Miracle-dz/UniFAR-FTUs huggingface dataset:
Bistatic ultra-wideband SAR for imaging of ground targets under foliage

Bistatic SAR is compared with monostatic SAR concerning, e.g. coherent integration time and spatial resolution. We also suggest that bistatic SAR may be used to suppress background clutter, e.g. when the clutter scattering is dominated by dihedral or trihedral scattering mechanisms. This idea is applied to the problem of detecting concealed vehicles in foliage using VHF-band SAR. Electromagnetic simulations show that the vehicle-to-clutter ratio can dramatically increase by choosing different incidence angles for the transmitter and receiver in a bistatic SAR.
Color harmonization for Augmented Reality

In this paper we discuss color harmonization for Augmented Reality. Color harmonization is a technique used to adjust the combination of colors in order to follow aesthetic guidelines. We implemented a system which is able to harmonize the combination of the colors in video based AR systems. The presented approach is able to re-color virtual and real-world items, achieving overall more visually pleasant results. In order to allow preservation of certain colors in an AR composition, we furthermore introduce the concept of constraint color harmonization.
Distance Based Thresholds for Cluster Head Selection in Wireless Sensor Networks

Central to the cluster-based routing protocols is the cluster head (CH) selection procedure that allows even distribution of energy consumption among the sensors, and therefore prolonging the lifespan of a sensor network. We propose a distributed CH selection algorithm that takes into account the distances from sensors to a base station that optimally balances the energy consumption among the sensors. NS-2 simulations show that our proposed scheme outperforms existing algorithms in terms of the average node lifespan and the time to first node death.
A Comparison of Practical Information Measures

This report compares a variety of computable information measures for finite strings. These include Shannon’s n-block entropy, the three best known versions of the Lempel-Ziv production complexity (LZ-76, LZ-77, and LZ-78), and the lesser known T-entropy. We apply these measures to strings of known entropy, each derived from the logistic map. Pesin’s identity allows us to deduce corresponding Shannon entropies (Kolmogorov-Sinai entropies) for the sample strings, without resorting to probabilistic methods.
Modeling human aesthetic perception of visual textures

Texture is extensively used in areas such as product design and architecture to convey specific aesthetic information. Using the results of a psychological experiment, we model the relationship between computational texture features and aesthetic properties of visual textures. Contrary to previous approaches, we build a layered model, which provides insights into hierarchical relationships involved in human aesthetic texture perception. This model uses a set of intermediate judgements to link computational texture features with aesthetic texture properties. We pursue two different approaches for modeling. (1) Supervised machine-learning methods are used to generate linear and nonlinear models from the experimental data automatically. The quality of these models is discussed, mainly focusing on interpretability and accuracy. (2) We apply a psychological-based approach that models the processing pathways in human perception of naturalness, introducing judgement dimensions (principal components) mediating the relationship between texture features and naturalness judgements. This multiple mediator model serves as a verification of the machine-learning approach. We conclude with a comparison of these two approaches, highlighting the similarities and discrepancies in terms of identified relationships between computational texture features and aesthetic properties of visual textures.
Tetranectin and apolipoprotein A‐I in cerebrospinal fluid as potential biomarkers for Parkinson’s disease

Wang E‐S, Sun Y, Guo J‐G, Gao X, Hu J‐W, Zhou L, Hu J, Jiang C‐C. Tetranectin and apolipoprotein A‐I in cerebrospinal fluid as potential biomarkers for Parkinson’s disease. Acta Neurol Scand: 2010: 122: 350–359. © 2010 The Authors Journal compilation © 2010 Blackwell Munksgaard.
EOG signal detection for home appliances activation

