aware radio resource management for multi-rate MC-CDMA wireless networks targeted at multimedia data exchanges in local areas

In this work, a novel methodology for radio resource management is considered for multi-rate MC-CDMA WLAN indoor networking. The proposed strategy is based on resource reallocation and rate adaptation depending on the network situation, monitored in terms of achieved QoS by an intelligent access-point (AP). As they access the medium, all users send bit-rate requests on the basis of their application requirements. Then, the AP monitors the QoS in terms of frame-error-rate (FER) and decides a) to reallocate the radio resources (in terms of number of orthogonal subchannels) and b) to reduce the data rate, in order to improve throughput performances for those users penalized by heavy FER. The "rate downshift" process is continued until the FER measured by the AP allows data transfer with an acceptable QoS. The intelligent AP can also issue a "rate upshift" for users previously downshifted, or in presence of explicit requests, when the channel situation improves. Simulation results underline a general improvement of the aggregated throughput deriving from adaptively manage the QoS requirements with respect to the network situation, thus enabling good resource usage with the WLAN cell.
One-class Gaussian process regressor for quality assessment of transperineal ultrasound images

The use of ultrasound guidance in prostate cancer radiotherapy workflows is not widespread. This can be partially attributed to the need for image interpretation by a trained operator during ultrasound image acquisition. In this work, a one-class regressor, based on DenseNet and Gaussian processes, was implemented to assess automatically the quality of transperineal ultrasound images of the male pelvic region. The implemented deep learning approach achieved a scoring accuracy of 94%, a specificity of 95% and a sensitivity of 93% with respect to the majority vote of three experts, which was comparable with the results of these experts. This is the first step towards a fully automatic workflow, which could potentially remove the need for image interpretation and thereby make the use of ultrasound imaging, which allows real-time volumetric organ tracking in the RT environment, more appealing for hospitals.
A Novel Graphical Model Approach to Segmenting Cell Images

Successful biological image analysis usually requires satisfactory segmentations to identify regions of interest as an intermediate step. Here we present a novel graphical model approach for segmentation of multi-cell yeast images acquired by fluorescence microscopy. Yeast cells are often clustered together, so they are hard to segment by conventional techniques. Our approach assumes that two parallel images are available for each field: an image containing information about the nuclear positions (such as an image of a DNA probe) and an image containing information about the cell boundaries (such as a differential interference contrast, or DIC, image). The nuclear information provides an initial assignment of whether each pixel belongs to the background or one of the cells. The boundary information is used to estimate the probability that any two pixels in the graph are separated by a cell boundary. From these two kinds of information, we construct a graph that links nearby pairs of pixels, and seek to infer a good segmentation from this graph. We pose this problem as inference in a Bayes network, and use a fast approximation approach to iteratively improve the estimated probability of each class for each pixel. The resulting algorithm can efficiently generate segmentation masks which are highly consistent with hand-labeled data, and results suggest that the work will be of particular use for large scale determination of protein location patterns by automated microscopy
A genetic algorithm based approach for systematic SOM clustering of directory metadata

Directories play an important role in describing resources and enabling information sharing within and among organizations. To communicate effectively, directories must resolve differing structures and vocabularies. This paper proposes a systematic approach to address the interoperability of directories. The approach couples a genetic algorithm with a neural network based clustering algorithm - Self-Organizing Maps (SOM) - to systematically cluster directory metadata, highlight similar structures, recognize developing patterns of practice, and ultimately promote homogeneity among the directories. To evaluate the effectiveness of the proposed approach, an experiment on Lightweight Directory Access Protocol (LDAP) directory metadata is conducted. The experimental results show that a genetic algorithm can discover parameter values for a SOM algorithm such that the computer clustering results are comparable to that of domain experts. The proposed approach provides an effective mechanism to systematically cluster directory metadata and promote homogeneity among them.
Experimental determination of lifetime engineering effects on free-carrier concentration

