Miracle-dz/UniFAR-FTUs huggingface dataset:
100 years of piezoelectric materials in acoustics: From a sonar to active metasurfaces

Since the discovery of the quartz ultrasound generator by Paul Langevin in 1917, piezoelectric materials have been successfully applied to many acoustic devices, which have greatly improved our lives. Nowadays, the piezoelectric transducers can employ a vast set of piezoelectric materials such as single crystals, ceramics, polymers, biopolymers, macro fiber composites, ferroelectrets, flexoelectric materials and some others. In this paper, a brief review of the use of piezoelectric materials in electroacoustic transducers will be given. Emphasis will be put on the modern applications of piezoelectric materials to the acoustics, especially on the method of active control of their elastic properties by means of active shunt circuits. The recent application of this method allowed the construction of so called active acoustic metamaterials (AAMM) and metasurfaces. The AAMMs based on the piezoelectric transducers offer the fabrication of efficient sound shielding structures with a low weight, a large area and .
Novel Three-Point Interpolation DFT Method for Frequency Measurement of Sine-Wave

This paper proposes a novel three-point interpolation discrete Fourier transform for accurate power system frequency measurement. The accurate formula of the proposed frequency measurement method is derived by using the maximum sidelobe decay windows. Moreover, the influence of white noise on the proposed frequency measurement is analyzed by deducing the expression of frequency measurement variance. The systematic errors and variances of frequency measurement are analyzed by simulation.
PeerWise Discovery and Negotiation of Faster Paths

Routing overlays have the potential to circumvent Internet pathologies to construct faster or more reliable paths. We suggest that overlay routing protocols have yet to become ubiquitous because they do not incorporate mechanisms for finding and negotiating with mutually advantageous peers: nodes in the overlay that can benefit equally from each other. We show that mutually advantageous peers exist in the Internet and that one-hop detour routing is sufficient for a latencyreducing overlay. We then simulate such an overlay construction process to show that it is efficient and scalable.
A neural network based on synchronized pairs of nano-oscillators

Artificial neural networks are intensively used to perform cognitive tasks such as image classification on traditional computers. With the end of CMOS scaling and increasing demand for efficient neural networks, alternative architectures implementing neural functions efficiently are being studied. This study leverages the demonstrated frequency tuning capabilities of compact nano-oscillators and their synchronization dynamics to implement a neuron using a pair of synchronized oscillators, and which features an unconventional response curve. We show that this compact neuron can naturally implement generic logic gates, including XOR. A simulated oscillator-based neural network is then shown to achieve results equivalent to standard approaches on two reference classification tasks. Finally, the performance of the system is evaluated in the presence of oscillator phase noise, an important issue of oscillating nanodevices. These results open the way for the design of alternative architectures adapted to efficient neural network execution.
The importance of pilot studies in the development of large-scale seawater desalination plants

Development of one or more large-scale seawater desalination plants in the State of Texas will provide a sustainable source of drinking water and represents a key component of alternative water resources planning for the future. Planning and implementation of a seawater desalination plant represents a significant infrastructure project and requires positive action in the areas of funding, environmental considerations, public involvement, design, permitting and others. A fundamental but vital method used to obtain the information that is needed in these areas is the execution of a field demonstration test of the desalination technology, known as a ‘pilot study’.
Intelligent Volume Visualization for Medical Datasets

For 3D medical data visualization, typically transfer functions (TFs) are employed to classify the data and to assign visual attributes to each material class. However, it is generally difficult to obtain a good transfer function. This paper presents a novel approach for exploring appropriate transfer functions by utilizing artificial intelligent (AI) techniques: the search for a transfer function is reformulated as a global optimization problem, which is subsequently solved by using the particle swarm optimizers (PSO). The initial population of transfer functions is pre-defined by users or selected randomly. The fitness value of each transfer function is defined by user on associated final rendering images or by user-defined objective functions. This approach bridges transfer functions and rendering images, and offers users an image that focuses on the part they interested in the medical datasets.
Prevalence and Risk Factors of Diabetic Nephropathy in an Urban South Indian Population

