Miracle-dz/UniFAR-FTUs huggingface dataset:
An architecture of distributed co-simulation backplane

This paper implements a distributed co-simulation backplane based on the client-server model. The backplane is the channel through which the different simulators (solvers), communicate. The proposed architecture is based on running the different simulators on different workstations. The simulators are connected together through a high speed LAN (Fast-Ethernet). The backplane is a multi-threaded TCP server running on one of the workstations connected to the same LAN. The proposed architecture gets use of the available networks evolution and resources, it offloads each workstation and adds only the overhead of communication to the original simulator.
Electoral Campaigns and Relation Mining: Extracting Semantic Network Data from Newspaper Articles

ABSTRACT Among the many applications in social science for the entry and management of data, there are only a few software packages that apply natural language processing to identify semantic concepts such as issue categories or political statements by actors. Although these procedures usually allow efficient data collection, most have difficulty in achieving sufficient accuracy because of the high complexity and mutual relationships of the variables used in the social sciences. To address these flaws, we suggest a (semi-) automatic annotation approach that implements an innovative coding method (Core Sentence Analysis) by computational linguistic techniques (mainly entity recognition, concept identification, and dependency parsing). Although such computational linguistic tools have been readily available for quite a long time, social scientists have made astonishingly little use of them. The principal aim of this article is to gather data on party-issue relationships from newspaper articles. In the first stage, we try to recognize relations between parties and issues with a fully automated system. This recognition is extensively tested against manually annotated data of the coverage in the boulevard newspaper Blick of the Swiss national parliamentary elections of 2003 and 2007. In the second stage, we discuss possibilities for extending our approach, such as by enriching these relations with directional measures indicating their polarity.
A comprehensive comparative performance analysis of Laplacianfaces and Eigenfaces for face recognition

Abstract This paper provides a comprehensive comparative analysis of the performance of locality preserving projections (LPPs)‐based Laplacianfaces, which is a recently introduced algorithm with the more traditional, principal component analysis (PCA)‐based Eigenfaces. All possible combinations of neighbourhood defining distance metrics, classifier distance metrics and number of retained eigenvectors have been tried on different imaging environments. The FERET facial database was chosen which provides enough diversity in illumination, facial expressions and aging. CsuFaceIdEval, an open source platform, is used for this comparison and recognition rates are studied in detail. As a result of our detailed analysis, we provide best combination of selected parameters to extract the best results from these two algorithms.
A Novel Collaborative Filtering Recommendation Approach Based on Field Authorities

This paper presents a novel collaborative filtering recommendation algorithm based on field authorities which simulates the real life word of mouth recommendation mode. It uses the specialistic knowledge from field authorities of different genres, and successfully addresses data sparsity and noise problems existing in traditional collaborative filtering. Meanwhile it also improves prediction accuracy and saves computational overhead effectively. Experiments on MovieLens datasets show that the accuracy of our algorithm is significantly higher than collaborative filtering approach based on experts, and has larger scope because of no external data limitations. Meanwhile, compared to traditional k-NN collaborative filtering, our algorithm has a better performance both in MAE and precision experiments, and the computational overhead has a decrease of 19.2% while they provide the same accuracy level.
Statistics-Based Interactive Evolutionary Computation for Color Scheme Search

This paper presents a statistics-based interactive evolutionary computation (IEC) method for color scheme searches. Generally, people who do not have sufficient skill or knowledge of colors need to devote considerable time and effort to creating color schemes. To overcome this problem, we propose a statistics-based interactive genetic algorithm and four similarity search functions. This combination allows users to easily and effectively obtain appropriate color schemes. To investigate the performance of the proposed method, we conducted two experiments and confirmed that the implemented application of the proposed method allows users to obtain a desired color scheme in less than 48 s. We also confirmed that the proposed method could provide users favorable recolored illustrations in less than 52 s. In addition, we confirmed that the search ability of the proposed method is superior to that of the conventional IEC method through a comparison experiment.
A Threshold Speed Computation Algorithm in Adaptive DVS Scheduling

Performance boosting of modern computing systems is constrained by the chip/circuit power dissipation. Dynamic voltage scaling (DVS) has been applied for reducing the energy consumption by dynamically changing the supply voltage. One can apply an adaptive scheme by computing a threshold speed of the supplied voltage, and adopting greedy online DVS scheduling algorithm when the voltage exceeds the threshold while choosing a conservative speed on the contrary. This paper presents an algorithm to determine the threshold speed. The proposed algorithm allows to obtaining the threshold speed for the adaptive DVS scheduling algorithm more efficiently.
A New Approach for Computing Semantic Relatedness with Wikipedia

