Miracle-dz/UniFAR-FTUs huggingface dataset:
Architecture of a network performance monitor for application services on multi-clouds

Recently, many new services are being deployed on the cloud due to its flexibility of on-demand allocation and deallocation of computing resources. As the services require more advanced features such as fault-tolerance and high performance, much interest is focused on the multi-clouds. Hence, the needs for effectively managing the quality of services on multi-clouds emerge rapidly. Among the many factors affecting the quality of services, we focus on the network performance in this paper. We identify essential requirements of network performance monitor for multi-clouds and propose an architecture. In particular we address the necessity of supporting external agents and discuss how to integrate with them in a flexible and extensible way. In addition, the issues of timely delivery and off-line analysis of measured results are addressed.
Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.
EQUIVALENT TRANSMISSION LINE MODEL

In this paper we propose the design of bow-tie antenna based on a simple modified transmission line model. The developed model is simple, accurate and takes into account all the antenna characteristics. The simulated antennas are designed to resonate at the frequencies 2.4 GHz and 8 GHz corresponding to RFID and Radars applications. To validate this last the obtained simulation results are compared to those obtained by the moment’s method (Agilent Momentum software). Using this transmission line approach the resonant frequency, input impedance, return loss can be determined simultaneously. The paper reports several simulation results that confirm the validity of the developed model. The obtained results are then presented and discussed.
The Use of Green Taxes in Denmark for the Control of the Aquatic Environment

In preparation for the Aquatic Environment Plan III, separate economic models were developed to assess the use of economic instruments to control for nitrogen and phosphorus pollution fromagriculture. These included taxes on various inputs; taxes on surpluses (inputs less outputs) at the national, sectoral and farm levels; and tradable quotas. The results indicated that to achieve the same reduction in nutrient surplus (a proxy for pollution) the adjustment costs for farmers were much higher when inputs were taxed than when surplus were taxed. While the government decided to not adopt a nitrogen tax (because of the success of the current regulation regime) it has introduced a tax on mineral phosphorus in feed (while having the largest adjustment cost for farmers this tax is simpler to administer). A review of the Danish pesticide tax suggested that it has been effective in moving pesticide consumption closer towards the substance quantity targets.
Association of Serum Tumor Necrosis Factor-Related Apoptosis Inducing Ligand with Body Fat Distribution as Assessed by Dual X-Rays Absorptiometry

A low chronic inflammation mediated by cytokine release is considered a major pathogenic mechanism accounting for the higher risk of cardiovascular disease in the overweight/obese population. In this context, although the existence of a possible interaction between soluble tumor necrosis factor- (TNF-) related apoptosis inducing ligand (TRAIL) and quantity and localization, of adiposity in the body has been hypothesized, no studies have yet investigated this link by radiologic techniques able to assess directly fat mass (FM) in different body regions. To address this issue, we assessed body fat distribution by dual X-rays absorptiometry (DXA) in a sample of 103 women and investigated the possible association between the derived adiposity measures and serum TRAIL concentration. The level of TRAIL showed a positive and independent correlation with arms FM (P < 0.05), trunk FM (P < 0.001) and trunk FM% (P < 0.05), total FM and total FM% (P < 0.001 for both), and an inverse association with legs FM% (P < 0.05). Only trunk FM retained a significant correlation (P < 0.05) with TRAIL after adjusting for all the other indices of regional adiposity. In conclusion, from our study it emerged a significant and independent association of serum TRAIL levels with overall, and, mainly, central adiposity. Further studies are needed to longitudinally investigate the cause-effect relationship between change in body fat distribution and TRAIL.
The Effects of Histaminergic Agents in the Nucleus Accumbens of Rats in the Elevated Plus-Maze Test of Anxiety

