Miracle-dz/UniFAR-FTUs huggingface dataset:
Polarimetric Analysis of Radar Signature of a Manmade Structure

Identification of manmade structures from radar images has always been a difficult task, especially for single-polarization radar. Fully polarimetric radar, however, can provide detailed information on scattering mechanisms that could enable the target or the structure to be identified. Complexity remains stemming from overlaps of single-bounce scattering, double-bounce scattering, and triple- and higher order bounce scattering from various components of a manmade structure, which makes physical interpretation a challenge. In this letter, an interesting example using polarimetric synthetic aperture radar (PolSAR) data of the Great Belt Bridge, Denmark, was presented to illustrate the capability of PolSAR in analyzing radar signatures. Polarimetric target decomposition is used to differentiate the multiple-bounce scatterings contained in the PolSAR images. Two C-band Danish EMISAR data takes, with the first obtained during the bridge's construction and the second after its completion, are used to extract the scattering characteristics of the bridge deck, bridge cables, and supporting structures
Reasons for use and non-use of dental services among people visiting a dental college hospital in India: A descriptive cross-sectional study

OBJECTIVE To find out the reasons for use and non-use of dental services among people visiting a dental college hospital in India. METHODS A descriptive cross-sectional study was carried out on 180 people, aged 15-65 years visiting the outpatient department of a dental college hospital in India. A self-administered questionnaire was used to collect data about the history of dental visits and reasons for use and non-use of dental services. RESULTS For a majority of the people (38.5%), time since the last dental visit was more than 2 years, and the main reason for visiting a dentist was dental pain (35.3%). Majority of the people had undergone extraction of teeth in their previous dental visit (44.3%). The major reason cited for not visiting a dentist was the presence of dental problem that was not severe enough to go to a dentist (43.1%). CONCLUSION Majority of the people were "problem-oriented visitors" rather than "prevention oriented visitors. "
Ovarian Follicular Fluid Constituents in Relation to Stage of Estrus Cycle and Size of the Follicle in Buffalo

The goal of the present study was to evaluate the difference in constituent of the ovarian follicular fluid in different stages of the estrus cycle and in medium and large sized follicle and also to evaluate the relation between serum and follicular fluid constituents in cyclic buffalos. A total of 34 clinically healthy buffalo (Bubals bubals), aged 7-10 years, were sent for slaughter in Moesha Abattoir, Assiut province in winter 2009. Blood samples and the whole genital tract of each animal were collected. The stage of the cycle (proestrus n= 8, estrus n= 7, metestrus n= 7 and diestrus n= 12) was determined post mortem. Biochemical analysis of serum and follicular fluid was performed through measuring total protein, albumin, chloride, potassium, phosphorus, magnesium, glucose, cholesterol, triglyceride, urea, creatinine levels and lactate dehydrogenase (LDH) activity. Results of the present study revealed that during the estrus cycle, only follicular triglyceride, urea, creatinine and phosphorus level showed significant changes. A positive correlation was found between follicular albumin, phosphorus levels and follicular diameter. Total protein, albumin, globulins, glucose, chloride and creatinine were significantly higher in the serum than that in the follicular fluid. Follicular triglyceride level and potassium level were significantly higher than serum level. Follicular LDH activity was higher in large sized follicle than small sized one. Further studies are required to elucidate the relation between concentration of urea and creatinine in the follicular fluid and oocyte viability.
Differential identifiability

A key challenge in privacy-preserving data mining is ensuring that a data mining result does not inherently violate privacy. ε-Differential Privacy appears to provide a solution to this problem. However, there are no clear guidelines on how to set ε to satisfy a privacy policy. We give an alternate formulation, Differential Identifiability, parameterized by the probability of individual identification. This provides the strong privacy guarantees of differential privacy, while letting policy makers set parameters based on the established privacy concept of individual identifiability.
Unknown Quantum States: The Quantum de Finetti Representation

