Miracle-dz/UniFAR-FTUs huggingface dataset:
Repurposing FM: Radio Nowhere to OSNs Everywhere

While online social networks (OSNs) play a critical role in developing social capital [18], many communities are unable to utilize the benefits of OSNs due to lack of Internet accessibility. In this paper, we investigate the feasibility of the Radio Broadcast Data System (RBDS) associated with FM radio stations as a means to deliver social network content to OSN users who do not have access to Internet services. Using Instagram as a case study, we analyze data from 254 public Instagram users associated with the Tribal Digital Village (TDV) network in Southern California. Our analysis of over 1.2 million unique Instagram posts reveals that Instagram users in the TDV network interact with locally generated content 46.6× more often than content generated by users from outside the network. We use our observations of OSN usage to compare five OSN content scheduling approaches. Our evaluation reveals that up to 81% of users received at least half of their content requests and 35.5% of the 1.1 million requested Instagram photos were transmitted to users.
Merlin : Metabolic Models Reconstruction using Genome-Scale Information ?

This article describes Merlin, a user-friendly program that performs functional genomic annotations of lists of genes. Merlin retrieves information of each homologue and automatically scores the results, allowing the user to change the score selection, and dynamically (re-)annotate the genome. Merlin expedites the transition from genome-scale data to SBML metabolic models, allowing the user to have a preliminary view of the biochemical network.
Multiset Canonical Correlations Using Globality Preserving Projections With Applications to Feature Extraction and Recognition

Multiset features extracted from the same patterns always represent different characteristics of data. Thus, it is very valuable to perform the extraction on multiple feature sets. This paper addresses the issue of multiset correlation feature extraction (MCFE) in multiple feature representations. A novel method is proposed to carry out the MCFE for classification, called multiset canonical correlations using globality-preserving projections (MCC-GPs), which can perform joint dimensionality reduction for high-dimensional data. MCC-GP integrates correlational characteristics of feature pairs and global geometric information of data in the transformed low-dimensional space. This makes MCC-GPs have better discriminant ability than a previous method proposed by the authors, called multiset integrated canonical correlation analysis (MICCA), which only considers correlations for recognition tasks. Furthermore, MCC-GP can subsume two popular feature extraction methods into its framework under some constraints. This also provides a new insight for these two methods. The proposed method is applied to pattern recognition and examined using the COIL-100 and ETH-80 object databases and AR, CMU PIE, and Yale face databases. Extensive experimental results show that MCC-GP outperforms MICCA and multiset canonical correlation analysis in terms of classification accuracy and efficiency.
Fast and Effective L0 Gradient Minimization by Region Fusion

L0 gradient minimization can be applied to an input signal to control the number of non-zero gradients. This is useful in reducing small gradients generally associated with signal noise, while preserving important signal features. In computer vision, L0 gradient minimization has found applications in image denoising, 3D mesh denoising, and image enhancement. Minimizing the L0 norm, however, is an NP-hard problem because of its non-convex property. As a result, existing methods rely on approximation strategies to perform the minimization. In this paper, we present a new method to perform L0 gradient minimization that is fast and effective. Our method uses a descent approach based on region fusion that converges faster than other methods while providing a better approximation of the optimal L0 norm. In addition, our method can be applied to both 2D images and 3D mesh topologies. The effectiveness of our approach is demonstrated on a number of examples.
A Simple Counterexample to Several Problems in the Theory of Asset Pricing

We give an easy example of two strictly positive local martingales that fail to be uniformly integrable, but such that their product is a uniformly integrable martingale. The example simplifies an earlier example given by the second author. We give applications in mathematical finance and we show that the phenomenon is present in many incomplete markets.
Loneliness in the Workplace

Loneliness in the workplace has received relatively little attention in the literature. The research surrounding loneliness tends to focus almost exclusively on personal characteristics as the primary determinant of the experience, and largely ignores the workplace as a potential trigger of loneliness. As such, personality tends to be overestimated as the reason for loneliness, whilst only modest emphasis is given to environmental factors, such as organisational environments. Therefore, the overall aim of this thesis was to explore the notion of loneliness in the workplace, with a particular emphasis on examining the antecedents and outcomes of its development in work contexts. The first stage of the research included the development and empirical examination of a scale measuring work-related loneliness. A 16-item scale was constructed and tested for its reliability and factor structure on a sample of 514 employees from various organisations. Exploratory factor analysis indicated two factors best represent the data, namely Social Companionship and Emotional Deprivation at Work. For the main study, a theoretical model was constructed whereby various antecedents (personal characteristics, social support, job characteristics, and emotional climate) were hypothesised to influence the development of work-related loneliness, which in turn was thought to affect employee attitudes and wellbeing. Employees from various organisations were invited to participate in the online research via email, which generated 362 submissions from diverse occupational groups. Structural equation modelling techniques were used to assess the hypothesised model, which was evaluated against a number of fit criteria. The initial results provided limited support for the Loneliness at Work Model. Consequently, a number of adjustments were necessary to obtain sufficient fit. The modified model suggests that organisational climate (comprising climate of fear, community spirit at work, and organisational fit) serves to simultaneously predict the emotional deprivation factor of loneliness (made up of seven items) and employee attitude and wellbeing. The results indicate that environmental factors such as fear, lack of community spirit, and value congruence play a role in the experience of workrelated loneliness and have an overall negative effect on employee withdrawal behaviours and job satisfaction. The findings from this study offer insight into possible areas for organisational intervention and future research.
Keplerian discs around post-AGB stars: a common phenomenon?

