Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical analysis of trajectories on Riemannian manifolds: Bird migration, hurricane tracking and video surveillance

We consider the statistical analysis of trajectories on Riemannian manifolds that are observed under arbitrary temporal evolutions. Past methods rely on cross-sectional analysis, with the given temporal registration, and consequently may lose the mean structure and artificially inflate observed variances. We introduce a quantity that provides both a cost function for temporal registration and a proper distance for comparison of trajectories. This distance is used to define statistical summaries, such as sample means and covariances, of synchronized trajectories and "Gaussian-type" models to capture their variability at discrete times. It is invariant to identical time-warpings (or temporal reparameterizations) of trajectories. This is based on a novel mathematical representation of trajectories, termed transported square-root vector field (TSRVF), and the $\mathbb{L}^2$ norm on the space of TSRVFs. We illustrate this framework using three representative manifolds---$\mathbb{S}^2$, $\mathrm {SE}(2)$ and shape space of planar contours---involving both simulated and real data. In particular, we demonstrate: (1) improvements in mean structures and significant reductions in cross-sectional variances using real data sets, (2) statistical modeling for capturing variability in aligned trajectories, and (3) evaluating random trajectories under these models. Experimental results concern bird migration, hurricane tracking and video surveillance.
Exploring the Impact of an External Crisis on R&D Expenditures of Innovative New Ventures

What is the impact of an exogenous crisis on research and development expenditures of innovative new ventures? Existing literature does not provide a clear answer. One view suggests that shrinking revenues and constrained funding reduce firms’ R&D intensity. The opposite view argues for amplified risk-seeking and innovative behavior of organizations in crisis, leading to higher commitment to R&D with resulting additional investments. We unite these opposing views in a generalized behavioral framework based on the premise that the impact of a crisis on a venture’s R&D expenditures is contingent on its pre-crisis R&D intensity. When facing a crisis, R&D-intensive companies reduce their R&D commitment, while non-R&D-intensive companies do not alter their R&D expenditure budgets, or even increase R&D spending to innovate themselves out of the adversity. We empirically test our behavioral framework using the longitudinal data from the Kauffman firm survey. The results strongly support our theoretical reasoning: during the 2008 financial crisis R&D-intensive ventures tended to substantively decrease their R&D investments (on average more than 10 percentage points decrease in R&D to sales), while their non-R&D-intensive counterparts demonstrated positive (although statistically insignificant) change in R&D investments. In other words, a crisis strikes most deeply the R&D activity of the most innovative ventures, despite the rational need to sustain R&D funding in industries with rapid technological change and short product life cycles. We conclude by positing underlying reasons for the observed behavioral patterns, and then suggest avenues for further research.
Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies

16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of ‘best available’ primer pairs for Bacteria and Archaea for three amplicon size classes (100–400, 400–1000, ≥1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.
Intelligent Fuzzy Type-Ahead Search in XML Data

: In a traditional keyword-search system over XML data, a user composes a keyword query, submits it to the system, and retrieves relevant answers. In the case where the user has limited knowledge about the data, often the user feels “left in the dark” when issuing queries, and has to use a try-and-see approach for finding information. In this paper, we study fuzzy type-ahead search in XML data, a new information-access paradigm in which the system searches XML data on the fly as the user types in query keywords. It allows users to explore data as they type, even in the presence of minor errors of their keywords. Our proposed method has the following features: 1) Search as you type: It extends Auto complete by supporting queries with multiple keywords in XML data.2) Fuzzy: It can find high-quality answers that have keywords matching query keywords approximately. 3) Intelligent: Our effective index structures, searching algorithms and materialized views can achieve a very high interactive speed. Answering queries using materialized views has been well studied in the context of structured queries and has shown significant performance benefits.
A real time multi-channel GPS positioning system architecture

The design of a system to deliver GPS observables for tracking multiple remotes in real time is discussed. The key objectives of this architecture are to allow the use of multiple small battery operated rovers and to provide low latency position measurements at a fixed central point. The GPS raw data is transmitted via a telemetry system to the central point, then presented to multiple Kalman filters. The selection of a GPS receiver for the application and design of the system architecture to distribute the load to multiple Kalman filters presents some interesting challenges. The focus of this paper is on the components, the architecture used to deliver the demanding real time processing requirements and the benefits of the system.
Research on the Execution Time Analysis Technology of the Worst Case System in Real Time System