The effects of lifetime engineering processes in fast recovery power diodes are measured by using an internal IR-laser deflection (IIR-LD) set-up. To evidence the local lifetime killing effects on such devices, a comparison between the measured physical parameters of irradiated and unirradiated diodes, free-carrier concentration and their decay time, is performed. A reduction of free-carrier concentration profile and local lifetime is observed in the region of the ion penetration range. Furthermore, even at low fluences, ion irradiation impact on the free-carrier concentration has been measured. The measured free-carrier concentrations are corroborated by simulation results, obtaining good qualitative agreement
Molecular Analysis of the Simultaneous Production of Two SHV-Type Extended-Spectrum Beta-Lactamases in a Clinical Isolate of Enterobacter cloacae by Using Single-Nucleotide Polymorphism Genotyping

ABSTRACT Bacteria that simultaneously produce multiple extended-spectrum beta-lactamases are frequently isolated. We report an Enterobacter cloacae isolate, ES24, producing four different beta-lactamases (AmpC type beta-lactamase, TEM-1, SHV-7, and a novel extended-spectrum beta-lactamase, SHV-30). Direct sequencing of blaSHV gene products gave a “double peak” at position 703, suggesting the presence of more than one allele. Using fluorescence resonance energy transfer real-time PCR to detect single-nucleotide polymorphisms, we were able to distinguish two different blaSHV genes in a single isolate. This may prove to be a useful technique in surveys of beta-lactamase production in contemporary clinical isolates.
GDNF FAMILY RECEPTORS IN PERIPHERAL TARGET INNERVATION AND HORMONE PRODUCTION

8 REVIEW OF THE LITERATURE 9 Introduction 9 Glial cell line-derived neurotrophic factor family 9 GDNF family ligands 9 GDNF family receptors 12 RET-dependent GDNF family signalling 14 RET-independent GDNF family signalling 18 Derivatives of the neural crest: peripheral nervous system and neuroendocrine cells 19 Somatic sensory nervous system 20 Sympathetic nervous system and the adrenal gland 24 Parasympathetic nervous system 26 Enteric nervous system 27 Thyroid C-cells 29 In vivo functions of GDNF family factors 30 GDNF/GFRα1/Ret signalling in the development of the enteric and parasympathetic nervous systems 31 GDNF/GFRα1/Ret signalling outside the nervous system 32 NRTN/GFRα2 signalling in the development of the parasympathetic and enteric neurons 33 GFRα3/ARTN signalling in the migration and initial axon outgrowth of sympathetic neurons 34 PSPN may protect the brain from ischaemia 35 RET mutations in human diseases 35 AIMS OF THE STUDY 37 MATERIALS AND METHODS 38 RESULTS AND DISCUSSION 41 A. GFRα2 in peripheral neurons 41 The development of intrapancreatic ganglia requires GFRα2 41 GFRα2 is needed to maintain the cell size of cholinergic sympathetic neurons . 42 GFRα2 is required to maintain the cell size of IB4-positive sensory neurons . 43 B. GFRα2 in peripheral innervation 44
An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical Models

In this paper we compare Naive Bayes (NB) models, general Bayes Net (BN) models and Probabilistic Decision Graph (PDG) models w.r. t. accuracy and efficiency. As the basis for our analysis we use graphs of size vs. likelihood that show the theoretical capabilities of the models. We also measure accuracy and efficiency empirically by running exact inference algorithms on randomly generated queries. Our analysis supports previous results by showing good accuracy for NB models compared to both BN and PDG models. However, our results also shows that the advantage of the low complexity inference provided by NB models is not as significant as assessed in a previous study.
High Availability for Software DSM

Although a cluster of desktop machines is a viable option as a low-cost computing platform for parallel and distributed applications, such clusters are susceptible to failures as they comprise of multiple independent machines and networking components. In this paper, we develop mechanisms needed to make a software DSM system highly available. We present protocol enhancements needed to accomplish high availability, and develop the theoretical reasoning behind why the proposed system can tolerate a single node failure. The proposed scheme results in restarting the computation only on the failed node from a previous checkpoint, and does not induce forced roll-backs of non-faulty nodes. Further, the proposed protocol enhancements do not require additional messages in failure-free periods. Abstract Although a cluster of desktop machines is a viable option as a low-cost computing platform for parallel and distributed applications, such clusters are susceptible to failures as they comprise of multiple independent machines and networking components. In this paper, we develop mechanisms needed to make a software DSM system highly available. We present protocol enhancements needed to accomplish high availability, and develop the theoretical reasoning behind why the proposed system can tolerate a single node failure. The proposed scheme results in restarting the computation only on the failed node from a previous checkpoint, and does not induce forced roll-backs of non-faulty nodes. Further, the proposed protocol enhancements do not require additional messages in failure-free periods.
Self-stabilized Flocking of a Group of Mobile Robots under Memory Corruption

