Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and Design of Transformer-Based Dual-Band VCO for Software-Defined Radios

This work presents complete analysis of both one- port and two-port dual-band oscillators using transformer-based fourth-order LC tanks, from which critical parameters including oscillation frequency, start-up condition, tank Q, phase noise-are thoroughly derived and compared. It is shown that one-port oscillators consume less power than two-port counterparts but may suffer from stability problem which can be solved by a notch-peak cancellation technique. On the other hand, compared to one-port oscillators, two-port oscillators need to consume more power to obtain the same output swing, but their phase noise can be improved more linearly with increasing bias current, and thus they can achieve lower phase noise with a sufficiently large bias current. Based on the results, a dual-band quadrature voltage- controlled oscillator (Q-VCO) is systematically designed and implemented in a 0.13- m CMOS process for software-defined -radio (SDR) applications, in which the two-port topology is used in the low band for low phase noise and the one-port topology is employed in the high band for low power consumption. The prototype achieves a dual-band operation with in-phase and quadrature-phase (IQ) output signals from 2.7 GHz to 4.3 GHz and from 8.4 GHz to 12.4 GHz. At 3.6 GHz and 10.4 GHz, phase noise at 3 MHz offset of dBc/Hz and dBc/Hz and sideband-rejection ratios (SBR) of 37 dB and 41 dB are measured, respectively.
Highly accurate DSM reconstruction using Ku-band airborne InSAR

We present a newly developed airborne InSAR system incorporating a novel phase unwrapping algorithm, capable of retrieving a highly accurate Digital Surface Model (DSM). The SAR sensor system, with a spatial resolution of 30 cm, is carried on an airborne platform which has 2 antennas placed in a baseline length of 1 m. We have established a DSM reconstruction processing technique, which includes the new "Iterated Conditional Modes-Minimum Cost Flow" (ICM-MCF) phase-unwrapping algorithm. The ICM-MCF algorithm finds a locally optimal configuration of unwrapped phases under a well-characterized statistical model of the terrain and noise. An experimental field observation was carried out in Tsukuba, Japan. The DSM was generated, and the height accuracy of the SAR-DSM was evaluated by comparing with laser profiler data. For 50 cm x 50 cm mesh, an accuracy of better than 50 cm in height was confirmed.
New Systems, New Behaviors, New Patterns: Monitoring Insights from System Standup

Disentangling significant and important log messages from those that are routine and unimportant can be a difficult task. Further, on a new system, understanding correlations between significant and possibly new types of messages and conditions that cause them can require significant effort and time. The initial standup of a machine can provide opportunities for investigating the parameter space of events and operations and thus for gaining insight into the events of interest. In particular, failure inducement and investigation of corner case conditions can provide knowledge of system behavior for significant issues that will enable easier diagnosis and mitigation of such issues for when they may actually occur during the platform lifetime. In this work, we describe the testing process and monitoring results from a testbed system in preparation for the ACES Trinity system. We describe how events in the initial standup including changes in configuration and software and corner case testing has provided insights that can inform future monitoring and operating conditions, both of our test systems and the eventual large-scale Trinity system.
Joint models for efficient estimation in proportional hazards regression models

In survival studies, information lost through censoring can be partially recaptured through repeated measures data which are predictive of survival. In addition, such data may be useful in removing bias in survival estimates, due to censoring which depends upon the repeated measures. Here we investigate joint models for survival T and repeated measurements , given a vector of covariates . Mixture models indexed as f(T∣) f(∣T,) are well suited for assessing covariate effects on survival time. Our objective is efficiency gains, using non‐parametric models for in order to avoid introducing bias by misspecification of the distribution for . We model (T∣) as a piecewise exponential distribution with proportional hazards covariate effect. The component (∣T,) has a multinomial model. The joint likelihood for survival and longitudinal data is maximized, using the EM algorithm. The estimate of covariate effect is compared to the estimate based on the standard proportional hazards model and an alternative joint model based estimate. We demonstrate modest gains in efficiency when using the joint piecewise exponential joint model. In a simulation, the estimated efficiency gain over the standard proportional hazards model is 6.4 per cent. In clinical trial data, the estimated efficiency gain over the standard proportional hazards model is 10.2 per cent. Copyright © 2003 John Wiley & Sons, Ltd.
Trait Heritability in Major Transitions 1 2

