Miracle-dz/UniFAR-FTUs huggingface dataset:
Bitrate and Tandem Detection for the AMR-WB Codec with Application to Network Testing

In network testing, identifying the cause for an observed speech quality degradation is of special interest. Common speech codec related causes to be identified are the application of a low bitrate or the occurrence of transcoding or self-tandem. This paper presents two comprehensible types of signal features which enable a speech-quality-motivated bitrate detection for the AMR-WB codec. The first type of feature is based on codec linearity, while the second type exploits the different structure of the fixed codebook at each bitrate. With these underlying features, the bitrate detection is performed with high accuracy. Since the one feature gathers information on the last applied bitrate and the other on coding effects accumulated during the entire transmission, this paper, additionally, provides a method to extract information on the occurrence of self-tandem in the network-under-test.
Femtosecond Pulsed Laser for Advanced Photonic Packaging

The purpose of the advanced applications of glass laser micromachining presented in this paper is to solve the difficulty of both electrical and optical interconnects needed in electro-optical packaging. Glass interposers constitute an innovative approach to integrate different types of functionalities onto the same functionalized substrate. The distinctive interest of this packaging approach is to integrate both the electronic and photonic chips and to implement a passive alignment strategy of the external fiber by butt coupling and of the photonic chip using a conventional flip-chip technique with state-of-the-art registration accuracy in the micron range. Multiplexer/demultiplexer, Y junction, directional couplers, micro-channels and waveguide can also be fabricated in glass using laser photo-inscription. This technique is based on nonlinear absorption under exposition to a focused laser beam that results in permanent structural glass modifications. In this paper, we report on femtosecond laser direct inscription in glass caused by local densification. Two main properties of densified glass are exploited, namely, i) the increase of the index of refraction suitable to fabricate optical waveguides and ii) the dramatic increase of the etching rate in hydrofluoric acid (HF) suitable for structuring integrated mirrors. Here, we demonstrate the fabrication of a photonic mirror in a glass interposer for redirecting light from a buried waveguide. A slanted trench was fabricated by laser inscription and a HF etching step was performed to obtain the appropriate angle and depth of the mirror. SEM pictures show the mirror uniformity and the proof of 90° beam redirection from a buried waveguide. Optical waveguides were also structured by direct laser inscription using a 0.5 NA microscope objective to focus the laser beam in the bulk of a glass substrate (SCHOTT AF32). The resulting waveguides exhibit single mode operation and losses of 4. 35dB for a length of 2.5 cm including the coupling losses.
Cluster-Based Learning from Weakly Labeled Bags in Digital Pathology

To alleviate the burden of gathering detailed expert annotations when training deep neural networks, we propose a weakly supervised learning approach to recognize metastases in microscopic images of breast lymph nodes. We describe an alternative training loss which clusters weakly labeled bags in latent space to inform relevance of patch-instances during training of a convolutional neural network. We evaluate our method on the Camelyon dataset which contains high-resolution digital slides of breast lymph nodes, where labels are provided at the image-level and only subsets of patches are made available during training.
Speech Enhancement Using Kalman Filtering in the Logarithmic Bark Power Spectral Domain

We present a phase-sensitive speech enhancement algorithm based on a Kalman filter estimator that tracks speech and noise in the logarithmic Bark power spectral domain. With modulation-domain Kalman filtering, the algorithm tracks the speech spectral log-power using perceptually-motivated Bark bands. By combining STFT bins into Bark bands, the number of frequency components is reduced. The Kalman filter prediction step separately models the inter-frame relations of the speech and noise spectral log-powers and the Kalman filter update step models the nonlinear relations between the speech and noise spectral log-powers using the phase factor in Bark bands, which follows a sub-Gaussian distribution. The posterior mean of the speech spectral log-power is used to create an enhanced speech spectrum for signal reconstruction. The algorithm is evaluated in terms of speech quality and computational complexity with different algorithm configurations compared on various noise types. The algorithm implemented in Bark bands is compared to algorithms implemented in STFT bins and experimental results show that tracking speech in the log Bark power spectral domain, taking into account the temporal dynamics of each subband envelope, is beneficial. Regarding the computational complexity, the percentage decrease in the real-time factor is 44% when using Bark bands compared to when using STFT bins.
Authentication of Galileo GNSS Signal by Superimposed Signature with Artificial Noise