Robotics has been paid a lot attentions because of its wide applications, like explore unknown planet or rescue people after earthquake or fire. In a group of mobile robots, robots are usually weak and are easy to get crash, especially working in dangerous or harsh environment. Unfortunately, to the best of our knowledge, only a few studies address on robot failure, especially transient failure. Therefore, in this paper, based on a pair of fault tolerant flocking algorithms which we proposed, we discuss if it is possible to make robots work together once robots' memory experiences corruption. Otherwise, we further explore the reason and then try to revise the existing algorithm to make robots self-stabilized.
Integrated Systems in the Role of Integration of Education

Information society paradigm and program highly affect the higher education as well. The rapidly changing environment reflects both the contents and the organisation. The effects are significant concerning the ICT related departments and disciplines, but the IT technology can change very traditional subjects as philosophy radically. An interesting symptom of the always- conservative academic world: the organizational structure of the universities is very hierarchical, the knowledge transfer (what we call education) is fragmented, atomised. On the other way around the real world requirements are just the opposites: there is a vast demand for students and profes- sionals having the ability of integration, knowledge absorption. The general tendencies look a little bit more sharpened in the world of transition, in both the economic and social sense. During the last ten years Hungary went through an intensive development and changing phase in which the expe- riences of transition and coping with the information society requirements mixed up. In our paper we are going to illustrate a way to develop the teaching in the higher education on an integrated
Spaceborne radar interferometry for mine subsidence monitoring in Australia

Land surface deformation can be caused by underground mining activities. The maximum subsidence normally occurs directly above the location of the excavation of the coal seam. In the case where the longwall mining technique is applied, the magnitude and shape of the subsidence bowl are constrained by the longwall structure (pillar). This paper describes the use of satellite radar interferometry for monitoring surface subsidence due to underground mining, as a cost-effective geodetic technique and complementary to conventional ground surveying techniques. This paper uses data acquired by the current generation of SAR satellites the European ENVISAT and the Japanese ALOS to monitor ground subsidence in the southern highland coal field in NSW, Australia. An accumulated DInSAR subsidence mine map is produced using 6 successive ALOS acquisitions. The results are postanalysed with the aid of geographic information systems (GIS) and validated using ground survey data.
Raf/MEK/MAPK signaling stimulates the nuclear translocation and transactivating activity of FOXM1c

The forkhead box (FOX) transcription factor FOXM1 is ubiquitously expressed in proliferating cells. FOXM1 expression peaks at the G2/M phase of the cell cycle and its functional deficiency in mice leads to defects in mitosis. To investigate the role of FOXM1 in the cell cycle, we used synchronized hTERT-BJ1 fibroblasts to examine the cell cycle-dependent regulation of FOXM1 function. We observed that FOXM1 is localized mainly in the cytoplasm in cells at late-G1 and S phases. Nuclear translocation occurs just before entry into the G2/M phase and is associated with phosphorylation of FOXM1. Consistent with the dependency of FOXM1 function on mitogenic signals, nuclear translocation of FOXM1 requires activity of the Raf/MEK/MAPK signaling pathway and is enhanced by the MAPK activator aurintricarboxylic acid. This activating effect was suppressed by the MEK1/2 inhibitor U0126. In transient reporter assays, constitutively active MEK1 enhances the transactivating effect of FOXM1c, but not FOXM1b, on the cyclin B1 promoter. RT-PCR analysis confirmed that different cell lines and tissues predominantly express the FOXM1c transcript. Mutations of two ERK1/2 target sequences within FOXM1c completely abolish the MEK1 enhancing effect, suggesting a direct link between Raf/MEK/MAPK signaling and FOXM1 function. Importantly, inhibition of Raf/MEK/MAPK signaling by U0126 led to suppression of FOXM1 target gene expression and delayed progression through G2/M, verifying the functional relevance of FOXM1 activation by MEK1. In summary, we provide the first evidence that Raf/MEK/MAPK signaling exerts its G2/M regulatory effect via FOXM1c.
Protective or not? [visual distraction]