Objective The nucleus accumbens (NAc) receive histaminergic neurons from tuberomammillary nuclei. There are reports indicating that central histamine systems are involved in many physiological behavioral processes, including anxiety. The aim of the present study was to assess whether the histaminergic system of the NAc is involved in anxiety-related behaviors. Methods Rats were anesthetized with intra-peritoneal injection of ketamine hydrochloride, plus xylazine and then were placed in a stereotaxic apparatus. In addition, two stainless-steel cannuale were placed 2 mm above the nucleus accumbens shell. Seven days after recovery from surgery, the behavioral testing was started. As a model of anxiety, the elevated plus maze which is a useful test to investigate the effects of anxiogenic or anxiolytic drugs in rodents, was used in male Wistar rats. Results Intra-NAc administration of histamine (0.01, 0.1 and 1 µg/rat) increased the percentage of open arm time (%OAT) and open arm entries (%OAE), but not locomotor activity, indicating an anxiolytic response. Furthermore, bilateral microinjections of different doses of the H1 receptor antagonist pyrilamine (0.001, 0.01, 0.1 and 1 µg/rat) or the H2 receptor antagonist ranitidine (0.001, 0.01, 0.1 and 1 µg/rat) into the NAc increased %OAT and %OAE, but not locomotor activity. However, both histamine and histamine receptor antagonists showed an anxiolytic-like effect; the antagonists (1 µg/rat) also decreased the histamine response. Conclusion The results may indicate a modulatory effect for the H1 and H2 histamine receptors of nucleus accumbens in the anxiety behavior of rats.
Object-Based Analysis of Airborne LiDAR Data for Building Change Detection

Building change detection is useful for land management, disaster assessment, illegal building identification, urban growth monitoring, and geographic information database updating. This study proposes an automatic method that applies object-based analysis to multi-temporal point cloud data to detect building changes. The aim of this building change detection method is to identify areas that have changed and to obtain from-to information. In this method, the data are first preprocessed to generate two sets of digital surface models (DSMs), digital elevation models, and normalized DSMs from registered old and new point cloud data. Thereafter, on the basis of differential DSM, candidates for changed building objects are identified from the points in the smooth areas by using a connected component analysis technique. The random sample consensus fitting algorithm is then used to distinguish the true changed buildings from trees. The changed building objects are classified as “newly built”, “taller”, “demolished” or “lower” by using rule-based analysis. Finally, a test data set consisting of many buildings of different types in an 8.5 km2 area is selected for the experiment. In the test data set, the method correctly detects 97.8% of buildings larger than 50 m2. The accuracy of the method is 91.2%. Furthermore, to decrease the workload of subsequent manual checking of the result, the confidence index for each changed object is computed on the basis of object features.
Shape Matching by Region Grouping

In this paper, we propose a novel region grouping approach to shape matching. It is proposed as an alternative region based approach to the traditional edge based shape matching using distance transforms. It has the advantage of obtaining a higher detection rate and obtaining meaningful object segmentation simultaneously. Each image is first segmented into image regions, and possible matches are found among the regions based on a proposed probabilistic similarity measure to the exemplars. We evaluate this new approach against edge based matching using Chamfer and Hausdorff distances. Pros and cons of the proposed method are discussed.
Signal processing applications for cognitive networks: State of the art

Cognitive radio is one of the most promising techniques of wireless communications, due to its many applications. Cognitive networks have the capability to congregate different cognitive users via cooperative spectrum sensing. Examples of cognitive networks can be found in important and different applications, such as digital television and wireless sensor networks. The objective of this paper is to analyze how signal processing techniques are used to provide reliable performance in such networks. Applications of signal processing in cognitive networks are presented and detailed.
Search based Software Testing Technique for Structural Test Case Generation

Software testing is an important activity in the software development life cycle and it is widely used validation approach in software industry, deployed by programmers and testers. The program with the moderate complexity cannot be tested completely. Innovative methods are needed to perform testing as a whole and unit testing in particular with minimum effort and time. Unit testing is mostly done by developers under a lot of schedule pressure since the software companies find a compromise among functionality, time to market and quality. Thus there is a need for reducing unit testing time by optimizing and automating the process. Test suite generation is an error-prone, tedious and time consuming part of unit testing. Two techniques are proposed to automatically generate test cases from the input domain using scatter search and tabu search for branch coverage criteria with respect to cyclomatic complexity measure.
Marinari-Parisi and Supersymmetric Collective Field Theory

A field theoretic formulation of the Marinari–Parisi supersymmetric matrix model is established and shown to be equivalent to a recently proposed supersymmetrization of the bosonic collective string field theory. It also corresponds to a continuum description of super-Calogero models. The perturbation theory of the model is developed and, in this approach, an infinite sequence of vertices is generated. A class of potentials is identified for which the spectrum is that of a massless boson and Majorana fermion. For the harmonic oscillator case, the cubic vertices are obtained in an oscillator basis. For a rather general class of potentials it is argued that one cannot generate from Marinari–Parisi models a continuum limit similar to that of the d = 1 bosonic string.
Tangible Viewports: Getting Out of Flatland in Desktop Environments