8 A crucial component of major transitions theory is that after the transition, adaptation 9 occurs primarily at the level of the new, higher-level unit. For collective-level adaptations 10 to occur, though, collective-level traits must be heritable. Since collective-level traits are 11 functions of lower-level traits, collective-level heritability is related to particle-level 12 heritability. However, the nature of this relationship has rarely been explored in the 13 context of major transitions. We examine relationships between particle-level heritability 14 and collective-level heritability for several functions that express collective-level traits in 15 terms of particle-level traits. When this relationship is linear, the heritability of a 16 collective-level trait is never less than that of the corresponding particle-level trait and is 17 higher under most conditions. For more complicated functions, collective-level 18 heritability is higher under most conditions, but can be lower when the function relating 19 particle to cell-level traits is sensitive to small fluctuations in the state of the particles 20 within the collective. Rather than being an impediment to major transitions, we show that 21 collective-level heritability superior to that of the lower-level units can often arise ‘for 22 free’, simply as a byproduct of collective formation. 23 24 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/041830 doi: bioRxiv preprint first posted online Feb. 29, 2016;
High-speed Depth Stream Generation from a Hybrid Camera

High-speed video has been commonly adopted in consumer-grade cameras, augmenting these videos with a corresponding depth stream will enable new multimedia applications, such as 3D slow-motion video. In this paper, we present a hybrid camera system that combines a high-speed color camera with a depth sensor, e.g. Kinect depth sensor, to generate a depth stream that can produce both high-speed and high-resolution RGB+depth stream. Simply interpolating the low-speed depth frames is not satisfactory, where interpolation artifacts and lose in surface details are often visible. We have developed a novel framework that utilizes both shading constraints within each frame and optical flow constraints between neighboring frames. More specifically we present (a) an effective method to find the intrinsics images to allow more accurate normal estimation; and (b) an optimization-based framework to estimate the high-resolution/high-speed depth stream, taking into consideration temporal smoothness and shading/depth consistency. We evaluated our holistic framework with both synthetic and real sequences, it showed superior performance than previous state-of-the-art.
On-line reference trajectory generation for manually convoying a platoon of automatic urban vehicles

Various #x201C;Urban Transportation Systems#x201D; are currently in developing, in order to put forward solutions to congestion and pollution in dense areas. Autonomous electric vehicles in free-access can be seen as an attractive approach, in view of the large flexibility that can be expected. One instrumental functionality linked to this solution is platoon motion: several autonomous vehicles accurately follow the trajectory of a manually driven first vehicle, with pre-specified inter-distances. A global decentralized platoon control strategy, supported by inter-vehicle communications and relying on nonlinear control techniques is here proposed. Each vehicle is controlled with respect to the same smooth reference trajectory, inferred on-line from the motion of the first vehicle via B-spline optimization. Experimental results, carried out with four urban vehicles, demonstrate the capabilities of the proposed approach.
An Investigation on the Effects of Virtual Social Support on Working Memory and Stress

Stress has a negative effect on day-to-day behavior and cognition. Face-to-face social interactions often induce feelings of social support, which works to counteract the negative effects of stress. However, it is unclear if virtual interactions offer the same benefits as face-to-face interactions. This study explores the relationship between perceived stress levels and their effect on perceived social support and working memory functioning. We also explored how mood is affected by stressful experiences. Participants engaged in a laboratory stressor, where participants submerged their hand in cold water, to elicit an appropriate stress response. After the stress task, participants engaged in a supportive imagined interaction and completed a working memory task. We found that an imagined virtual interaction does not induce feelings of social support when compared to a control condition. We also saw no significant difference in positive or negative affect after the supportive interaction and no effect on working memory performance. Our findings suggest that imagining supportive interaction is not an effective way to induce feelings of social support and does not increase positive affect after experiencing a stressful event.
Removing Shadows from Images

Illumination conditions cause problems for many computer vision algorithms. In particular, shadows in an image can cause segmentation, tracking, or recognition algorithms to fail. In this paper we propose a method to process a 3-band colour image to locate, and subsequently remove shadows. The result is a 3-band colour image which contains all the original salient information in the image, except that the shadows are gone. We use the method set out in [1] to derive a 1-d illumination invariant shadow-free image. We then use this invariant image together with the original image to locate shadow edges. By setting these shadow edges to zero in an edge representation of the original image, and by subsequently re-integrating this edge representation by a method paralleling lightness recovery, we are able to arrive at our sought after full colour, shadow free image. Preliminary results reported in the paper show that the method is e ective. A caveat for the application of the method is that we must have a calibrated camera. We show in this paper that a good calibration can be achieved simply by recording a sequence of images of a xed outdoor scene over the course of a day. After calibration, only a single image is required for shadow removal. It is shown that the resulting calibration is close to that achievable using measurements of the camera's sensitivity functions.
Towards process-oriented ontology for financial analysis