Aims. We aim at showing that the broad-band SED characteristics of our sample of post-AGB stars are best interpreted, assuming the circumstellar dust is stored in Keplerian rotating passive discs. Methods. We present a homogeneous and systematic study of the Spectral Energy Distributions (SEDs) of a sample of 51 post-AGB objects. The selection criteria to define the whole sample were tuned to cover the broad-band characteristics of known binary post-AGB stars. The whole sample includes 20 dusty RV Tauri stars from the General Catalogue of Variable Stars (GCVS). We supplemented our own Geneva optical photometry with literature data to cover a broad range of fluxes from the UV to the far-IR. Results. All the SEDs display very similar characteristics: a large IR excess with a dust excess starting near the sublimation temperature, irrespective of the effective temperature of the central star. Moreover, when available, the long wavelength fluxes show a black-body slope indicative of the presence of a component of large mm sized grains. Conclusions. We argue that in all systems, gravitationally bound dusty discs are present. The discs must be puffed-up to cover a large opening angle for the central star and we argue that the discs have some similarity with the passive discs detected around young stellar objects. We interpret the presence of a disc to be a signature for binarity of the central object, but this will need confirmation by long-term monitoring of the radial velocities. We argue that dusty RV Tauri stars are those binaries which happen to be in the Population II instability strip.
Towards Realization of Open Cloud Services Architecture for Data Service in Materials Field ⋆

Against the new challenges for data management and service architecture due to the evolution of “big data”, the problems of scientific domain “big data” management, reuse and on-demand services must be solved. In this paper, we propose an Open Cloud Service Architecture (OCSA) based on the joint building of materials Virtual DataSpace (VDS), Requirement Space (RS) model and Behavior Space (BS) analysis, and discuss the theoretical concept and construction method of them. Based on the cloud computing supporting environment, we adopt the mechanisms of semantic mapping and dynamic evolution to support the idea of “data first, on-demand service”. The theoretical feasibility and supporting effect of OCSA have been effectively verified through the application of materials scientific data sharing service platform.
De novo Transcriptome Assembly of Common Wild Rice (Oryza rufipogon Griff.) and Discovery of Drought-Response Genes in Root Tissue Based on Transcriptomic Data

Background The perennial O. rufipogon (common wild rice), which is considered to be the ancestor of Asian cultivated rice species, contains many useful genetic resources, including drought resistance genes. However, few studies have identified the drought resistance and tissue-specific genes in common wild rice. Results In this study, transcriptome sequencing libraries were constructed, including drought-treated roots (DR) and control leaves (CL) and roots (CR). Using Illumina sequencing technology, we generated 16.75 million bases of high-quality sequence data for common wild rice and conducted de novo assembly and annotation of genes without prior genome information. These reads were assembled into 119,332 unigenes with an average length of 715 bp. A total of 88,813 distinct sequences (74.42% of unigenes) significantly matched known genes in the NCBI NT database. Differentially expressed gene (DEG) analysis showed that 3617 genes were up-regulated and 4171 genes were down-regulated in the CR library compared with the CL library. Among the DEGs, 535 genes were expressed in roots but not in shoots. A similar comparison between the DR and CR libraries showed that 1393 genes were up-regulated and 315 genes were down-regulated in the DR library compared with the CR library. Finally, 37 genes that were specifically expressed in roots were screened after comparing the DEGs identified in the above-described analyses. Conclusion This study provides a transcriptome sequence resource for common wild rice plants and establishes a digital gene expression profile of wild rice plants under drought conditions using the assembled transcriptome data as a reference. Several tissue-specific and drought-stress-related candidate genes were identified, representing a fully characterized transcriptome and providing a valuable resource for genetic and genomic studies in plants.
A General Form for Reset Control Including Fractional Order Dynamics