We present an elementary proof of the quantum de Finetti representation theorem, a quantum analog of de Finetti’s classical theorem on exchangeable probability assignments. This contrasts with the original proof of Hudson and Moody [Z. Wahrschein. verw. Geb. 33, 343 (1976)], which relies on advanced mathematics and does not share the same potential for generalization. The classical de Finetti theorem provides an operational definition of the concept of an unknown probability in Bayesian probability theory, where probabilities are taken to be degrees of belief instead of objective states of nature. The quantum de Finetti theorem, in a closely analogous fashion, deals with exchangeable density-operator assignments and provides an operational definition of the concept of an “unknown quantum state” in quantum-state tomography. This result is especially important for information-based interpretations of quantum mechanics, where quantum states, like probabilities, are taken to be states of knowledge rather than.
Spectrum sensing in wideband OFDM based Cognitive Radio

Cognitive Radio is a novel technology in today's radio environment to improve the utilization efficiency of radio spectrum. In this paper we are going to use Orthogonal Frequency Division Multiplexing (OFDM) based spectrum sensing cognitive radio system is addressed. The main purpose is to identify the underutilized spectrum or white space without inferring the PU signal, called Existing Users (EUs) system altogether. To use the unused spectrum, spectrum sensing is needed to know whether the PU is present or not. The performance of cooperation based spectrum sensing scheme will be studied for OFDM based cognitive user using the energy detector method and wavelet based spectrum sensing scheme. Several factors like fading and shadowing affects the ability of cognitive radio to detect the PU. Here AWGN as well as Rayleigh fading channel are considered. Wavelet edge detection is one of the most widely used spectrum sensing techniques. This technique observes a spatial distribution of spectral data at multiple resolutions. The slope of the power spectral density is used as an index to differentiate between sharp and blurred peaks. Power spectra with conspicuous peaks utilize Haar wavelet transform, while for subtle peaks use Gaussian wavelet transform, and also explain how wavelet transform is advantageous then Energy detection.
Updates in the AquaLogic Data Services Platform

The BEA AquaLogic Data Services Platform (ALDSP) is a middleware platform for creating services that integrate and manipulate information from disparate enterprise data sources. This paper provides a technical overview of the all-new update support in ALDSP 3.0, released in January 2008. It describes the update side of data services, our unique model for making update automation transparent and flexible, and the use of the XQuery Scripting Extension (XQSE) for further customizing the system's default handling of updates. It also gives an overview of the ALDSP update processing machinery, including the automatic generation of update maps from read functions, translation of update maps into Update Virtual Machine (UVM) programs, the UVM instruction interpreter, and SQL generation for updates to data drawn from relational data sources.
Identifying the Dominant Language of Web Page Using Supervised N-grams

Natural language processing is an emerging technology in linguistic industry and an aid to human-computer interaction in computer science. Language identification, on the other hand, is a form of pattern recognition that helps to identify predefined language of a web page and to predict the unknown language of one particular text. Written texts are constructed by common features such as character, word and n-gram and these characteristics are unique among languages. From the experiment result, the performance of the supervised n-gram produces an accurate identification value and outperforms the distance measurement on Arabic script web pages.
A fast, efficient and scalable algorithm for perceptual high quality speech coding

In this paper an adaptive variable degree-k zero-tree (AVDZ) algorithm is proposed for re-encoding of perceptually quantized wavelet packet transform coefficients of high quality wideband speech. Its performance is compared with two well-known schemes comprising: 1- Embedded Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees (SPIHT). This comparison is carried out using the speech modified versions of these schemes. It is shown that the proposed AVDZ algorithm outperforms these methods by about 6–10% in coding efficiency and respectively 50% and 35% (on average) in total computation times.
On supervised mining of dynamic content‐based networks 1