Spatial augmented reality and tangible interaction enrich the standard computer I/O space. Systems based on such modalities offer new user experiences and open up interesting perspectives in various fields. On the other hand, such systems tend to live outside the standard desktop paradigm and, as a consequence, they do not benefit from the richness and versatility of desktop environments. In this work, we propose to join together physical visualization and tangible interaction within a standard desktop environment. We introduce the concept of Tangible Viewport, an on-screen window that creates a dynamic link between augmented objects and computer screens, allowing a screen-based cursor to move onto the object in a seamless manner. We describe an implementation of this concept and explore the interaction space around it. A preliminary evaluation shows the metaphor is transparent to the users while providing the benefits of tangibility.
Visualization and structure analysis for efficient XML design

XML is extensible data format and used in various areas. Thus it is proposed by independent criteria and updated frequently. But structures designed without explicit guidelines decrease dependencies in the future extension and efficiencies of parsing program. In this paper we study general structure and suggest direction for designs of efficient structures based on the relation between parsing time and complexity. We use parser for structure analysis, and propose visualization method using Cascade Style Sheet (CSS). Proposed method will provide structure analysis function for XML format designing continuously, and identify efficient structures.
Exploring the Factors Associated with Expert Systems Success

As the widespread use and company dependency on expert systems (ES) incease, so does the need to assess their value and to ensure implementation success. This study identifies and empirically tests eight major variables proposed in the literature as determinants of ES success, in this case measured in terms of user satisfactions. IBM's Corporate Manufacturing Expert Systems Project Center collected information from 69 project managers to support the study. The results clearly support the hypothesized relationships and suggest the need for ES project managers to pay special attention to these determinants of ES implementation success. ES success is directily related to the quality of developers and the ES shells used, end-user characteristcs, and degree of user involvement in ES development, as each has been defined in this study. For exploratory purposes, the component items for each of these major variables were correlated with the components of user satisfaction. Based on the results, several recommendations are proposed for ES project managers to enhance the likelihood of project success, including: adding problem difficulty as a criteriaon for ES application selection; increasing ES developer training to improve people skills; having the ability to model and use a systems approach in solving business problems; sharping end-user attitudes and expectations regarding ES; improving the selction of domain experts; more thoroughly understanding the ES impact on end-user jobs; restricting the acquistion of ES shells based on a rpopsoed set of criteria; and ensuring a proper match of ES development techniques and tools to the business problem at hand.
Visualisation of complex systems

There are a large number of computer based, and other, systems which are composed of large numbers of interacting components. Examples include large software systems, the world wide web and a wide range of information systems. Understanding and manipulating the structure and behaviour of these systems is extraordinarily difficult, even when the systems (eg. programs) have been well designed and engineered. The approach described in this paper is to maintain a representation of the system within a virtual reality. The organisation of the components within the virtual reality is determined by behaviours attached to the components which, typically, leads to a spatial organisation which reflects the semantic structure of the system. A prototype implementation of a development environment for the SELF programming language is described. This system shows how effectively previously hidden structure can emerge. There is also some discussion and examples of further work hich is being undertaken to further support the visualisation and manipulation being undertaken by the user.
Molecular Characterization of Pneumococcal Isolates from Pets and Laboratory Animals