OBJECTIVE—The aim of this study was to determine the prevalence of diabetic nephropathy among urban Asian-Indian type 2 diabetic subjects. RESEARCH DESIGN AND METHODS—Type 2 diabetic subjects (n = 1,716), inclusive of known diabetic subjects (KD subjects) (1,363 of 1,529; response rate 89.1%) and randomly selected newly diagnosed diabetic subjects (NDD subjects) (n = 353) were selected from the Chennai Urban Rural Epidemiology Study (CURES). Microalbuminuria was estimated by immunoturbidometric assay and diagnosed if albumin excretion was between 30 and 299 μg/mg of creatinine, and overt nephropathy was diagnosed if albumin excretion was ≥300 μg/mg of creatinine in the presence of diabetic retinopathy, which was assessed by stereoscopic retinal color photography. RESULTS—The prevalence of overt nephropathy was 2.2% (95% CI 1.51–2.91). Microalbuminuria was present in 26.9% (24.8–28.9). Compared with the NDD subjects, KD subjects had greater prevalence rates of both microalbuminuria with retinopathy and overt nephropathy (8.4 vs. 1.4%, P < 0.001; and 2.6 vs. 0.8%, P = 0.043, respectively). Logistic regression analysis showed that A1C (odds ratio 1.325 [95% CI 1.256–1.399], P < 0.001), smoking (odds ratio 1.464, P = 0.011), duration of diabetes (1.023, P = 0.046), systolic blood pressure (1.020, P < 0.001), and diastolic blood pressure (1.016, P = 0.022) were associated with microalbuminuria. A1C (1.483, P < 0.0001), duration of diabetes (1.073, P = 0.003), and systolic blood pressure (1.031, P = 0.004) were associated with overt nephropathy. CONCLUSIONS—The results of the study suggest that in urban Asian Indians, the prevalence of overt nephropathy and microalbuminuria was 2.2 and 26.9%, respectively. Duration of diabetes, A1C, and systolic blood pressure were the common risk factors for overt nephropathy and microalbuminuria.
Analysis of pointers and structures

High-level languages could be optimized significantly if compilers could determine automatically how pointers and heap allocated structures are used. Setter knowledge of aliasing can improve classical optimizations applied to scalars (common sub-expression elimination, loop-invariant code motion, reduction in st.rength, constant propagation) by permitting less conservative assumptions about what is affected by an update to stor,age, and can aid in dependence analysis for purposes of parallelization. In addition, information about the shape and use of linked data structures can be used to apply storage overwriting and allocation optimizations (for instance, reusing storage instead of making a copy). This problem is a complex one, in part because it is possible to construct unbounded data structures that must necessarily be represented in some finite way. As with almost all program a:lalysis and optimization problems, one must limit the kinds of information one tries to collect, because exact information is generally undecidable or at least very difficult to compute. Our work follows that of Jones and Muchnick [Jbl81] who summarize the data structures allocated in a heap by making a graph, in which one node corresponds to possibly many nodes in the heap. The major issue is how to choose which heap cells to associate with which nodes. We view the program as a generator for data structures. Each symbolic execution of X +cons (A, X) adds a new node to the data structure. As the data structure grows, it must be compressed by making one node stand for many. We difler from other works principally in the kind of information we use to do the compression. Most work to date [Sch75a, Sch75b, JM81, Rug87, RM88, LH88, Lar89, HPR89] does this compression by bounding acyclic path length in the modeled data structures; this is known as k-bounded approximation. They limit the length of (acyclic) paths to k by truncating long paths with summary nodes containing all paths occurring in the original. The (path-length) k-b ounded approaches have several flaws: they are potentially very slow (unless k is very small), unbounded structures lose all structure beyond depth k, and information provided by the program structure is ignored.
An Ontology-Alignment Based Recommendation Mechanism for Improving the Acquisition and Implementation of Managerial Training Services in Project Oriented Organizations

The paper proposes a recommendation mechanism to enhance the managerial training in project-oriented organizations (POOs). The mechanism is presented within the framework of an innovative system used to provide support to POOs during the acquisition and implementation of training services. The recommender engine has, as inputs, the knowledge gaps of the employees given by an assessment system and the alignment in RDF/XML format between two ontological representations: one for the management documents provided by POOs and one for the training curriculum offered to the POOs. The recommender engine makes suggestions for adapting the training curriculum to the POOs' needs, by translating the ontology alignment result into a user-friendly form and by identifying web resources suitable to fill up the knowledge gaps. The outputs are smart recommendations meant to personalize the training curriculum to POOs and, thus, to increase the competitiveness of POOs.
Legacy system integration using a grammar-based transformation system

Enterprise information system management is the operation of different corporate databases, applications, and more and more often of integration and interoperability of legacy systems, acquired through mergers and acquisitions. These legacy systems produce structured or semistructured data that add to the vast amounts of data that a company generates every day. This data needs to be communicated between heterogeneous systems within the same company and eventually beyond the company's walls. Transformations of communicated data are required to enable companies to tightly integrate their systems into a cohesive infrastructure without changing their applications and systems. We present a transformation system that uses a grammar-based approach to provide direct integration of applications and systems at the data level. Sequences of transformations allow flexible and effective exchange of data between heterogeneous systems resulting in a single information network
Dissatisfaction in Child Welfare and Its Role in Predicting Self-Efficacy and Satisfaction at Work: A Mixed-Method Research