Global navigation satellite systems (GNSS) are widely used in many civil applications to get information on position, velocity and timing (PVT). However, current systems (such as global positioning system (GPS) and Galileo) do not include any feature to authenticate the received signal, therefore leaving open the possibility from an attacker to spoof the GNSS signal and induce a wrong PVT computation at the receiver. In this paper we propose a solution based on the superposition of an authentication message (signature) and artificial noise (AN) on top of the existing navigation signal. Both the authentication message and AN are unpredictable and therefore can not be arbitrarily generated by an attacker. After transmission, through an external public authenticated but asynchronous (thus not useful for PVT) channel, both the authentication message and the AN are revealed, allowing the receiver to check if they were present along the previously received navigation signal. We consider the hypothesis testing problem at the legitimate receiver to decide the authenticity of the message, and we analyze its performance under two attacks: a generation attack in which the attacker does not generate the authentication signal and a replay attack in which a legitimate (including authentication message) signal is replayed by the attacker with a suitable delay in order to induce the desired PVT at the victim. The receiver operating characteristic (ROC) curve is obtained for the hypothesis testing problem under the two attacks.
Unsupervised Domain Adaptation by regularizing Softmax Activation

In recent years, deep learning has achieved very good results with a large amount of labeled data but can't generalize well when there is a shift between train data distri-bution(source domain) and test data distribution(target domain). Deep domain adaptation is an effective way to solve this problem. Many previous deep domain adaptation methods are based on Maximum Mean Discrepancy(MMD). These methods use MMD to regularize the feature-layers to learn transferable features directly. However, in this paper, we propose to use MMD to regularize the softmax predictions to learn more transferable features by backpropagating. At the same time, in order to get discriminative classifiers, we propose to depart but bridge the domain-invariant feature, which is learned by matching the feature distribution, and the classifying feature, which is before the final softmax, by a Residual-block. Our method can be implemented in almost all deep networks with softmax classifiers. In order to compare with the recent deep domain adaptation methods, we implement our method on Alexnet and outperforms almost all state-of-the-art methods on standard domain adaptation benchmarks.
Video Salient Object Detection via Multiple Time-scale Analysis

This paper focuses on salient object detection in video by multiple time-scale analysis, which exploits the temporally consistent information under three different scales. In the first time-scale, we define an effective measure called motion contrast from both low-level cues and the optical flow fields. In the second time-scale, we propose a novel approach to repair the inaccurate motion contrast due to the mistake of optical flow. In the third time-scale, considering the low-contrast objects that stop moving for a certain amount of time and cannot remain prominent, we present a robust motion detection method based on point-tracking and trajectories clustering. Finally, the outcomes from the three time-scales jointly formulate the saliency detection by Bayesian inference. The proposed model is evaluated on the widely-used DAVIS and FBMS benchmark. Experiments demonstrate that our proposed model substantially outperforms the state-of-the-art saliency detection models.
Spatio-Temporal Control of Cell Adhesion: Toward Programmable Platforms to Manipulate Cell Functions and Fate

Biophysical and biochemical signals of material surfaces potently regulate cell functions and fate. In particular, micro- and nano-scale patterns of adhesion signals can finely elicit and affect a plethora of signaling pathways ultimately affecting gene expression, in a process known as mechanotransduction. Our fundamental understanding of cell-material signals interaction and reaction is based on static culturing platforms, i.e., substrates exhibiting signals whose configuration is time-invariant. However, cells in-vivo are exposed to arrays of biophysical and biochemical signals that change in time and space and the way cells integrate these might eventually dictate their behavior. Advancements in fabrication technologies and materials engineering, have recently enabled the development of culturing platforms able to display patterns of biochemical and biophysical signals whose features change in time and space in response to external stimuli and according to selected programmes. These dynamic devices proved to be particularly helpful in shedding light on how cells adapt to a dynamic microenvironment or integrate spatio-temporal variations of signals. In this work, we present the most relevant findings in the context of dynamic platforms for controlling cell functions and fate in vitro. We place emphasis on the technological aspects concerning the fabrication of platforms displaying micro- and nano-scale dynamic signals and on the physical-chemical stimuli necessary to actuate the spatio-temporal changes of the signal patterns. In particular, we illustrate strategies to encode material surfaces with dynamic ligands and patterns thereof, topographic relieves and mechanical properties. Additionally, we present the most effective, yet cytocompatible methods to actuate the spatio-temporal changes of the signals. We focus on cell reaction and response to dynamic changes of signal presentation. Finally, potential applications of this new generation of culturing systems for in vitro and in vivo applications, including regenerative medicine and cell conditioning are presented.
Optical Microscopy Study of Soiling on Photovoltaic Glass: Evaluation of Mitigation Strategies