Semantic relatedness measures are used in many applications in natural language processing and we propose a Wikipedia-based method to compute it. Unlike existed methods that only focus on a small section of Wikipedia (e.g. info box or hyperlinks), our method makes full use of the rich information contained in the Wikipedia page and could get a higher accuracy within reasonable time. In our method, we first use some special sections (e.g. synonyms and hyponyms) in the Wikipedia page to judge whether two concepts are closely related. If they are not, we then use pattern matching to find whether they are related through usual relatedness (e.g. ―a part of‖, ―result in‖, and ―is a member of ‖). And if the relatedness score hasn't been computed out through former steps, we then use a method which makes some improvement on the famous explicit semantic analysis method to compute the relatedness.
Development of a map matching method using the multiple hypothesis technique

This paper proposes a map matching method using the multiple hypothesis technique (MHT) to determine a road in probabilistic approach. The MHT is a method to track multiple targets under the clutter environment using a likelihood function. To realize a map matching method using the MHT, pseudo-measurements are generated utilizing adjacent roads of GPS position and the MHT is reformulated as a single target problem. Since pseudo-measurements are generated using digital maps, topological properties such as road connection, direction, and road facility information can be considered by calculating the probabilities of hypotheses. In order to reduce the degradation of the map matching performance by bias errors in the road data in digital maps, a Kalman filter is employed to estimate the bias. Field experimental results show that the proposed map matching method provides a consistent performance even in complex downtown areas, overpass/underpass areas, and in the areas that roads are adjacent in parallel.
Automatic C Code Generation for Avionics Software Based on VxWorks653 Platform

At present, model-driven development method has been gradually applied in safety-critical avionics software to improve reliability and productivity. Existing ARINC653 annex of the Architecture Analysis & Design Language (AADL) is used to model avionic software based on ARINC653-compatible OS, such as VxWorks653 commercial platform. In this paper, a refined C code generation algorithm is proposed to enable automatically generate VxWorks653-runnable code from the AADL ARINC653 models. Finally, a simplified autopilot system example is as a case study to show the validity of our approch.
A Parallel PDA Algorithm for Closely-Spaced Targets Tracking in Clutter

To reduce the computational complexity of JPDA and resolve closely-spaced targets efficiently, decompose JPDA into parallel PDA algorithms without regarding the correlation of targets. For a target, measurements are all clutter except the ones originated from itself. The PDA algorithm to track every single target with fixed covariance of states. When targets got closed within thick clutter, try to avoid coalescence and reduce complexity of association, maintaining the independence of targets through neglecting the assignment association model of measurement-to-track which used to happen once targets gates got overlapped. Simulations give arguments that parallel PDA has a better performance than JPDA in tracking closely-spaced targets.
Sensor fusion for complex articulated body tracking applied in rowing

This paper presents a sensor fusion model for integrating wearable inertial measures with sensors in the environment. This approach is designed and tested to support body motion tracking of rowing in indoor and outdoor environments. This paper presents the approach based on a complex kinematic model and Unscented Kalman filtering. The approach is validated in an indoor setup based on the SPRINT rowing system by comparison against results obtained from a commercial motion capture system, thus providing future directions for the assessment of rowers’ performance on an instrumented boat.
The quarter-state sequence (Q-sequence) to represent the floorplan and applications to layout optimization

A new data structure "Q-sequence" for representing a floorplan of n rooms is proposed. The Q-sequence is a concatenation of room names and two kinds of positional symbols, totally of length 3n. It is shown that encoding of a given floorplan and decoding to a floorplan are both possible in a linear time of n. An exact counting formula of distinct floorplans is given. Numerical estimation shows that the number is only slightly larger than that of a slicing structure, and far smaller than (n! )/sup 2/ which is the size of the packing solution space by the sequence-pair representation.
Continuous low-dose therapy with vinblastine and VEGF receptor-2 antibody induces sustained tumor regression without overt toxicity

Various conventional chemotherapeutic drugs can block angiogenesis or even kill activated, dividing endothelial cells. Such effects may contribute to the antitumor efficacy of chemotherapy in vivo and may delay or prevent the acquisition of drug-resistance by cancer cells. We have implemented a treatment regimen that augments the potential antivascular effects of chemotherapy, that is devoid of obvious toxic side effects, and that obstructs the development of drug resistance by tumor cells. Xenografts of 2 independent neuroblastoma cell lines were subjected to either continuous treatment with low doses of vinblastine, a monoclonal neutralizing antibody (DC101) targeting the flk-1/KDR (type 2) receptor for VEGF, or both agents together. The rationale for this combination was that any antivascular effects of the low-dose chemotherapy would be selectively enhanced in cells of newly formed vessels when survival signals mediated by VEGF are blocked. Both DC101 and low-dose vinblastine treatment individually resulted in significant but transient xenograft regression, diminished tumor vascularity, and direct inhibition of angiogenesis. Remarkably, the combination therapy resulted in full and sustained regressions of large established tumors, without an ensuing increase in host toxicity or any signs of acquired drug resistance during the course of treatment, which lasted for >6 months. This article may have been published online in advance of the print edition. The date of publication is available from the JCI website, http://www.jci. org. J. Clin. Invest. 105:R15–R24 (2000).
System dynamics and cybernetics: a synergetic pair