In recent years, a large amount of information has become available online in the form of web documents, social networks, or blogs. Such networks are large, heterogeneous, and often contain a huge number of links. This linkage structure encodes rich structural information about the topical behavior of the network. Such networks are often dynamic and evolve rapidly over time. Much of the work in the literature has focused on classification either with purely text behavior or with purely linkage behavior. Furthermore, the work in the literature is mostly designed for static networks. However, a given network may be quite diverse, and the use of either content or structure could be more or less effective in different parts of the network. In this paper, we examine the problem of node classification in dynamic information networks with both text content and links. Our techniques use a random walk approach in conjunction with the content of the network to facilitate an effective classification process. Our approach is dynamic, and can be applied to networks which are updated incrementally. Our results suggest that an approach based on both content and links is extremely robust and effective. We also present methods to perform supervised keyword‐based clustering of nodes using this approach. We present experimental results illustrating the effectiveness and efficiency of our classification approach. We also show that the approach is able to find effective and coherent clusters. © 2012 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 5: 16–34, 2012
Relationship between structural changes and hyperpolarized gas magnetic resonance imaging in chronic obstructive pulmonary disease using computational simulations with realistic alveolar geometry

Both the development of accurate models of lung function and their quantitative validation can be significantly enhanced by the use of functional imaging techniques. The advent of hyperpolarized noble gas magnetic resonance imaging (MRI) technology has increased the amount of local, functional information we can obtain from the lung. In particular, application of 3He to measure apparent diffusion coefficients has enabled some measure of lung microstructure and airspace size within the lung. Models mimicking image acquisition in hyperpolarized gas MRI can improve understanding of the relationship between image findings and lung structure, and can be used to improve the definition of imaging protocols. In this paper, we review the state of the art in hyperpolarized gas MRI modelling. We also present our own results, obtained using a Monte Carlo approach and a realistic alveolar sac geometry, which has previously been applied in functional lung studies. In this way, we demonstrate the potential for models combining lung function and image acquisition, which could provide valuable tools in both basic studies and clinical practice.
A Lightweight Protocol Analysis and Modification for Secure RFID System

A radio frequency identification (RFID) is an important part in mobile and ubiquitous domain, and brings enormous productivity benefits in applications where objects require automatic identification. However, this pervasive use of RFID tags opens up the possibility of various attacks that violate user privacy and authentication. Security mechanisms for RFID systems are therefore of the utmost important. In this paper, the RFID security protocols (HB++[first] and HB++[second]) presented in Bringer et al. are shown to be vulnerable to active attacks and a modified solution is presented. Some of the security violations that may occur and possible remedies that were provided in the literature are discussed. Finally, the modifications to HB++, a recent variant of HB is proposed.
Design and Implementation of an Improved Carry Increment Adder

A complex digital circuit comprises of adder as a basic unit. The performance of the circuit depends on the design of this basic adder unit. The speed of operation of a circuit is one of the important performance criteria of many digital circuits which ultimately depends on the delay of the basic adder unit. Many research works have been devoted in improving the delay of the adder circuit. In this paper we have proposed an improved carry increment adder (CIA) that improves the delay performance of the circuit. The improvement is achieved by incorporating carry look adder (CLA) in the design of CIA contrary to the previous design of CIA that employs ripple carry adder (RCA). A simulation study is carried out for comparative analysis. The coding is done in Verilog hardware description language (HDL) and the simulation is carried out in Xilinx ISE 13.1 environment.
Dynamic management of TurboMode in modern multi-core chips