The article presents an approach to integrate a business process knowledge of Decision Support Systems. It concerns two major aspects of the system, i.e. the formalization of processes predefined in Business Process Modeling Notation, the reuse of a domain ontology, and the analysis of economic and financial information. The described approach is a continuation of the construction of the intelligent cockpit for managers (InKoM project), whose main objective was to facilitate financial analysis and the evaluation of the economic status of the company in a competitive market. The current project is related to the design of smart decision support systems based on static (structural) and procedural knowledge. The content of the knowledge is focused on essential financial concepts and relationships related to the management of small and medium enterprises (SME). An experiment was carried out on real financial data extracted from the financial information system.
Language and conceptualization: Mapping conceptual representations into linguistic representations: the role of attention in grammar

Introduction Two complementary sets of problems face researchers seeking to understand the interplay between conceptual and linguistic representations: (1) How linguistic representations reveal or constrain conceptual representations, and How conceptual representations are mapped into linguistic representations. Most linguistic research aimed at cognitive or conceptual issues in language addresses the first set. Thus, work by Jackendoff (1983, 1987), Lakoff (1987), Lakoff and Johnson (1980), Langacker (1987,1991), Talmy (1988a, 1988b), and others typically begins with observations about language and uses these observations to make interesting and important inferences about what conceptual representations must or might look like given what we have observed about language, in effect reverse-engineering conceptual representations from linguistic representations. But it is also important to investigate the second set of problems – how conceptual representations are mapped into linguistic representations. This problem is rather different from the first, because it does not make use of language to draw inferences about conceptualization – to use language precludes asking this second question in a non-circular fashion. Instead, the second set of problems requires that one develop a theory or model of conceptualization that is language-independent and then investigate how particular languages, as well as language in general, map those independently describable conceptual representations into linguistic representations. This chapter presents a framework for investigating how conceptual representations of visual events are mapped into language.
Re-Ranking High-Dimensional Deep Local Representation for NIR-VIS Face Recognition

Heterogeneous face recognition refers to matching facial images captured from different sensors or sources, which has wide applications in public security and law enforcement. Because of the great differences in sensing and creating procedure, there is a huge feature gap between heterogeneous facial images. The existing methods merely focus on comparing the probe image with the gallery in feature space, while the true target may not appear at the first rank due to the appearance variations caused by different sensing patterns. In order to exploit valuable information from the initial ranking result, this paper proposes to re-rank high-dimensional deep local representation for matching near-infrared (NIR) and visual (VIS) facial images, i.e., NIR-VIS face recognition. A high-dimensional deep local representation is first constructed by extracting and concatenating deep features on local facial patches via a convolutional neural network (CNN). The initial NIR-VIS recognition ranking results can be obtained by comparing the compressed deep features. We then propose a novel and efficient locally linear re-ranking (LLRe-Rank) technique to refine the initial ranking results, which can explore valuable information from the initial ranking result. The proposed re-ranking method does not require any human interaction or data annotation and can be served as an unsupervised postprocessing technique. The experimental results on the most challenging Oulu-CASIA NIR-VIS database and CASIA NIR-VIS 2.0 database demonstrate the effectiveness of our method.
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments

The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to finally find satisfactory parameters. Of course, there exist various kinds of parameter control techniques, but not for parameter tuning. The Design of Experiment (DoE) paradigm offers a way of retrieving optimal parameter settings. It is still a tedious task, but it is known to be a robust and well tested suite, which can be beneficial for giving reason to parameter choices besides human experience. In this paper we analyse evolution strategies (ES) and particle swarm optimisation (PSO) with and without optimal parameters gathered with DoE. Reasonable improvements have been observed for the two ES variants.
High Endemicity of Soil-Transmitted Helminths in a Population Frequently Exposed to Albendazole but No Evidence of Antiparasitic Resistance