The authors advocate building a bridge between two systems approaches, namely system dynamics (SD) and the viable system model (VSM), which is the main exponent of organizational cybernetics (OC). Such a synthesis is aimed at opening a path towards a better capability of actors to deal with complex issues in both organizations and society. Given their respective strengths - modeling and simulation of content issues in the case of SD, and providing a viable organizational context in the case of OC - a combination of the two approaches is claimed to be potentially fertile. That argument gets twofold support. Firstly, the complementarity of SD and the VSM is cogently shown. Secondly, the authors refer to examples of synergy development through a combination of the two approaches.
An adaptive deterministic annealing approach for medical image segmentation

We present a stochastic model based technique that uses the concept of deterministic annealing to obtain a generalized solution to the nonconvex optimization problem encountered by many image segmentation techniques. Deterministic annealing [DA] is an elegant and useful tool for clustering and classification. This novel optimization approach works with the efficiency of a deterministic procedure and has been successfully applied to a number of combinatorial optimization problems. We demonstrate effective segmentation of simulated MR brain images and provide a quality measure for accuracy of classification. A generalized deterministic annealing procedure, which works tender a structural constraint of mass or density, has been utilized for this purpose. This method produces a hierarchy of solutions giving segmentation results from a coarse to a fine level. Automatic edge detection can be performed using these solutions that are at different degrees of coarseness. The procedure has been made more efficient by utilizing a new similarity parameter from the concepts of neuro-fuzzy clustering.
Design and portable device implementation of feature-based partial matching algorithms for personal spoken sentence retrieval

With the increasingly widespread use of personal portable devices, it is essential to devise an efficient method for spoken data retrieval for its resource-limited identity. This investigation proposes two efficient feature-based sentence-matching algorithms for speaker-dependent personal spoken sentence retrieval. Such a system can efficiently retrieve database sentences only partially matched to query sentence inputs. The query and database sentences are initially segmented into equal-sized matching units. A matching plane that comprises matching blocks is then created. For each matching block, a local similarity score is then determined from the feature distance. A whole-matching-plane-based accumulation scheme and a column-based row-based accumulation scheme are then designed to determine the global similarity score. The global similarity score of the matching plane reveals the similarity between the query and database sentences. The proposed algorithms are based on the feature-level comparison and do not require acoustical and language models. Experiments on news titles and personal schedules were conducted. The experimental results show that the proposed algorithms can efficiently work on both PC and HP iPAQ H5550 PDA.
Commentary: A Prospective Comparison Between Neutralizing the pH of 1% Lidocaine with Epinephrine (Buffering) and Pre‐Operative Skin Cooling in Reducing the Pain of Infiltration of Local Anesthetic

Dermatologic surgeons have long been trying to find ways to eliminate patient discomfort associated with dermatologic procedures. Although some dermatologic procedures, such as facial resurfacing and extensive procedures performed on children, require intravenous or general anesthesia, dermatologic surgical procedures usually require only local anesthesia, which is frequently administered via injection, to eliminate pain at the surgical site. The article by Mohammed Alshahwan, MD, titled “A Prospective Comparison Between Neutralizing the pH of 1% Lidocaine with Epinephrine (Buffering) and Preoperative Skin Cooling in Reducing the Pain of Infiltration of Local Anesthetic,” addresses the pain inherent in infusion of local anesthetic.
Production of Enzymes and Biotransformation of Orange Waste by Oyster Mushroom, Pleurotus pulmonarius (Fr.) Quél.

The wood-decay fungi are able to bioconvert a wide variety of lignocellulosic residues due to the secretion of extracellular enzymes. The use of agricultural wastes as substrate for mushroom cultivation or enzymes production can help to solve environmental problems caused by inadequate discharge in the nature. The production of hydrolytic and oxidative enzymes by Pleurotus pulmonarius developed in solid state system using orange waste as substrate was evaluated in this work. Among the hydrolytic enzymes, pectinase was the main enzyme produced by the fungus, presenting the highest enzymatic activity of 9.4 U/mL after 35 days of cultivation. Considering the oxidative enzymes, laccase was the main enzyme produced with maximal activity of 12.2 U/mL obtained after 20 days of cultivation. Low enzyme levels of manganese peroxidase, β-glucosidase and β-xy-losidase were detected with activity peaks at the end of the cultivation. The enzymatic levels of amylase, carboxymethyl cellulase and xylanase were similar and less than 1.5 U/mL. No aryl-alcohol oxidase activity was detected. NDF, ADF and cellulose values increased during 45 days of cultivation. There was no lignin degradation during the study period and the fungus culture in orange solid waste caused protein enrichment in the substrate. Our results demonstrate that P. pulmonarius was an efficient producer of two important industrial enzymes, pectinase and laccase in a cheap solid state system using orange waste as substrate.
A survey of security issues in Cognitive Radio Networks