Abstract Currently, reset control focuses on using structures which allow new resetting rules in order to avoid limit cycle to be caused and improve the performance of the system. This paper investigates the properties of some reset strategies, of integer and fractional order, which reset controller states to fixed or variable non-zero values and are able to eliminate or reduce the overshoot in first and higher order systems, respectively. Based on them, a general reset control strategy with fractional order dynamics is proposed with both fixed and variable resetting to non-zero values. A comparative study is given to show its benefits in terms of prevention of limit cycle and reduction of the overshoot. As a result, some guidelines to be considered for the design of such controllers depending on the application are offered.
Flow-valve: embedding a safety-valve in RED

In this paper, we present the flow-valve, a safety-valve mechanism for RED (random early detection) to protect the network from misbehaving or overpumping flows and to promote end-to-end congestion control. The flow-valve can be regarded as an implementation of the concept known as a "RED penalty-box" but our focus is to protect router resources in times of congestion. The flow-valve detects a traffic increase that goes beyond the control range of RED, and protect the local resources by forcing overpumping flows to back off. The flow-valve provides an incentive for end-to-end congestion control to keep the packet drop rate low under moderate congestion, and to conservatively back off under heavy congestion. Our simulation results demonstrate that the flow-valve can effectively protect the network from misbehaving flows and, at the same time, isolate undesirable behavior of conformant TCP. The flow-valve also has been successfully implemented onto FreeBSD.
Proceedings of Masplas'02 the Mid-atlantic Student Workshop on Programming Languages and Systems Combining Multiple Feature Selection Methods

This paper proposes a feature selection method that combines various feature selection techniques. Feature selection has been realized as one of the most important processes in various applications, especially pattern classification problems. When too many attributes are involved, training a machine to classify patterns into their respective classes is seemingly impossible. Hence, selecting good features is necessary. Albeit numerous methods to select features have been proposed, there exists no universal solution for this problem unless one searches all possible subsets of all attributes. Some techniques such as forward selection and backward elimination are feasible in terms of speed, but suffer from the effect of local optima problem. Exhaustive search technique guarantees to find the optimal subset, but it takes too long for users to wait for the output; its computational time complexity is exponential. Hence, we propose first to reduce the number of features to the minimum size, so that exhaustive search technique can handle in reasonable time, using forward selection and backward elimination techniques. In this way, the selected feature set is much better than those from forward selection and backward elimination and computed much faster than the exhaustive search technique. The proposed combined feature selection technique is tested on the off-line signature verification data set.
Construction of LT codes with unequal erasure protection for rateless data transmission

A new degree distribution, termed as the Flexible Soliton Degree Distribution(FSDD), is proposed to meet the performance need of LT codes with Unequal Erasure Protection(UEP). Owing to use the variable number of output symbols and the number of priority levels as parameters in FSDD, the encoder can flexibly generate the suitable degree distribution for LT codes with UEP. Furthermore, the improved encoding algorithm, called FSDD-LT, is proposed. The performance of the proposed encoding algorithm is compared with other conventional LT codes with UEP under the same parameters in Binary Erasure Channel(BEC).
Parallel visualization of gigabyte datasets in GeoFEM

An initial overview of parallel visualization in the GeoFEM software system is provided. Our visualization subsystem offers many kinds of parallel visualization methods for the users to visualize their huge finite‐element analysis datasets for scalar, vector and/or tensor fields at a reasonable cost. A polygonal simplification scheme is developed to make the transmission and rendition of output graphic primitives more efficient. A salient feature of the subsystem lies in its capability in the automatic setting of visualization parameter values based on the analysis of scalar/flow field topology and volumetric coherence, to improve the quality of visualization results with a minimized number of batch re‐executions. Representative experimental results illustrate the effectiveness of our subsystem. Copyright © 2002 John Wiley & Sons, Ltd.
Fast IP packet classification with configurable processor

The next generation IP routers/switches need to provide quality of service (QoS) guarantees and differentiated services. These capabilities require a packet to be classified according to multiple fields in order to determine which flow an incoming packet belongs to. We present a way of achieving fast IP packet classification with a configurable processor as a more flexible and future proof alternative to using a hard-wired ASIC. Configurable processors can be tuned by the system designer with new instructions and hardware. To accelerate table lookups and bitmap manipulation, we develop several customized instructions that are specially optimized to yield large performance improvements. It is shown that one packet needs 16 cycles in the case of cache hit and 30 cycles in the worst case of cache miss for multiple field classification (compared to hundreds of cycles for a standard RISC processor). Thus, it is demonstrated that by using two 200 MHz processors with a proper configuration, OC48 wire-speed packet classification can be achieved while matching multiple fields with sophisticated rules of ranges and/or prefixes.
Balanced allocation on graphs