Eye movement is the most common way for paralysis patients to communicate. Eye movement can be used by the paralysis patients and armless persons to perform simple tasks, for examples to activate a system in order to get attention or to switch home appliances on and off when they are alone. This study investigates the reliability of EOG signals for activating home appliances. A replica of a living room with a fixed location of the television and a switch was set up and the EOG signals were recorded when the subjects were sitting and standing at various positions. Various distances between the subject and the television and gaze angles were considered to obtain optimum EOG signals. An algorithm to detect the occurrence of the EOG signals was developed and its performance was examined. It was found that the proposed eye movement technique could produce clear EOG signals which are suitable for activating home appliances and the success percentage of the algorithm is 92%.
Economic Valuation of the Chinook Salmon Sport Fishery of the Gulkana River, Alaska, under Current and Alternate Management Plans

This paper extends the standard travel cost method (TCM) to develop estimates of the economic value of recreational chinook salmon fishing on the Gulkana River, Alaska, under existing and hypothetical fishery management conditions. Respondents were asked to state how the number of trips that they took to the study area would change if alternative fishery management practices were imposed. Three hypothetical management conditions were considered: a doubled 1992 sport fish harvest, a doubled daily bag limit, and a season bag limit of five. Each of the hypothetical fishery management conditions provides increased economic returns to anglers.
DTN based dominating set routing technique for mobile ad hoc networks

With the wide spread of user mobility and the existence of various types of wireless networks, effective inter-networking is mandatory in order to support user roaming while maintaining the connectivity. In our previous work [1], we propose a system architecture to achieve the connectivity over a heterogeneous wireless network, which employs the delay-tolerant network (DTN) concept to overcome the problem of potential intermittent connections caused by user roaming and ensures quality of service (QoS) in the presence of a long disconnection period. In this paper, we present a new routing technique for mobile ad hoc networks (MANETs) based on the DTN system architecture. We introduce the concept of virtual network topology and redefine the dominating-set based routing for the challenged network environment under consideration. In addition, we propose a time based methodology to predict the probability of future contacts between node pairs to construct the virtual network topology. Simulation results demonstrate the effectiveness of the proposed dominating-set based routing scheme under the DTN system architecture.
A Note on CVA and Wrong Way Risk

Hull and White approach to Wrong Way Risk in the computation of Credit Value Adjustment (CVA) is considered the most straightforward generalization of the standard Basel approach. The model is financially intuitive and it can be implemented by a slight modification of existing algorithms for CVA calculation. However, path dependency in the key quantities has non-elementary consequences in the calibration of model parameters. We propose a simple and fast approach for computing these quantities via a recursion formula. We show in detail the calibration methodology on market data and CVA computations in two relevant cases: a FX forward and an interest rate swap.
Detecting pedestrians and vehicles in traffic scene based on boosted HOG features and SVM

This paper presents a popular method called boosted hog features to detect pedestrians and vehicles in static images. We compared the differences and similarities of detecting pedestrians and vehicles, then we selected boosted hog features to get an satisfying result. In the part of detecting pedestrians, Histograms of Oriented Gradients (HOG) feature is applied as the basic feature due to its good performance in various kinds of background. On that basis, we create a new feature with boosting algorithm to obtain more accurate results. In the part of detecting vehicle, we select the shadow underneath vehicle as the feature, so we can utilize it to detect vehicles in daytime. The shadow is an important feature for vehicles in traffic scenes. The region under vehicle is usually darker than other objects or backgrounds and can be segmented by setting a threshold. Finally, experimental results show that the detection of pedestrians and vehicles using boosted hog feature and linear svm combines the advantages of hog feature and adaboost classifier, and can achieve better detection results than the detector using conditional HOG features. At the end, the paper shows its efficiency and effectiveness using to application in real situations.
Faint Radio Sources in the NOAO Boötes Field: VLBA Imaging and Optical Identifications

