Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel adaptive reception scheme for satellite-DMB systems

The paper proposes an adaptive reception (AR) scheme for S-DMB systems. Layered streams are generated by adopting scalable video coding (SVC) technique to transmit video data hierarchically over broadcasting channel(s). Depending on the terminal's type, the minimum amount of data frames are adoptively received by employing a frame selection control at the receiver. We quantitatively investigate the benefits in terms of power consumption and available viewing time with a case of S-DMB phones.
An Agent-Based Emergent Task Allocation Algorithm in Clouds

Cloud computing has become a promising platform for dealing with emergent tasks. Meanwhile, dynamic task allocation algorithm plays a very important role in obtaining high performance computational capabilities. Unfortunately, little work has been done for emergent task scheduling under Cloud computing environment. To address this issue, we put forward a novel agent-based allocation algorithm (ABAA for short). The algorithm employed the fair competition principle of a roulette to accomplish load balancing, and adopted the dynamic adjustment principle of a buffer pool to accommodate the diversification of task arrival. We conducted extensive experiments on CloudSim platform to evaluate the performance of the strategy. The experimental results indicate that the proposed algorithm can efficiently solve emergent task allocation problem in Clouds.
Observing Spin Correlations in Single Top Production and Decay

The weak decay of a polarized top quark has a rich structure of angular correlations among its decay products. We describe some of the noteworthy features of such decays. We then examine the three modes of single top production, with an emphasis on the status of calculations of the degree and direction of polarization at Run II of the Tevatron. The associated production of a top quark with a W boson will be very difficult to observe at the Tevatron. Prospects for observing the other two production mechanisms are much better. The spin state of the produced top quark is understood at leading order in the W* production channel. For the Wg-fusion process, we present new results including the resummed logarithmic corrections of the form ln(mt^2/mb^2). The spin-dependence of the complete order alpha_s corrections to either of these processes has not yet been determined. The fraction of spin up top quarks is large (approx. 95%) for both modes provided that the appropriate spin quantization axis is chosen.
A non-uniformly distributed three-microphone array for speech enhancement in directional and diffuse noise field

This paper proposes a non-uniformly distributed threemicrophone array speech enhancement system to suppress directional interferences and diffuse noise simultaneously. Each pair of microphones is designed to tackle one kind of noise. Unlike other hybrid systems, which combine different noise suppression techniques derived in different domains, the proposed system integrates two noise suppression techniques derived in the unified power spectral density domain. In terms of objective LLR and PESQ measures, the proposed hybrid system is demonstrated more effective in eliminating directional and diffuse noise under various SNR conditions than each individual suppression technique.
Estimating Clothing Thermal Insulation Using an Infrared Camera

In this paper, a novel algorithm for estimating clothing insulation is proposed to assess thermal comfort, based on the non-contact and real-time measurements of the face and clothing temperatures by an infrared camera. The proposed method can accurately measure the clothing insulation of various garments under different clothing fit and sitting postures. The proposed estimation method is investigated to be effective to measure its clothing insulation significantly in different seasonal clothing conditions using a paired t-test in 99% confidence interval. Temperatures simulated with the proposed estimated insulation value show closer to the values of actual temperature than those with individual clothing insulation values. Upper clothing’s temperature is more accurate within 3% error and lower clothing’s temperature is more accurate by 3.7%~6.2% error in indoor working scenarios. The proposed algorithm can reflect the effect of air layer which makes insulation different in the calculation to estimate clothing insulation using the temperature of the face and clothing. In future, the proposed method is expected to be applied to evaluate the customized passenger comfort effectively.
Variability in the Effect of 5-HTTLPR on Depression in a Large European Population: The Role of Age, Symptom Profile, Type and Intensity of Life Stressors

Background Although 5-HTTLPR has been shown to influence the risk of life stress-induced depression in the majority of studies, others have produced contradictory results, possibly due to weak effects and/or sample heterogeneity. Methods In the present study we investigated how age, type and intensity of life-stressors modulate the effect of 5-HTTLPR on depression and anxiety in a European population cohort of over 2300 subjects. Recent negative life events (RLE), childhood adversity (CHA), lifetime depression, Brief Symptoms Inventory (BSI) depression and anxiety scores were determined in each subject. Besides traditional statistical analysis we calculated Bayesian effect strength and relevance of 5-HTTLPR genotypes in specified models. Results The short (s) low expressing allele showed association with increased risk of depression related phenotypes, but all nominally significant effects would turn to non-significant after correction for multiple testing in the traditional analysis. Bayesian effect strength and relevance analysis, however, confirmed the role of 5-HTTLPR. Regarding current (BSI) and lifetime depression 5-HTTLPR-by-RLE interactions were confirmed. Main effect, with other words direct association, was supported with BSI anxiety. With more frequent RLE the prevalence or symptoms of depression increased in ss carriers. Although CHA failed to show an interaction with 5-HTTLPR, in young subjects CHA sensitized towards the depression promoting effect of even mild RLE. Furthermore, the direct association of anxiety with the s allele was driven by young (≤30) individuals. Limitations Our study is cross-sectional and applies self-report questionnaires. Conclusions Albeit 5-HTTLPR has only weak/moderate effects, the s allele is directly associated with anxiety and modulates development of depression in homogeneous subgroups.
Secure deduplication on mobile devices