The natural soiling of photovoltaic cover glass has recently been shown to include both inorganic and organic particulate matter. Under favorable growth conditions, the latter can lead to the growth of dense colonies of filamentous fungi, potentially leading to measurable performance losses over time. Herein, we report on a field study where glass coupon samples were deployed in soiling-prone locations, focusing on Dubai (United Arab Emirates) and Mumbai (India). For each site location, clear differences in the soiling were observed. The samples from Mumbai were contaminated with an abundance of filamentous fungi whereas the samples from Dubai had primarily inorganic contamination. The effectiveness of soiling mitigation strategies, including cleaning techniques and glass coatings, are discussed in detail.
Rank Projection Trees for Multilevel Neural Network Interpretation

A variety of methods have been proposed for interpreting nodes in deep neural networks, which typically involve scoring nodes at lower layers with respect to their effects on the output of higher-layer nodes (where lower and higher layers are closer to the input and output layers, respectively). However, we may be interested in picking out a prioritized collection of subsets of the inputs across a range of scales according to their importance for an output node, and not simply a prioritized ranking across the inputs as singletons. Such a situation may arise in biological applications, for instance, where we are interested in epistatic effects between groups of genes in determining a trait of interest. Here, we outline a flexible framework which may be used to generate multiscale network interpretations, using any previously defined scoring function. We demonstrate the ability of our method to pick out biologically important genes and gene sets in the domains of cancer and psychiatric genomics.
Seasonal Renting Scheme

The Cloud computing programme expounds the operation of hiring the servers for service access to users from remote locations. In the existing system the service provider would hire predetermined amount of servers to provide customer service, which is achieved by renting long term servers. The fixed amount of servers is inadequate to serve the service to users in seasonal period, where request for the service is abruptly increase in seasonal period. This scenario infects the business profit and results reduction in revenue. To overcome these drawbacks from existing system, it introduces seasonal renting scheme, which contains both long term servers and short term servers. Seasonal renting scheme would hire the additional servers in seasonal period, when the requests for service were increases. These additional servers are short term servers dedicated for only seasonal period of time and its cost is higher than comparable to long term servers. In this paper, it describes about how to analyze the service efficiency of customer requests in seasonal period based on the waiting period for each customer to get a service response. And using service efficiency factor service provider would decide to hire the additional servers (short term servers) to give an efficient service to customer. By hiring the additional servers at seasonal period will not infect the profit and it would increases revenue [9] of the business.
Accuracy Verification of Knife Tip Position Estimation for Liver Surgery Support System

Our surgical support system can issue a warning when the surgical knife approaches that should not be cut, e.g. a large blood vessel. It can also navigate the knife-tip to appropriately resect a tumor. Our system estimates the position and orientation of the surgical knife and the target organ using two different distance sensors during surgery. The distance between the knife-tip and the blood vessels inside the organ is measured. In this paper, we report the verification of accuracy of the knife-tip position estimation. The experimental results show that the position estimation error of the knife-tip is 0.3 mm and the standard deviation is 0.3 mm.
Efficient Re-planning for Robotic Cars

We consider the problem of the reactive re-planning of an optimal trajectory for autonomous vehicles subject to geometric and dynamic constraints. Reactive replanning is used when a vehicle following a planned trajectory encounters an unforeseen obstacle. In such a case, a new local trajectory that avoids the obstacle has to be generated, without violating any constraint and preserving optimality. The solution presented in the paper guarantees that the new trajectory rejoins the previously planned one shortly after the obstacle. Moreover, the transition between old and new trajectory is smooth up to second derivative (curvature), which makes it easy to track an emergency manoeuvre. Finally, our solution is efficient and can be implemented in real-time on lean hardware. In order to validate the approach, we show how the re-planning can be executed in a few milliseconds (on a standard machine) for the realistic example of a racing car.
Artsy-GAN: A style transfer system with improved quality, diversity and performance

This paper proposes Artsy-GAN: a generative adversarial approach for style transfer. Style transfer has focused mostly on transferring the style of one image (e.g. painting) to another image (e.g, a photograph). Important progress has been done to process any image in real-time and, more recently, with arbitrary style images. A different approach has been proposed based on Generative Adversarial Networks (GAN), by translating an image from one context (e.g. photograph) to another (e.g. Van Gogh painting). To achieve this image-to-image translation, for example, Cycle-GAN uses a cycle consistency requirement to be able to recover the original image after translation and thus keep the content from the input images. This is complex and slow to train. Another disadvantage of this systems is that they take the source of randomness only from the input image, limiting the diversity of the output. In this work, we improve the quality, efficiency and diversity in three ways. First, we use perceptual loss to replace the reconstructor with significant improvement in quality and speed of training. Second, we improve the speed for predicting by processing images with chroma sub-sampling. Third, we improve diversity by introducing noise in the input of the generator and a new loss function that encourages to generate different details for the same content image. Experiment results show that, compared to the state-of-art, Our method could improve the quality and diversity of the output, as well as the speed advantage.
The computation of the kQ-product and properties of wireless power transfer systems