As a step toward investigating the parsec-scale properties of faint extragalactic radio sources, the Very Long Baseline Array (VLBA) was used at 5.0 GHz to obtain phase-referenced images of 76 sources in the NOAO Boötes field. These 76 sources were selected from the Faint Images of the Radio Sky at Twenty cm (FIRST) catalog to have peak flux densities above 10 mJy at 5″ resolution and deconvolved major diameters of less than 3″ at 1.4 GHz. Of these faint radio sources, 57 were identified with accretion-powered radio galaxies and quasars brighter than 25.5 mag in the optical I band. On Very Large Array (VLA) scales at 1.4 GHz, a measure of the compactness of the faint sources (the ratio of the peak flux density from FIRST to the integrated flux density from the NRAO VLA Sky Survey catalog) spans the full range of possibilities arising from source-resolution effects. Of the faint radio sources, 30, or 39%, were detected with the VLBA at 5.0 GHz with peak flux densities above 6 σ ∼ 2 mJy at 2 mas resolution. The VLBA detections occur through the full range of compactness ratios. The stronger VLBA detections can themselves serve as phase-reference calibrators, boding well for opening up much of the radio sky to VLBA imaging. For the adopted cosmology, the VLBA resolution corresponds to 17 pc or finer. Most VLBA detections are unresolved or slightly resolved, but one is diffuse and five show either double or core-jet structures; the properties of these latter six are discussed in detail. Three VLBA detections are unidentified and fainter than 25.5 mag in the optical I band; their properties are highlighted because they likely mark optically obscured active nuclei at high redshift.
Compensated Rotational-Invariant Fast Motion Tracking with Collateral Trajectory Guess

In this paper we introduce a method to track the motion of a fast moving objects, in a video with blurred background images being captured by a rotating camera. When tracking motion of a fast-moving object like a car, we need to find solutions basically for two issues. Firstly, to eliminate the rotational effect of the camera we need to find a method of matching two given consecutive frames in the sequence. Because of the fast rotation of the camera that follows the moving vehicles, the use of feature points (i.e. detection and matching) is of little value as we get blurred background (and possibly blurred foreground objects as well). Secondly, it is necessary to identify a fast-processing method either to develop a reference background for an indirect method, or to detect fast-moving objects in direct processing for motion tracking. Instead of applying blind search for whole image frames, we derive an Progressively Optimized Representative Scanning Window (PORSW) method for the sake of high efficiency. The method limits the region of interest, that is initially determined in a training phase and is progressively updated with our proposed progressive random walk algorithm. The initial window is obtained by applying an adaptive Lucas Kanade method to determine the direction of the movement of the pixels in each scan line, running towards the trailing end from the starting boundary. Unusual pixel behaviour, i.e. when pixels do not comply with expected direction and magnitude of the flow given by background pixels, is categorized as the motion of foreground pixels. Our evaluation shows that the estimation result is more stable even for significant angular error, as we propose to employ the variation in the flow vector of image data for the control functions at different image sequences.
LERD, a locality enhanced and resemblance based deduplication scheme for large data sets

As one kind of storage technology, deduplicaition is widely deployed in all kinds of storage systems. However, the key problems of duplication, such as data throughput and usage of RAM, have not been perfectly addressed. Especially, with the emergence of cloud storage, traditional deduplication methods are not able to adapt to the velocity characteristic of the large data sets. This paper proposes LERD, a temporal locality enhanced resemblance based Duplication scheme, aiming at rapidly querying duplicated data for large scale data sets. LERD takes advantage of data resemblance and temporal locality of data stream to narrow query range, which not only rise throughput, but also decline usage of RAM. Theoretical analysis and experimental results show that LERD's performance is much better than other state-of-the-art schemes.
The efficacy of performing shockwave lithotripsy before retrograde intrarenal surgery in the treatment of multiple or large (≥1.5 cm) nephrolithiasis: A propensity score matched analysis