It is well known that if <i>n</i> balls are inserted into <i>n</i> bins, with high probability, the bin with maximum load contains (1 + <i>o</i>(1)) log <i>n</i>/log log <i>n</i> balls. Azar, Broder, Karlin, and Upfal [1] showed that instead of choosing one bin, if <i>d</i> ≥ 2 bins are chosen at random and the ball in serted into the least loaded of the <i>d</i> bins, the maximum load reduces drastically to log log <i>n</i>/log <i>d</i> + <i>O</i>(1). In this paper, we study the two choice balls and bins process when balls are not allowed to choose any two random bins, but only bins that are connected by an edge in an underlying graph. We show that for <i>n</i> balls and <i>n</i> bins, if the graph is almost regular with degree <i>n</i><sup>ε</sup>, where ε is not too small, the previous bounds on the maximum load continue to hold. Precisely, the maximum load is log log <i>n</i> + <i>O</i>(1/ε) + <i>O</i>(1). So even if the graph has degree <i>n</i><sup>Ω(1/log log <i>n</i>)</sup>, the maximum load is <i>O</i>(log log <i>n</i>). For general Δ-regular graphs, we show that the maximum load is log log <i>n</i> + <i>O</i>(log <i>n</i>/log (Δ/log<sup>4</sup> <i>n</i>)) + <i>O</i>(1) and also provide an almost matching lower bound of log log <i>n</i> + log <i>n</i>/log (Δ log <i>n</i>). Further this does not hold for non-regular graphs even if the minimum degree is high. Vöcking [29] showed that the maximum bin size with <i>d</i> choice load balancing can be further improved to <i>O</i>(log log <i>n/d</i>) by breaking ties to the left. This requires <i>d</i> random bin choices. We show that such bounds can be achieved by making only two random accesses and querying <i>d</i>/2 contiguous bins in each access. By grouping a sequence of <i>n</i> bins into 2<i>n/d</i> groups, each of <i>d</i>/2 consecutive bins, if each ball chooses two groups at random and inserts the new ball into the least-loaded bin in the lesser loaded group, then the maximum load is <i>O</i>(log log <i>n/d</i>) with high probability. Furthermore, it also turns out that this partitioning into aligned groups of size <i>d</i>/2 is also essential in achieving this bound, that is, instead of choosing two aligned groups, if we simply choose random but possibly unaligned random sets of <i>d</i>/2 consecutive bins, then the maximum load jumps to Ω(log log <i>n</i>/log <i>d</i>) even if the two sets are always chosen to be disjoint.
Robust vision based lane tracking using multiple cues and particle filtering

One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US$518 billion. One way of combating this problem is to develop Intelligent Vehicles that are self-aware and act to increase the safety of the transportation system. This paper presents the development and application of a novel multiple-cue visual lane tracking system for research into Intelligent Vehicles (IV). Particle filtering and cue fusion technologies form the basis of the lane tracking system which robustly handles several of the problems faced by previous lane tracking systems such as shadows on the road, unreliable lane markings, dramatic lighting changes and discontinuous changes in road characteristics and types. Experimental results of the lane tracking system running at 15 Hz will be discussed, focusing on the particle filter and cue fusion technology used.
SDL modeled hybrid error control scheme for reliable multicast over Internet

With the development of IP multicast and the Internet multicast backbone (Mbone), audio/video conferencing applications become more and more popular. These realtime multicast applications usually have stringent QoS requirements. As one of the most challenging tasks in the QoS guaranteed multicast network, the technology of controlling packet loss has attracted more and more attention. We introduce a new hybrid error control scheme that integrates interleaving, forward error correction (FEC), and threshold based automatic repeat request (threshold based ARQ) to mitigate the error and loss effects encountered in wire and wireless networks. In particular, the threshold based ARQ is studied carefully to shorten the transmission delay in reliable multicast. Moreover, in order to simplify the description and validation of our scheme, specification and description language (SDL) is used for modeling it. SDL depicts different levels of our scheme, from a broad overview down to detailed designs. After the basic algorithms of hybrid error control are devised, the corresponding implementations are developed to achieve the practical performance of our scheme, and the experimental results are analyzed.
An Embedded Solution to Visual Mapping for Consumer Drones

In this paper, we propose a real-time visual mapping scheme which can be implemented on a low-cost embedded system for consumer-level ratio control (RC) drones. In our work, a 3-dimensional occupancy grid map is obtained based on an estimated trajectory from data fusion of multiple on-board sensors, composed of two downward-facing cameras, two forward-facing cameras, a GPS receiver, a magnetic compass and an inertial measurement unit (IMU) with 3-axis accelerometers and gyroscopes. Taking the advantages of the low-cost FPGA and ARM NEON intrinsics, we run our visual odometry and mapping algorithms at 10Hz on board. Meanwhile, we also present a hierarchical multi-sensor fusion algorithm to provide a robust trajectory for mapping usage. Finally, we verify the feasibility of our approaches and serval potential applications with experimental results in complex indoor/outdoor environments.