Child welfare organizations are increasingly concerned with challenges emerging from the assessment of social workers' dissatisfaction. This type of service represents the work area where social workers are at greater risk of burnout. Although several studies account for high social workers' burnout scores, they do not systematically dwell upon its sources and roots. In addition, scholars point out that a considerable number of work related issues may be perceived both as a source of dissatisfaction and satisfaction. We assume that there is a need to deepen the understanding of how dissatisfaction's sources may exert an impact on both personal job satisfaction and professional self-efficacy, which are positively associated with well-being at work. The present mixed-method research has two aims: (1) the extensive exploration, applying qualitative methodology, of the perceived sources of dissatisfaction; (2) the attempt to identify the extent to which those sources predict job satisfaction and professional self-efficacy. It is our purpose to further explore which differences emerge by age. The research involved child welfare workers, that is, SWs employed in public child welfare agencies in the North East of Italy. Results show the predominant role of interpersonal trust and mutual respect, as main predictors of both professional self-efficacy and job satisfaction. Practical implications of findings are discussed.
A comparison of friction in 28 mm conventional and 55 mm resurfacing metal-on-metal hip replacements

Abstract Total hip replacement has been a common, successful surgical intervention for many years. However, it has long been considered unsatisfactory for younger, more active patients due to the limited survivorship of conventional implants employing polyethylene. Larger resurfacing implants were developed to preserve bone stock and improve stability, however, early metal-on-polyethylene implants failed due to high wear. More recent developments, utilizing a metal-on-metal bearing, have encouraging short- to medium-term clinical performance. Concerns exist regarding the increased sliding distance and frictional torque generated within a larger diameter bearing. A large diameter metal-on-metal surface replacement was contrasted with a conventional 28 mm diameter implant with the same bearing material combination using a pendulum friction simulator. Studies were performed under different swing-phase load and lubrication conditions. The larger diameter bearing exhibited the lower friction factor under all test conditions, although the measured frictional torque was higher. Increasing swing-phase load was shown to cause an increase in friction factor in all tests. Increased serum concentration resulted in a reduction in friction factor for both bearings. Variation of the friction factor with the head diameter suggested that fluid-film lubrication contributed to the reduction of friction.
Privacy in pervasive computing environments - a contradiction in terms?

Technical progress in electronics allows the transformation of visions of pervasive computing into real world options. This perspective has raised deep concerns about the survival of privacy, as central building blocks of pervasive computing are in direct conflict with the fundaments of privacy protection. Considerable efforts have been undertaken to cope with these concerns with only limited success. While pertinent efforts have resulted in solutions for single aspects, they proved insufficient to eliminate the fears; on the contrary, they highlighted the principal incompatibility of privacy and pervasive information systems. Technical concepts alone, regardless how complex they are, cannot be sufficient; rather, a mix of privacy enhancing technologies, restrictions on the utilization of pervasive computing, and new regulations required to preserve some remnants of privacy.
A fast progressive lossless image compression method for space and satellite images

This paper presents a fast lossless image compression method for space and satellite images. The method, which we call HIREW, is based on hierarchical interpolating prediction and adaptive Golomb-Rice coding, and achieves 7-35 times faster compression than existing methods such as JPEG2000 and JPEG-LS, at similar compression ratios. Additionally, unlike JPEG-LS, it supports additional features such as progressive decompression using resolution scaling. An implementation of this codec will be used in the Japan Aerospace Exploration Agency (JAXA)'s Venus Climate Orbiter mission (PLANET-C).
Assessment of the subglottic region by ultrasonography for estimation of appropriate size endotracheal tube: A clinical prospective study

Background: Endotracheal intubation is important to carry out various surgical procedures. The estimation of endotracheal tube size is governed by narrowest diameter of the upper airway. The objective of the study was to assess the narrowest tracheal diameter by ultrasound for selection of the appropriate size endotracheal tube. Materials and Methods: After the approval of institution ethical committee and written informed consent, 112 patients aged 3 to 18 years of both genders with normal airways, scheduled for surgery under general anesthesia and intubation, were enrolled for this prospective clinical observational study. Preanesthetic ultrasonography of the subglottic region was performed by experienced ultrasonologist with a high-resolution linear array transducer in sniffing position for every patient and the subglottic tracheal diameter was estimated to select the appropriate-size endotracheal tube. The endotracheal tube, calculated on the basis of physical indices and by ultrasound, was statistically correlated with the appropriate size endotracheal tube used clinically for intubation. Results: The ultrasound guided selection criterion has estimated the appropriate-sized endotracheal tube better than physical indices (age or height)-based formulas. The estimated endotracheal tube size by ultrasound was significantly correlated with the clinically used endotracheal tube. Conclusion: Ultrasonography may be used for the assessment of the subglottic diameter of trachea in children to estimate the appropriate size endotracheal tube for intubation.
Robust video fingerprints based on subspace embedding