Purpose To investigate the effect of performing shockwave lithotripsy (SWL) before retrograde intrarenal surgery (RIRS) on the treatment outcomes of patients with nephrolithiasis. Materials and Methods The data of 189 patients with renal stones who underwent RIRS from July 2007 to July 2014 was reviewed retrospectively. Patients with stones larger than 1.5 cm were recommended to undergo SWL before RIRS. Patients were divided into 2 groups based on whether the preoperative SWL was performed (group 1, n=68) or not (group 2, n=121). The cohorts of the 2 groups cohorts were matched 1:1 using propensity score analysis. Patient, stone characteristics, operative parameters, and stone-free rates were compared. Results Patients in groups 1 and 2 were matched with respect to stone size, number, and location, leaving 57 patients in each group. After matching, no differences were identified between the 2 groups regarding age, body mass index, sex, stone composition, density and multiplicity. Compared to group 2 patients, patients in group 1 had fewer number of procedures performed (1.10 vs. 1.26, p=0.045) and higher stone-free rate (89.4% vs.73.6%, p=0.039). In multivariate analysis, Non lower calyceal location (odd ratio [OR], 8.215; 95% confidence interval [CI], 1.782–21.982; p=0.041), stone size (OR, 6.932; 95% CI, 1.022–18.283; p<0.001), and preoperative SWL (OR, 2.210; 95% CI, 1.058–7.157; p=0.019) were independent factors predicting a stone-free state after RIRS. Conclusions Performing SWL before RIRS may favor stone eliminations during surgery and increase the stone-free rate in selected patients.
3D Space-Time Visualization of Player Behaviour in Pervasive Location-Based Games

Location-based games not only offer new experiences for the players, but also present new challenges for researchers in terms of analyzing player behaviour. Whilst many ethnographical studies have presented useful qualitative insights into this area, there is the potential to both improve support for these studies and to provide more effective representations of the quantitative data that can often be extracted from the game itself in a manner that enables greater understanding. In this paper, we illustrate how combined spatial and temporal information can be represented using the human geographers' technique of space-time paths to provide 3D visualizations of a player's or players' movement. Our analysis of a particular location-based game shows how a richer understanding of overall game play is obtained and highlights the possibilities for using the technique for a whole range of location-based services to provide a more complete view of complexities of journeys. Further, we discuss how these techniques can be utilized more generally by ethnographers who study the behaviour of mobile actors.
Cognitive radio network as wireless sensor network (I): Architecture, testbed, and experiment

This paper explores the vision of a dual-use sensing/communication system based on Cognitive Radio Network (CRN). The motivation of the paper is to push the convergence of sensing and communication systems into a unified cognitive network. The concept design of this sensing/communication system is presented along with potential functions and challenges. A through tree target detection using real data collected by CRN testbed is demonstrated. The CRN testbed will be built based on Rice WARP nodes. To further exploit the advantages of dynamic spectrum access and frequency diversity, multi-frequency signal, which is similar to OFDM signal, are employed to for detection experiment in the harsh radio environment. The experiment results illustrate the vision of employing a CRN as wireless sensor network.
A Survey on Location Based Routing Protocols in Mobile Ad-hoc Networks

Mobile Ad-hoc networks (MANET) is a collection of wireless mobile nodes forming a temporary network without using any centralized access point, infrastructure, or centralized administration. Till now wireless networking community designed hundreds of new routing protocols targeting the various scenarios of this design space. The paper present taxonomy of the mobile ad-hoc routing protocols and survey of location based routing protocols.
A Non-Transparent European Central Bank? Who is to Blame?