Dynamic overclocking of CPUs, or TurboMode, is a feature recently introduced on all x86 multi-core chips. It leverages thermal and power headroom from idle execution resources to overclock active cores to increase performance. TurboMode can accelerate CPU-bound applications at the cost of additional power consumption. Nevertheless, naive use of TurboMode can significantly increase power consumption without increasing performance. Thus far, there is no strategy for managing TurboMode to optimize its use across all workloads and efficiency metrics. This paper analyzes the impact of TurboMode on a wide range of efficiency metrics (performance, power, cost, and combined metrics such as QPS/W and ED2) for representative server workloads on various hardware configurations. We determine that TurboMode is generally beneficial for performance (up to +24%), cost efficiency (QPS/$ up to +8%), energy-delay product (ED, up to +47%), and energy-delay-squared product (ED2, up to +68%). However, TurboMode is inefficient for workloads that exhibit interference for shared resources. We use this information to build and validate a model that predicts the optimal TurboMode setting for each efficiency metric. We then implement autoturbo, a background daemon that dynamically manages TurboMode in real time without any hardware changes. We demonstrate that autoturbo improves QPS/$, ED, and ED2 by 8%, 47%, and 68% respectively over not using TurboMode. At the same time, autoturbo virtually eliminates all the large drops in those same metrics (-12%, -25%, -25% for QPS/$, ED, and ED2) that occur when TurboMode is used naively (always on).
Multi-Resource Parallel Query Scheduling and Optimization

Scheduling query execution plans is a particularly complex problem in shared-nothing parallel systems, where each site consists of a collection of local time-shared (e.g., CPU(s) or disk(s)) and space-shared (e.g., memory) resources and communicates with remote sites by message-passing. Earlier work on parallel query scheduling employs either (a) one-dimensional models of parallel task scheduling, effectively ignoring the potential benefits of resource sharing, or (b) models of globally accessible resource units, which are appropriate only for shared-memory architectures, since they cannot capture the affinity of system resources to sites. In this paper, we develop a general approach capturing the full complexity of scheduling distributed, multi-dimensional resource units for all forms of parallelism within and across queries and operators. We present a level-based list scheduling heuristic algorithm for independent query tasks (i.e., physical operator pipelines) that is provably near-optimal for given degrees of partitioned parallelism (with a worst-case performance ratio that depends on the number of time-shared and space-shared resources per site and the granularity of the clones). We also propose extensions to handle blocking constraints in logical operator (e.g., hash-join) pipelines and bushy query plans as well as on-line task arrivals (e.g., in a dynamic or multi-query execution environment). Experiments with our scheduling algorithms implemented on top of a detailed simulation model verify their effectiveness compared to existing approaches in a realistic setting. Based on our analytical and experimental results, we revisit the open problem of designing efficient cost models for parallel query optimization and propose a solution that captures all the important parameters of parallel execution.
Guideline for determination of link length of a 3 DOF planar manipulator for human-robot collision safety

In recent years, collision safety between a human and a robot has been increasingly important along with the spread of service robots. Much research has been conducted on how to design a safe manipulator, but it is not applicable to real manipulators yet. To deal with this problem, we propose a guideline to design a safe manipulator, which is composed of two phases, the safety evaluation and design parameter adjustment. To evaluate collision safety, we adopt the effective mass and manipulability and simplify the spatial collision between a human and a multi-DOF manipulator. Moreover, the experimental results from the biomechanical literature are employed for more realistic evaluation of collision safety. The design parameters and proper adjustment strategy can be established based on the safety evaluation results, and the design parameters of a manipulator can be modified to satisfy the collision safety and design requirement. The proposed guideline is implemented in the design of a 3 DOF safe manipulator, and it is shown that this guideline can be used to design a multi-DOF safe manipulator.
A compact LTCC-based Ku-band transmitter module