In the last decade, cognitive radio (CR) has emerged as a major next generation wireless networking technology, which is the most promising candidate solution to solve the spectrum scarcity and improve the spectrum utilization. However, there exist enormous challenges for the open and random access environment of CRNs, where the unlicensed secondary users (SUs) can use the channels that are not currently used by the licensed primary users (PUs) via spectrum-sensing technology. Because of this access method, some malicious users may access the cognitive network arbitrarily and launch some special attacks, such as primary user emulation attack, falsifying data or denial of service attack, which will cause serious damage to the cognitive radio network. In addition to the specific security threats of cognitive network, CRNs also face up to the conventional security threats, such as eavesdropping, tampering, imitation, forgery, and noncooperation etc. Hence, Cognitive radio networks have much more risks than traditional wireless networks with its special network model. In this paper, we considered the security threats from passive and active attacks. Firstly, the PHY layer security is presented in the view of passive attacks, and it is a compelling idea of using the physical properties of the radio channel to help provide secure wireless communications. Moreover, malicious user detection is introduced in the view of active attacks by means of the signal detection techniques to decrease the interference and the probabilities of false alarm and missed detection. Finally, we discuss the general countermeasures of security threats in three phases. In particular, we discuss the far reaching effect of defensive strategy against attacks in CRNs.
Transmit Antenna Selection withPowerandRate Allocation forGeneralized Distributed Wireless Communication Systems

This paper studies downlink transmit antenna selection withpowerandrateallocation ingeneralized distributed wireless communication systems(G-DWCS). Basedon the large-scale fading statistics (pathlossandshadowfading) at thetransmitter, antenna selection criteria havebeenproposed for combined spacetimeblock code(STBC)andVertical Bell-Labs Layered Space Time(V-BLAST) structure, whereeachlayer of V-BLASTiscomposed ofco-located multiple antennas for independent STBCtransmission. Thesub-optimal antenna set, sub-optimal powerandrateallocation aredetermined tominimize anupperboundonthesymbol error rate(SER). Atthereceiver a fixed detection orderisfollowed whichisobtained meanwhile in theantenna selection process atthetransmitter. It's verified by MonteCarlosimulation thatourproposed antennaselection criteria canjudiciously select theoptimal antenna setandallocate proper powerandrate, andareverysuitable forG-DWCSsystem. IndexTerms-Antenna Selection, G-DWCS,Multiple Input Multiple Output(MIMO), PowerandRateAllocation, STBC, V-BLAST.
Microwave Radar Investigation of Coastal Ocean Wave Propagation

A groundbased, portable FMCW 3 GHz microwave radar operating at moderately shallow grazing angles, has been used to measure ocean wave orbital velocities from which ocean waveheight spectra are calculated. Measurement at a large number of contiguous range cells has allowed the study of the evolution of waves though shoaling regions, including wavefront steepening and eventual breaking. An initial comparison of wave height spectra with those obtained from an S4 buoy shows promising agreement. The spatio-temporal coverage of the radar has been exploited to obtain frequency versus wavenumber spectra for particular wave directions, giving the dispersion relation for water waves. These spectra have been obtained using both the backscattered power and the velocity information.
Documenting learning environments and experiences

At their best, ICTs can support knowledge construction, learning-by-doing, by conversing and by reflecting (Jonassen, 1999) but managing all this in a student-centred environment is a complex task that might be made more manageable by teachers sharing and re-using effective learning designs. Furthermore, if these designs were available in machinereadable format, educators would be able to select a learning design to suit their context “off the shelf” and plug-and-play it. A number of attempts are currently being made to comprehensively document learning designs that would allow educators to share successful, stimulating and engaging learning environments and experiences. IMS-LD, LAMS and the AUTC Learning Design Project are three developments where a comprehensive system is being produced that utilises a consistent data standard and vocabulary to describe the teaching and learning environment and the different theoretical approaches employed (Oliver & Littlejohn, 2006) and two of the three are machine-readable (INS-LD and LAMS). This paper provides a review of each of these methods of documenting learning designs and details the results of a study that demonstrated that a system that educators can use to comprehensively describe successful, stimulating and engaging learning designs so that they can be shared and re-used is still beyond the reach of the average pre-service teacher. However, all have features that illustrate that the dream of an easy-to-use, machinereadable and comprehensive learning design documentation system may not be too far away.