The calculation results of the embedded real-time system correctness depends not only on the logical system, and the results also spent time, the system must ensure in response to external events in a predictable period of time. Worst Execution Time (the worst case execution time (Case) is the maximum execution time of the program in the process of running. It plays a very important role in the research of real time scheduling, task priority arbitration, resource conflict arbitration, inter task communication and hardware / software partitioning. This paper focuses on the specific hardware platform (ARM7TDMI processor), the worst case Garfield system MP3 decoding program execution time (WCET) were evaluated on the MP3 decoding program optimization and give objective evaluation, but also provide important basis for the division of hardware and software of MP3 module. The worst case execution time (WCET) calculation is mainly related to two aspects: the high level analysis (Analysis High-Level) and the underlying modeling (Modeling Low-Level). High level analysis is to analyze the program structure in a high level language, find out the sequence of instructions in the worst case, while the bottom is built hardware model in assembly environment, the worst case has a known sequence of instructions execution time. The complexity of the WCET calculation limits the size of the analyzed program and the accuracy of the calculation. This paper introduces an effective method to calculate the worst-case execution time (WCET), and develops a path analysis tool CRYINGCAT. The path analysis tools to get the instruction execution time from the bottom of the model, the anti mark flow graph analysis control extracted from the top (Control Flow Graph), and then use the containing control execution time information flow diagram to establish the integer linear programming model, and finally through the worst case solving integer linear programming model to obtain the execution time of the program (WCET). Prior informed system program in the worst case execution time (Worst-Case Execution, Time, WCET) is the design and verification of real-time scheduling and schedulability analysis of the premise, but also to determine whether the periodic tasks meet their performance goals, in order to find the basis system performance bottleneck. This paper summarizes the analysis methods of WCET program, describes the definition and composition of WCET analysis, summarize the program flow fact analysis method, and points out the research program flow fact analysis and WCET analysis of the existing problems.
Application of standing waves as audible information in hypertension therapy

Globally, there are 9.4 million cardiovascular deaths accounted for by hypertension complications. Prediction studies reveal that this number will increase to 1.15 billion in 2025 due to lack of awareness and insufficient treatment. Treatments in lowering blood pressure are less successful. Another factor is the presence of hypertension medication resistance among patients. This suggests that a solution to treat hypertension has to be found in non-pharmalogical approaches. In this study, standing waves are implemented in an audio therapy to lower blood pressure values among the tested patients. 34 subjects from both genders of different age groups joined this study. The results are promising. In total, 65% of the participating patients experienced lower systolic blood pressure values, while 53% experienced lower diastolic values. An important finding is that parallel medication interferes with the therapy and yields no improvement. This study implies that standing waves therapy is an encouraging approach for treating hypertension in a long term. Future studies will be conducted with improved experimental conditions and larger subject groups for better results.
Soil Collembola communities along a steep microclimatic gradient in the collapse doline of the Silická ľadnica Cave, Slovak Karst (Slovakia)

In spring 2005 we investigated the collembolan communities in the 50-m-deep collapse doline of the perennial ice cave Silická ľadnica in the Slovak Karst (Slovakia). Samples were taken at seven sites along a 117.5-m-long transect on the slope from the ice-bearing cave mouth at the bottom of the doline up to the terrain surface at 500 m above sea level (a.s.l.). The temperature above the soil surface (+0.6 to +13.6°C) positively correlated with altitude. Species numbers (ranging from 20–32) and diversity indices were highest at sites in the middle of the slope with rendzina and well developed organic profiles. A Kruskal-Wallis ANOVA revealed significant differences in abundance between the sites. Mean abundance near the permafrost zone at the bottom of the doline was significantly higher than at the sites further upslope. The abundances of some eurytopic and forest species were significantly correlated with soil temperature. Cluster analysis and the IndVal method indicated differences in the structure of Collembolan communities along the transect. The community at the coldest site had the lowest species richness and the highest mean abundance of individuals. A total of ten montane species were recorded, with a lower number near the permafrost zone compared to the micro-climatically more favourable middle section of the gradient.
Work, rest and (press) play: Music consumption as an indicator of human economic development