Background Between 1986 and 2008 Streptococcus pneumoniae was isolated from 41 pets/zoo animals (guinea pigs (n = 17), cats (n = 12), horses (n = 4), dogs (n = 3), dolphins (n = 2), rat (n = 2), gorilla (n = 1)) treated in medical veterinary laboratories and zoos, and 44 laboratory animals (mastomys (multimammate mice; n = 32), mice (n = 6), rats (n = 4), guinea pigs (n = 2)) during routine health monitoring in an animal facility. S. pneumoniae was isolated from nose, lung and respiratory tract, eye, ear and other sites. Methodology/Principal Findings Carriage of the same isolate of S. pneumoniae over a period of up to 22 weeks was shown for four mastomys. Forty-one animals showed disease symptoms. Pneumococcal isolates were characterized by optochin sensitivity, bile solubility, DNA hybridization, pneumolysin PCR, serotyping and multilocus sequence typing. Eighteen of the 32 mastomys isolates (56%) were optochin resistant, all other isolates were optochin susceptible. All mastomys isolates were serotype 14, all guinea pig isolates serotype 19F, all horse isolates serotype 3. Rats had serotypes 14 or 19A, mice 33A or 33F. Dolphins had serotype 23F, the gorilla serotype 14. Cats and dogs had many different serotypes. Four isolates were resistant to macrolides, three isolates also to clindamycin and tetracyclin. Mastomys isolates were sequence type (ST) 15 (serotype 14), an ST/serotype combination commonly found in human isolates. Cats, dogs, pet rats, gorilla and dolphins showed various human ST/serotype combinations. Lab rats and lab mice showed single locus variants (SLV) of human STs, in human ST/serotype combinations. All guinea pig isolates showed the same completely new combination of known alleles. The horse isolates showed an unknown allele combination and three new alleles. Conclusions/Significance The isolates found in mastomys, mice, rats, cats, dogs, gorilla and dolphins are most likely identical to human pneumococcal isolates. Isolates from guinea pigs and horses appear to be specialized clones for these animals. Our data redraw attention to the fact that pneumococci are not strictly human pathogens. Pet animals that live in close contact to humans, especially children, can be infected by human isolates and also carriage of even resistant isolates is a realistic possibility.
A 200Mb/s 3–5GHz Ping-Pong structure UWB transmitter using synchronized pulse position modulation

In this paper, a 3-5GHz IR-UWB transmitter based on 0. 18μm CMOS is presented. The transmitter has the features of low power and low complexity by using a symmetrical “Ping-Pong” structure. Two digital transmitters are combined to overcome the noise due to effect of charge injection. A synchronized pulse position modulation and demodulation method is proposed. It improves the efficiency of the transmitter while keeping the receiver simplified. A template-based digital delay generation scheme is used to improve the delay accuracy. Measurement results show that no unwanted spur is generated. The transmitter consumes 36 pJ/b to achieve a maximum data rate of 200 Mb/s.
Multitask Learning for Spoken Language Understanding

In this paper, we present a multitask learning (MTL) method for intent classification in goal oriented human-machine spoken dialog systems. MTL aims at training tasks in parallel while using a shared representation. What is learned for each task can help other tasks be learned better. Our goal is to automatically re-use the existing labeled data from various applications, which are similar but may have different intents or intent distributions, in order to improve the performance. For this purpose, we propose an automated intent mapping algorithm across applications. We also propose employing active learning to selectively sample the data to be re-used. Our results indicate that we can achieve significant improvements in intent classification performance especially when the labeled data size is limited
Greedy Clique Decomposition for Symbolic Satisfiability Solving

(1) School of Information Science and Technology Beijing Forestry University China; (2) Naveen Jindal School of Management The University of Texas at Dallas United States; (3) College of Mathematics Physics and Information Engineering Zhejiang Normal University Jinhua China; (4) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China
Fault diagnosis of identical brushless DC motors under patterns of state change

In this paper we proposed a model of a fault diagnosis expert system with high reliability to compare identical well-functioning motors. The purpose of the survey was to determine if any differences exit among these identical motors and to identify exactly what these differences were, if in fact they were found. Using measured data for many identical brushless dc motors, this study attempted to find out whether normal and fault can be classified by each other. Measured data was analyzed using the change of state model (CSM). Based on a proposed CSM method, the effect of a different normal state is minimized and the detection of fault is improved in identical motor system. Experimental results are presented to prove that CSM method could be a useful tool for diagnosing the condition of identical BLDC motors.
An energy-efficient mobility-supporting MAC protocol in wireless sensor networks

Although mobile applications are an essential characteristic of wireless sensor networks, most existing media access control (MAC) protocols focus primarily on static networks. In these protocols, fixed periodic neighbor discovery and schedule updating are used to connect and synchronize neighbors to provide successful data transmission; however, they cannot adapt to mobile speed variation and degrade the network performance dramatically. In this paper, we propose a mobile-supporting mechanism for MAC protocols, in which the decision to update the neighbors of a mobile node is made adaptively according to the mobile speed. Analysis and simulation results demonstrate that the mechanism efficiently avoids the disconnection of a mobile node from its neighbors and achieves a better performance as compared with fixed periodic neighbor discovery.