Introduction: Soil-transmitted helminths (STHs) are gastrointestinal parasites widely distributed in tropical and subtropical areas. Mass drug administration (MDA) of benzimidazoles (BZ) is the most recommended for STH control. These drugs have demonstrated limited efficacy against Trichuris trichiura and the long-term use of single-dose BZ has raised concerns of the possible emergence of genetic resistance. The objective of this investigation was to determine whether genetic mutations associated with BZ resistance were present in STH species circulating in an endemic region of Honduras. Methods: A parasitological survey was performed as part of this study, the Kato–Katz technique was used to determine STH prevalence in children of La Hicaca, Honduras. A subgroup of children received anthelminthic treatment in order to recover adult parasite specimens that were analyzed through molecular biology techniques. Genetic regions containing codons 200, 198, and 167 of the β-tubulin gene of Ascaris lumbricoides and Trichuris trichiura were amplified and sequenced. Results: Stool samples were collected from 106 children. The overall STH prevalence was 75.47%, whereby T. trichiura was the most prevalent helminth (56.6%), followed by A. lumbricoides (17%), and hookworms (1.9%). Eighty-five sequences were generated for adjacent regions to codons 167, 198, and 200 of the β-tubulin gene of T. trichiura and A. lumbricoides specimens. The three codons of interest were found to be monomorphic in all the specimens. Conclusion: Although the inability to find single-nucleotide polymorphisms (SNPs) in the small sample analyzed for the present report does not exclude the possibility of their occurrence, these results suggest that, at present, Honduras’s challenges in STH control may not be related to drug resistance but to environmental conditions and/or host factors permitting reinfections.
Balanced metric labeling

We define the balanced metric labeling problem, a generalization of the metric labeling problem, in which each label has a capacity, i.e., at most l vertices can be assigned to it. The balanced metric labeling problem is a generalization of fundamental problems in the area of approximation algorithms, e.g., arrangements and balanced partitions of graphs. It is also motivated by resource limitations in certain practical scenarios. We focus on the case where the given metric is uniform and note that this case alone encompasses various well-known graph partitioning problems. We present the first (pseudo) approximation algorithm for this problem, achieving for any ε, 0 < ε < 1, an approximation factor of O((ln n)/ε), while assigning at most min {O(ln k)/1 - ε, l + 1| ( 1 + ε) l vertices to each label (k is the number of labels). Our approximation algorithm is based on a novel randomized rounding of a linear programming formulation that combines an embedding of the graph in a simplex together with spreading metrics and additional constraints that strengthen the formulation. Our randomized rounding technique uses both a randomized metric decomposition technique and a randomized label assignment technique. At the heart of our approach is the fact that only limited dependency is created between the labels assigned to different vertices, allowing us to bound the expected cost of the solution and the number of vertices assigned to each label, simultaneously. We note that the number of vertices assigned to each label is bounded via a new inequality of Janson[15] for tail bounds of (partly) dependent random variables.
Blind identification of image manipulation type using mixed statistical moments

Abstract. We present a blind identification of image manipulation types such as blurring, scaling, sharpening, and histogram equalization. Motivated by the fact that image manipulations can change the frequency characteristics of an image, we introduce three types of feature vectors composed of statistical moments. The proposed statistical moments are generated from separated wavelet histograms, the characteristic functions of the wavelet variance, and the characteristic functions of the spatial image. Our method can solve the n-class classification problem. Through experimental simulations, we demonstrate that our proposed method can achieve high performance in manipulation type detection. The average rate of the correctly identified manipulation types is as high as 99.22%, using 10,800 test images and six manipulation types including the authentic image.
The Light Stages and Their Applications to Photoreal Digital Actors

The Light Stage systems built at UC Berkeley and USC ICT have enabled a variety of facial scanning and reﬂectance measurement techniques that have been explored in several research papers and used in various commercial applications. This short paper presents the evolutionary history of the Light Stage Systems and some of the techniques and applications they have enabled
A new efficient bypass coding scheme based on logarithmic domain

This paper proposes a new efficient bypass coding scheme (EBCS) based on Logarithmic Binary Arithmetic Coding (LBAC). The bypass coding model is used to encode a symbol which has equal probability (0.5). The percentage of the bypass coding model is about 25 in CABAC of H.265/HEVC. The proposed EBCS provides a hardware-efficient design that can significantly increase the processing speed, and it has a simple algorithm structure. Experimental results show that the EBCS can reduce bypass coding time by 60% roughly. For a hardware implementation in this paper, the overall processing speed is improved by about 96%, and the hardware cost is low.