Background in music computing. Rapidly growing databases, derived from download and live-stream services like MixRadio, Last.fm or Spotify, are providing unprecedented access to global music-listening information. Part of the appeal for researchers in these data lies in the collaborative filtering these services employ—whether to navigate, find resources or engage in serendipitous browsing, mood and genre tags together with download and play data are a rich resource through which discoveries are being made concerning the influence of extra-musical, sociocultural factors on music consumption, including human development. Background addressed with to a composite to Rather than merely the expresses the level of human wellbeing a the study of music downloading monetary indicator Domestic HDI depends on three main factors: life expectancy, and standard of living. Aims. explore relationships between human and leisure, and unemployment levels in 27 hypothesize and (2) that download variability between periods of work and non-work, due to a decrease in the population for whom there is a clear distinction between work and non-work. Main contribution. A music database, consisting of over 180 million mobile-phone downloads, is used to investigate our hypotheses. The data are from millions of users that had free access to unlimited amounts of music, allowing them to explore tracks and albums unfettered by cost constraints; each download comprises various metadata relating to (anonymized) user, time, place and track. Consistent with our first hypothesis, we found significant correlations between countries’ HDI values and music-download variability across aggregated one-day and one-week time periods; countries with higher HDI values had greater download variability across these timescales. Music downloading was found to relate to differences in unemployment rates between southern- and northern-European countries in a manner consistent with our second hypothesis. Implications. Download variability correlates positively with levels of human development and employment. Our research indicates that music downloading is connected to people’s working lives, the nature of their leisure time, general living standards, and the extent to which they are able to access goods and services. We discuss our findings in respect of HDI, the European Sovereign Debt Crisis, literature on paid and unpaid work, and the types of leisure enjoyed by people in different countries. Erik Hurst’s 2007 paper, which shows that between 1965 and 2003 leisure for men increased by six to nine hours per week and for women by four to eight hours per week.
Prefrontal Cortex Motivated Cognitive Architecture for Multiple Robots

In this paper, we introduce a cerebral cortex inspired architecture for robots in which we have mapped hierarchical cortical representation of human brain to logic flow and decision making process. Our work focuses on the two major features of human cognitive process, viz. the perception action cycle and its hierarchical organization, and the decision making process. To prove the effectiveness of our proposed method, we incorporated this architecture in our robot which we named as Cognitive Insect Robot inspired by Brain Architecture (CIRBA). We have extended our research to the implementation of this cognitive architecture of CIRBA in multiple robots and have analyzed the level of cognition attained by them
A hybrid method using haar-like and skin-color algorithm for hand posture detection, recognition and tracking

Human hand posture detection and recognition is a challenging problem in computer vision. We introduce an algorithm that is capable to recognize hand posture in a sophisticated background. The system combines two algorithms to achieve better detection rate for hand. Recently Viola et al. in [10] have introduced a rapid object detection scheme; we use this approach to detect the hand posture in the first set of consecutive frames. The chromatic color distribution of skin can be found within this cluster. As the shape of hand posture keep changing in the subsequent frames, the skin regions updated dynamically. The classification of hand posture makes use of static feature for locating and counting hand fingers. Kalman Filter is used to track the face and hand blobs based on their position. In the experiments, we have tested our system in various environments, and results showed effectiveness of the approach.
Incentive-Based Energy Consumption Scheduling Algorithms for the Smart Grid

In this paper, we study Demand Response (DR) problematics for different levels of information sharing in a smart grid. We propose a dynamic pricing scheme incentivizing consumers to achieve an aggregate load profile suitable for utilities, and study how close they can get to an ideal flat profile depending on how much information they share. When customers can share all their load profiles, we provide a distributed algorithm, set up as a cooperative game between consumers, which significantly reduces the total cost and peak-to-average ratio (PAR) of the system. In the absence of full information sharing (for reasons of privacy), when users have only access to the instantaneous total load on the grid, we provide distributed stochastic strategies that successfully exploit this information to improve the overall load profile. Simulation results confirm that these solutions efficiently benefit from information sharing within the grid and reduce both the total cost and PAR.
Under the Tip of the Iceberg: Absorptive Capacity, Environmental Strategy, and Competitive Advantage

Although existing research evaluates how the adoption of proactive environmental strategies affects corporate performance, there is little understanding of the organizational mechanisms that link such strategies to competitive advantage. It is, therefore, unclear how environmental strategies relate to other management strategies that could lead to a competitive advantage. In this article, we analyze the organizational capabilities that underlie a firm’s ability to generate competitive advantage from the adoption of proactive environmental strategies. We develop and test a model where absorptive capacity facilitates the development of proactive environmental strategies that result in competitive advantage. Results from a survey of 157 German chemical firms strongly support the model.
A 1V , 10-bit Rail-to-Rail Successive Approximation Analog-to-Digital Converter in Standard 0 . 18 μ m CMOS Technology