Transparency of central banks - defined here as the degree of genuine understanding of the monetary policy process and policy decisions by the public - has become a major issue. The authors use the term disclosure whenever we refer to the activities of a central bank to enhance the publics understanding of its policies. The European Central Bank (ECB) ranks high on our proposed central bank disclosure indicator.Nevertheless, there is quite some evidence suggesting that financial markets do not consider the ECB to be very transparent. The paper zooms in on two issues that may be relevant to understand this paradox: the monetary policy strategy of the ECB and the role of newspapers as intermediary between the central bank and the public. The authors conclude that the two-pillar strategy hinders transparency. Focusing on articles in the Financial Times and the Frankfurter Allgemeine Zeitung, the authors also find that newspaper reports on ECB policy decisions are sometimes biased.
Phase Coherent Detection of Steady-State Evoked Potentials: Experimental Results and Application to Brain-Computer Interfaces

Steady-state visual evoked potentials (SSVEP) have frequently been used in brain-computer interfaces (BCI). These BCIs commonly use non-coherent estimators for the discrimination of different visual stimuli. Here we present a novel phase coherent detection method for discrimination. This method utilizes information about the stimulus phase which leads to a significant reduction in classification error. In addition, using stimuli with identical reversal rate but different phases allow for a more flexible BCI system design. In this study, EEG-signals from two electrodes were recorded while subjects gazed at one out of two stimuli. These stimuli differed in reversal rate and/or relative phase shift. We compared the results obtained with the conventional non-coherent estimator with our phase coherent estimator in an offline analysis for different stimulus conditions. We found that including phase information into the analysis can reduce error probability by at least a factor of two. In addition we showed that stimuli of identical frequency that differed in phase, only, can reliably be discriminated. Similar low error probabilities as for stimuli that differed in phase and frequency were found
The collaborative leadership fieldbook : a guide for citizens and civic leaders

Foreword (John Parr). Preface. Acknowledgments. The Author. The Contributors. Introduction: The Power of Collaboration. PART ONE: META: THE IMPORTANCE OF COLLABORATION. 1. America s Civic Challenges. 2. Civil Society, Democracy, and Collaboration. 3. Building the Civic Community. PART TWO: MACRO: PREMISES AND PRINCIPLES OF SUCCESSFUL COLLABORATION. 4. Essential Concepts of Collaboration. 5. A Framework for Collaboration. PART THREE: MICRO: PRACTICES OF SUCCESSFUL COLLABORATION. 6. Getting Started. 7. Setting Up for Success. 8. Working Together. 9. Moving to Action. 10. Developing Networks of Responsibility. PART FOUR: STORIES AND EXAMPLES OF SUCCESSFUL COLLABORATION AND CIVIC LEADERSHIP DEVELOPMENT. 11. Joint Venture Silicon Valley (Christopher Wilson). 12. Transforming Civic Culture: Sitka, Alaska 1999 2001 (David D. Chrislip). 13. Neighborhood Action Initiative: Engaging Citizens in Real Change (William R. Potapchuk). 14. Equal Partners, Shared Vision: The Colorado Partnership for Educational Renewal (Carol A. Wilson). 15. Scenarios: Catalysts for Civic Change (David D. Chrislip, James Butcher, Adam Kahane). 16. Building Civic Leadership in Portland, Maine (Thomas J. Rice). 17. Building Leadership Capacity in a Socially Emerging Community (Allan Wallis). Appendix A: Learning from Research and Experience. Appendix B: Institute for Civic Leadership Curriculum and Agenda. References. Index.
Linked Data Driven Information Systems as an Enabler for Integrating Financial Data

With increased dependence on efficient use and inclusion of diverse corporate and Web based data sources for business information analysis, financial information providers will increasingly need agile information integration capabilities. Linked Data is a set of technologies and best practices that provide such a level of agility for information integration, access, and use. Current approaches struggle to cope with multiple data sources inclusion in near real-time, and have looked to Semantic Web technologies for assistance with infrastructure access, and dealing with multiple data formats and their vocabularies. This chapter discusses the challenges of financial data integration, provides the component architecture of Web enabled financial data integration and outlines the emergence of a financial ecosystem, based upon existing Web standards usage. Introductions to Semantic Web technologies are given, and the chapter supports this with insight and discussion gathered from multiple financial services use case implementations. Finally, best practice for integrating Web data based on the Linked Data principles and emergent areas are described.