We present a novel video fingerprinting method based on subspace embedding. The proposed method is particularly robust against frame-rate conversion attacks and geometric attacks among other attacks including compression and spatial scaling. Using a sliding window, we extract fingerprints from a group of subsequent video frames. For the generation of the fingerprints, we first calculate the basis vectors of a coarse representation of this group of frames using a singular value decomposition (SVD). Then, we project the coarse representation of the video frames onto a subset of the basis vectors. Thus, we obtain a subspace representation of the input video frames. Finally, we extract the fingerprint bits by projecting a temporal average of these representations onto pseudorandom basis vectors. Since the subspace is estimated from the input video data itself, any global attack on video such as rotation would result in a corresponding change in estimated basis vectors thereby preserving the subspace representation. We present experimental results on 250 hrs of video to show the robustness and sensitivity of the proposed signature extraction method.
Detection of Nocturnal Epileptic Seizures from Wireless Inertial Measurements and Muscular Activity

The goal of this paper is to provide a lightweight approach for the early detection of epileptic seizures using data from inertial measurement unit and muscular activity. The detection procedure runs in a portable data collection device and raises an alarm for family member or other persons in the vicinity for fast assistance and eventually for saving the life of the monitored patient. The instantaneous power of sliding window is derived for inertial measurements from 3D Accelerometer (ACM), 3D Gyroscope (Gyro) and for the muscular activity from the ElectroMyoGram (EMG). The residual between forecasted and measured power is used as input for the detection algorithm based on Shewhart control chart. When the error between forecasted and derived power exceeds statistical chart limits [lower, upper] for several consecutive slots, an alarm is raised. The proposed approach is intended to improve the performance of existing detection systems by increasing the detection accuracy and reducing the false alarms through correlation analysis of collected data from 3D ACM, 3D Gyro and EMG. Our experimental results on real data set collected in Necker hospital from epileptic patients show that our proposed approach is robust against nocturnal movements and achieves a high level of detection accuracy with low false alarm rate.
Indoor WLAN localization using high-dimensional manifold alignment with limited calibration load

With the rapid development of Wireless Local Area Network (WLAN) technique, the indoor WLAN localization has caught significant attention. In this paper, a novel indoor WLAN localization approach by using the high-dimensional manifold alignment with limited calibration load is proposed. Different from the conventional dimension-reduction based manifold alignment approach which preserves a limited part of the Received Signal Strength (RSS) data information, we first construct an innovative objective function from the augmented physical locations and the corresponding RSS data. Second, the closed-form solution to the objective function is obtained by applying the Lagrange multiplier approach. Finally, the target location is estimated at the closest point in the manifold. Furthermore, we present some preliminary analysis towards the generalization of the proposed objective function to the scenario with multiple types of measurements used for the localization. The extensive analytical and experimental results demonstrate that the performance of the proposed approach is well with limited calibration load and can be further improved by using more calibrated locations with known RSS data.
Compact Modeling of Gate Capacitance in III–V Channel Quadruple-Gate FETs

In this paper, we present a compact model for charge density and gate capacitance for low effective mass channel material based quadruple-gate FETs (QGFETs). The proposed model accounts for the effect of quantum capacitance and conduction band non-parabolicity, which are important in FETs comprised of the low effective mass channel material. In modeling of QGFET, we propose and use a new form of Fermi–Dirac integral of order $-$ 1/2, which matches closely with the numerical data. Our model for the charge density and gate capacitance is compared with three-dimensional technology computer aided design (TCAD) simulations data, and shows excellent match. The proposed explicit compact model can be easily employed in efficient exploration of circuits based on the low effective mass QGFET nanowires.
Inter-level and intra-level deconvolution based image deblurring algorithm for wide field microscopy

This paper proposes an inter-level and intra-level deconvolution based image deblurring algorithm (ILILD) for microscopic images. Pyramid structure is used, and inter-level deconvolution is applied to estimate latent image from coarse level to fine level. The inter-level algorithm is based on total variation regularized Richardson-Lucy scheme, which can estimate latent image with artifacts suppressed. After inter-level deconvolution, intra-level deconvolution is applied. In each pyramid level of image, the residual deconvolution is done as the intra-level deconvolution scheme to recover image edges and details furtherly. Experiments show that ILILD algorithm can estimate latent images in less time and the results have better peak signal to noise ratio, higher image entropies and few artifacts.