This paper presents an efficient computation algorithm of the kQ-product, based on a generalized power transfer system. Giving an explicit definition for the kQ product– called also Figure of Merit (FoM), the inaccuracies of previous definitions have been over fulfilled. Based on the circuit theory, in the definition of the transfer quality factor, we prove that the kQ-product is very useful in the analysis and design of the load matching networks that are optimized for the maximum power transfer efficiency. In this way, the concept of the kQ-product is extended from just coupled coils to the general two-port systems.
CPW-fed Monopole Printed Antenna using Staircase shaped Defected Ground Structure for Wireless Application

A CPW- fed monopole printed antenna using staircase shaped defected ground structure has been proposed in this paper. In this Defected ground contains a wide asymmetrical rectangular slotted ground with additional staircase shaped stub and a pair of inverted L shaped stub on either side of CPW–fed. The proposed antenna results a broad impedance bandwidth of 1.32GHz-3.23GHz(1.91GHz) at 2.1GHz solution frequency, and having a very good radiation pattern, suitable peak gain of 4.42 dB and high impedance matching with VSWR<2,which make it suitable for wireless and WLAN applications as CDMA, GPS, Wifi, Bluetooth, LTE33-41.
Hermetic Wafer Level Packaging of LED Modules with Phosphor Ceramic Converter for White Light Applications based on TSV Technology

In this work we present the development of a new hermetic wafer level packaging approach for fabrication of white light LEDs with suspended phosphor ceramic converter. In this new architecture, the ceramic converter is not directly attached to the LED chip but part of the package and is arranged with a defined distance to the LED. This enables the heat generated by the light conversion to be dissipated directly via the ceramic converter into the package instead of through the LED itself. The packaging approach relies on through silicon via (TSV) based silicon interposer wafers which are wafer to wafer bonded to silicon frame wafers using AuSn seal rings to form cavity wafers. The frame wafers have through cavities with sloped mirroring side walls to enable an optimal reflection of light out of the cavities and thus a high light efficiency of the mounted LEDs.The LEDs are bonded into the cavities onto the silicon interposer which feeds the electrical contacts to its back side. The cavities with the mounted LEDs are subsequently sealed with the phosphor converter ceramics. The created LED modules are assembled to test boards were the thermal resistance of the package was determined and compared with simulation results.
A Joint Density Based Rank-Score Fusion for Soft Biometric Recognition at a Distance

In order to improve recognition performance, fusion has become a key technique in the recent years. Compared with single-mode biometrics, the recognition rate of multi-modal biometric systems is improved and the final decision is more confident. This paper introduces a novel joint density distribution based rank-score fusion strategy that combines rank and score information. Recognition at a distance has only recently been of interest in soft biometrics. We create a new soft biometric database containing the human face, body and clothing attributes at three different distances to investigate the influence by distance on soft biometric fusion. A comparative study about our method and other state of the art rank level and score level fusion methods are also conducted in this paper. The experiments are performed using a soft biometric database we created. The results demonstrate the recognition performance is significantly improved by our proposed method.
Tools for Attacking Tumors: Performance Comparison of Triaxial, Choke Dipole, and Balun-Free Base-Fed Monopole Antennas for Microwave Ablation

Microwave ablation (MWA) is a promising therapeutic technique that uses minimally invasive interstitial antennas for heating tumors to cytotoxic temperatures [1], [2]. Over the years, numerous MWA antennas have been reported in the literature (e.g., [3]-[15]). MWA antenna designs typically use coaxial cable feed lines to deliver the microwave energy to the active part of the antenna. Due to the unbalanced nature of coaxial cables, current can flow on the outer surface of the outer conductor. If not appropriately suppressed, this current can cause unwanted heating of healthy tissue along the antenna? s insertion path. Moreover, in such situations, the input impedance of the antenna becomes dependent on the insertion depth.
Sensing Matrix Sensitivity to Random Gaussian Perturbations in Compressed Sensing

In compressed sensing, the choice of the sensing matrix plays a crucial role: it defines the required hardware effort and determines the achievable recovery performance. Recent studies indicate that by optimizing a sensing matrix, one can potentially improve system performance compared to random ensembles. In this work, we analyze the sensitivity of a sensing matrix design to random perturbations, e.g., caused by hardware imperfections, with respect to the total (average) matrix coherence. We derive an exact expression for the average deterioration of the total coherence in the presence of Gaussian perturbations as a function of the perturbations' variance and the sensing matrix itself. We then numerically evaluate the impact it has on the recovery performance.