Two architectures for a 1-V, 10-bit 200-kS/s successive approximation analog-to-digital converter (ADC) implemented in a standard CMOS 0.18 μm digital process are presented. A track-andhold circuit based on a novel implementation of the bootstrapped low-voltage analog CMOS switch with a novel rail-to-rail trackand-latch comparator circuit is described. A pMOS-only ladder containing a rail-to-rail current-to-voltage converter, performs the DAC function in the second ADC topology whereas a conventional R-2R ladder is used in the first one. Successive approximation and control logic is implemented using of a robust single clock phase D flip flop.
MULTI-SCALE IMAGE ANALYSIS OF SATELLITE DATA USING PERCEPTUAL GROUPING

A meaningful image segmentation groups the pixels into disjoint regions that consist of uniform components. Facing absence of contextual knowledge, the only alternative which can enrich our knowledge concerning the significance of our segmented groups is the creation of a hierarchy guided by the knowledge which emerges from the superficial and deep image structure [1]. In the present work, we deal with information which can be retrieved from the superficial structure of the image and we study hierarchical methods based on a region-based approach, wherein the initial pixel grouping is guided by the principles of the watershed analysis [2]. Hierarchical feature representation through multi-scale segmentation offers new possibilities in object-oriented and multi-scale image analysis of satellite images [3, 4]. Our objective, in this work, is to create a hierarchy among the gradient watersheds which preserves the topology of the initial watershed lines and extracts homogeneous objects of a larger scale. The proposed method segments an image into regions, which are then merged using an innovative saliencydriven perceptual organization approach. Moreover, we propose a criterion which allows automatically extracting the best segmentation level from the obtained hierarchical levels.
DNS of auto-ignition in turbulent diffusion H2/air flames

Direct numerical simulation (DNS) is used to study auto–ignition of turbulent diffusion flames. A novel, all–Mach number algorithm developed by Doom et al is used. The chemical mechanism is a nine species, nineteen reaction mechanism for H2 and Air from Mueller at el. 2 Simulations of three dimensional turbulent diffusion flames are performed. Isotropic turbulence is superimposed on an unstrained diffusion flame where diluted H2 at ambient temperature interacts with hot air. Both, unity and non–unity Lewis number are studied. The results are contrasted to the homogeneous mixture problem and laminar diffusion flames. Results show that auto–ignition occurs in fuel lean, low vorticity, high temperature regions with low scalar dissipation around a most reactive mixture fraction, ζMR (Mastorakos et al.). However, unlike the laminar flame where auto-ignition occurs at ζMR, the turbulent flame auto–ignites over a very broad range of ζ around ζMR, which cannot completely predict the onset of ignition. The simulations also study the effects of three-dimensionality. Past two–dimensional simulations (Mastorakos et al.) show that when flame fronts collide, extinction occurs. However, our three dimensional results show that when flame fronts collide; they can either increase in intensity, combine without any appreciable change in intensity or extinguish. This behavior is due to the three–dimensionality of the flow.
Array compression for MRI with large coil arrays

Arrays with large numbers of independent coil elements are becoming increasingly available as they provide increased signal‐to‐noise ratios (SNRs) and improved parallel imaging performance. Processing of data from a large set of independent receive channels is, however, associated with an increased memory and computational load in reconstruction. This work addresses this problem by introducing coil array compression. The method allows one to reduce the number of datasets from independent channels by combining all or partial sets in the time domain prior to image reconstruction. It is demonstrated that array compression can be very effective depending on the size of the region of interest (ROI). Based on 2D in vivo data obtained with a 32‐element phased‐array coil in the heart, it is shown that the number of channels can be compressed to as few as four with only 0.3% SNR loss in an ROI encompassing the heart. With twofold parallel imaging, only a 2% loss in SNR occurred using the same compression factor. Magn Reson Med 57:1131–1139, 2007. © 2007 Wiley‐Liss, Inc.
MUSIC-Based Joint DoA Estimation and Signal Enumeration

In this paper we describe a new criterion for the detection of the number of signals impinging on a M-element uniform linear array (ULA). Our criterion makes explicit use of the peak information of the MUSIC spectrum. Specifically, for each hypothesis of k sources, in addition to computing the noise variance estimate using the M-k smallest eigenvalues of the sample covariance matrix, the new criterion applies an additional correction term calculated from the k largest peaks of the MUSIC spectrum which is generated from the testing noise subspace of dimension M-k. We prove that the proposed criterion provides a consistent estimate of the number of signals and demonstrate that it has a better performance at low SNR for equal-power sources when compared with the original MDL-based signal number detection criterion [1]. Enumeration Ren Wu and Ioannis N. Psaromiligkos