There is general consistency in research results on visual distraction and on visual-manual distraction. Visual tasks involving long periods of glance are negative for driving performance and negative for safety, while visual-manual tasks such as texting are particularly harmful to the safer performance of driving. As regards cognitive distraction, there is no such general consensus. Simulator studies have consistently shown that even hands-free phone conversations impair driving performance, while naturalistic studies conducted on real-world driving have generally shown that cognitive distraction in the form of hands-free mobile phone conversation is “protective”, i.e. reduces risk as compared to baseline driving without such conversation. This paper attempts to square the circle, and assess whether cognitive distraction can indeed make driving more safe. It reviews both the simulator and naturalistic studies as well as those that have analysed accident data, and seeks to solve the puzzle of apparent contradiction between the various research methodologies.
Agent Mediated Electronic Commerce IV : Designing Mechanisms and Systems , Springer Verlag , 2002 . ATTac-2001 : A Learning , Autonomous Bidding Agent

Auctions are becoming an increasingly popular method for tr ansacting business, especially over the Internet. This paper pres ents a general approach to building autonomous bidding agents to bid in multiple sim ultaneous auctions for interacting goods. The core of our approach is learning a model of the empirical price dynamics based on past data and using the model to a nalytically calculate, to the greatest extent possible, optimal bids. This approach is fully implemented asATTa -2001, a top-scoring agent in the second Trading Agent Competition (TAC-01). ATTa -2001 uses boosting techniques to learn conditional distributions of auction clearing prices. We present exper im nts demonstrating the effectiveness of this predictor relative to several rea son ble alternatives.
Genomic Comparison of the Closely Related Salmonella enterica Serovars Enteritidis and Dublin

The Enteritidis and Dublin serovars of Salmonella enterica are closely related, yet they differ significantly in pathogenicity and epidemiology. S. Enteritidis is a broad host range serovar that commonly causes gastroenteritis and infrequently causes invasive disease in humans. S. Dublin mainly colonizes cattle but upon infecting humans often results in invasive disease.To gain a broader view of the extent of these differences we conducted microarray-based comparative genomics between several field isolates from each serovar. Genome degradation has been correlated with host adaptation in Salmonella, thus we also compared at whole genome scale the available genomic sequences of them to evaluate pseudogene composition within each serovar. Microarray analysis revealed 3771 CDS shared by both serovars while 33 were only present in Enteritidis and 87 were exclusive to Dublin. Pseudogene evaluation showed 177 inactive CDS in S. Dublin which correspond to active genes in S. Enteritidis, nine of which are also inactive in the host adapted S. Gallinarum and S. Choleraesuis serovars. Sequencing of these 9 CDS in several S. Dublin clinical isolates revealed that they are pseudogenes in all of them, indicating that this feature is not peculiar to the sequenced strain. Among these CDS, shdA (Peyer´s patch colonization factor) and mglA (galactoside transport ATP binding protein), appear also to be inactive in the human adapted S. Typhi and S. Paratyphi A, suggesting that functionality of these genes may be relevant for the capacity of certain Salmonella serovars to infect a broad range of hosts.
Domain specific languages contextualized

Many software systems attempt to provide solutions to problems located in the real-world. Problem frames identify specific combinations, and interactions, of problems, real-world domains, and requirements. Domain-Specific Languages (DSL's) are exemplary in their ability to provide solutions to specific problem domains. This paper explores the relationship between problem frames, that describe the types of problems that a software system is attempting to address, and DSL decision patterns that detail when a DSL might prove useful. Thirty-five DSL case studies are used in mapping the decision patterns to their corresponding problem frames. It is shown that all of the decision patterns map to transformation or workpieces problems. This mapping serves as a guide linking a given problem to appropriate decision patterns, and ultimately to DSL employment.