Presents design, implementation, and measurement of a three-dimensional (3-D)-deployed RF front-end system-on-package (SOP) in a standard multi-layer low temperature co-fired ceramic (LTCC) technology. A compact 14 GHz GaAs MESFET-based transmitter module integrated with an embedded bandpass filter was built on LTCC 951AT tapes. The up-converter MMIC integrated with a voltage controlled oscillator (VCO) exhibits a measured up-conversion gain of 15 dB and an IIP3 of 15 dBm, while the power amplifier (PA) MMIC shows a measured gain of 31 dB and a 1-dB compression output power of 26 dBm at 14 GHz. Both MMICs were integrated on a compact LTCC module where an embedded front-end band pass filter (BPF) with a measured insertion loss of 3 dB at 14.25 GHz was integrated. The transmitter module is compact in size (400 /spl times/ 310 /spl times/ 35.2 mil/sup 3/), however it demonstrated an overall up-conversion gain of 41 dB, and available data rate of 32 Mbps with adjacent channel power ratio (ACPR) of 42 dB. These results suggest the feasibility of building highly SOP integrated RF front ends for microwave and millimeter wave applications.
AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE

Patient wait time and access to care have long been a recognized problem in modern outpatient healthcare delivery systems. Despite all the efforts to develop appointment rules and policies, the problem of long patient waits persists. Regardless of the reasons, the fact remains that there are few implemented models for effective scheduling that consider patient wait times, physician idle time, overtime, ancillary service time, as well as individual no-show rate, and are generalized sufficiently to accommodate a variety of outpatient clinic settings. The goal of this research is to improve the quality and efficiency of healthcare delivery by developing a patient scheduling system that meets the clinical policies without overbooking while using an innovative „wait ratio‟ concept, a patient arrival schedule from the physician schedule accounting for ancillary services, an evidence-based predictive model of no-show probability for individual patient, and a model-supported dynamic overbooking policy to reduce the negative impact of no-shows. This research provides a step-bystep method for implementation of a scheduling model in outpatient clinics. Consequently, this research will improve the outpatient experience for both patients and medical providers, increase patient access to care, and ultimately enhance the quality of care.
Immunohistological Changes in Dilated Cardiomyopathy Induced by Immunoadsorption Therapy and Subsequent Immunoglobulin Substitution

Background—Immunoadsorption (IA) and subsequent immunoglobulin (Ig) G substitution represent an additional therapeutic approach in dilated cardiomyopathy (DCM). It remains to be elucidated whether this treatment modulates myocardial inflammation, which is possibly a causal factor of ventricular dysfunction. Methods and Results—From 25 DCM patients (EF <30%), 12 patients were randomized for IA therapy and subsequent IgG substitution at 1-month intervals until month 3. Before (<7 days) and after IA therapy, right ventricular biopsies were obtained from all patients. Biopsies were also obtained at intervals of 3 months from 13 patients without IA/IgG treatment (controls). IA/IgG treatment induced improvement in left ventricular ejection fraction from 21.3±1.7% (±SEM) to 27.0±1.3% (P <0.01 versus baseline/controls) and reduction of the &bgr;-receptor autoantibody serum levels (P <0.01 versus baseline/controls). The number of CD3 cells decreased from 5.7±0.8 to 2.9±0.5 cells/mm2 (P <0.01 versus baseline/controls). This decline was paralleled by a decrease in CD4 (P <0.01 versus baseline/controls) and CD8 (P <0.05 versus baseline/controls) lymphocytes. The number of leukocyte common antigen–positive cells (leukocytes) was reduced from 20.0±3.2 to 9.9±2.8 cells/mm2 (P <0.01 versus baseline/ P <0.05 versus controls). HLA class II expression decreased from 2.1±0.7% to 1.1±0.4% (P <0.05 versus controls/baseline). The number of immunopositive cells and the expression of HLA class II in controls remained stable. In both groups, the degree of fibrosis remained unchanged. Conclusions—IA and subsequent IgG substitution mitigate myocardial inflammation in DCM.
Automatic speaker recognition using a unique personal feature vector and Gaussian Mixture Models

This article presents an automatic speaker recognition system implemented in Matlab, which uses a unique feature vector, the so-called “Voice Print” (VP), to describe the voice. The system uses Gaussian Mixtures Models (GMM) in the classification process. The final part of the paper presents research on the efficiency of speaker recognition for different variants of the system, as well as the results of optimisation of the system.