An increased use of mobile devices such as smart phones, PDAs and tablet computers with capabilities of storing and processing is rapidly growing. It allows users to carry an increasing volume of data, the value of this information must be protected from loss, theft or any kind of accident which may occur with the devices, making the backup process a key factor. In mobile devices the data transmission has a high cost, in price and energy, and this devices depend on batteries, optimizing the bandwidth use is crucial. Deduplication allows substantial reductions in the data volume to be transmitted over network on backup sessions, by identifying common chunks of data, transferring and storing them only once. On the other hand, usually mobile devices communications use mobile networks, and cloud storage is a viable solution for data backup. Consequently it is essential the use of cryptographic processes to protect data, during the transmission but also in storage. This paper proposes a model and a process for measuring the best performance of a safe and energy efficient backup system.
MapReduce Frequent Itemsets for Mining Association Rules

Frequent Patterns generation takes much time to execute, compute and the efficiency is less with massive datasets. In this paper, the enhanced FP-Growth (EFP-Growth) based on MapReduce framework using Hadoop approach has been proposed. The new method has high achieving performance with different minimum support. The EFP-growth can works with the large amount of datasets to discover a frequent patterns in a transaction database. With EFP-Growth, many challenges has been solved, to mine frequent patterns such as large memory consumption, high I/O cost, high time and space complexity. In the proposed method, the execution time under different minimum supports and large datasets is decreased.
A method for enhancing image retrieval based on annotation using modified WUP similarity in WordNet

Images are the most common contents on the Internet for a long time. Lots of researchers have been studied to satisfy user demands for semantic visual recognition using low-level feature (such as color or texture) or keywords which were textual annotations but still challenging. Keywords in images give great evidence to identify what images are. Keywords are not always related with image its own. It is necessary to remove those irrelevant keywords and give higher values to relevant keywords using statistical models and knowledge base such as WordNet. For this reason, we propose a modified WUP similarity measurement in WordNet to decide which keywords are close to image. To identify irrelevant keywords, we use various semantic similarity measures between keywords and image titles. We focus on solving word sense disambiguation of image titles (such as bat, mouse, jaguar, etc). The results show that by augmenting knowledge-based with proposed method we can remove irrelevant images and take a further step to solve the WSD problem.
Parameter free image artifacts detection: a compression based approach

The qualified Earth Observation (EO) images sometimes may present unexpected artifacts. These perturbations and distortions can make more difficult the analysis of images and may decrease the efficiency of interpretation algorithms because the information is distorted. Thus is necessary to implement methods able to detect these artifacts regardless of the model which are formed, i.e. parameter free. In this article, we propose and present a method based on data compression, whether lossy compression or lossless compression for detecting aliasing, strips, saturation, etc.
Common Gaps in Information Systems

Information systems and databases in six Finnish organizations are evaluated in this multiple case study research. The main idea of the research was to describe the main gaps in information systems in the case organizations. In each case the gaps are presented with authentic descriptions. The research identified altogether seven different categories of gaps. These are first abstracted to four common categories of gaps: 1) data, 2) infrastructure, 3) turning data into information and 4) people working with the information systems. Finally, the four categories are further abstracted to two common categories of gaps: 1) information and 2) infrastructure.
FBM model based network-wide performance analysis with service differentiation

In this paper, we demonstrate that traffic modeling with the fractional Brownian motion (FBM) process is an efficient tool for end-to-end performance analysis over a network provisioning differentiated services (DiffServ). The FBM process is a parsimonious model involving only three parameters to describe the Internet traffic showing the property of self-similarity or long-range dependence (LRD). As a foundation for network-wide performance analysis, the FBM modeling can significantly facilitate the single-hop performance analysis. While accurate FBM based queueing analysis for an infinite/finite first-in-first-out (FIFO) buffer is available in the existing literature, we develop a generic FBM based analysis for multiclass single-hop analysis where both inter-buffer priority and intra-buffer priority are used for service differentiation. Moreover, we present both theoretical and simulation studies to reveal the preservation of the self-similarity, when the traffic process is multiplexed or randomly split, or goes through a queueing system. It is such self-similar preservation that enables the concatenation of FBM based single-hop analysis into a network-wide performance analysis.
Recognizing cochlear implant-like spectrally reduced speech with HMM-based ASR: experiments with MFCCs and PLP coefficients

In this paper, we investigate the recognition of cochlear implantlike spectrally reduced speech (SRS) using conventional speech features (MFCCs and PLP coefficients) and HMM-based ASR. The SRS was synthesized from subband temporal envelopes extracted from original clean speech for testing, whereas the acoustic models were trained on a different set of original clean speech signals of the same speech database. It was shown that changing the bandwidth of the subband temporal envelopes had no significant effect on the ASR word accuracy. In addition, increasing the number of frequency subbands of the SRS from 4 to 16 improved significantly the system performance. Furthermore, the ASR word accuracy attained with the original clean speech, by using both MFCC-based and PLP-based speech features, can be achieved by using the 16-, 24-, or 32-subband SRS. The experiments were carried out by using the TI-digits speech database and the HTK speech recognition toolkit.
The structure and dynamics of Abell 1942

Aims. We present a dynamical analysis of the galaxy cluster Abell 1942 based on a set of 128 velocities obtained at the European Southern Observatory. Methods. Data on individual galaxies are presented and the accuracy of the determined velocities as some properties of the cluster are discussed. We have also made use of publicly available Chandra X-ray data. Results. We obtained an improved mean redshift value z = 0.22513 ± 0.0008 and velocity dispersion σ = 908 +147 −139 km s −1 . O ur analysis indicates that inside a radius of ∼1.5 h −1 70 Mpc (∼7 arcmin) the cluster is well relaxed, without any remarkable features and the X-ray emission traces the galaxy distribution fairly well. Two possible optical substructures are seen at ∼5 arcmin from the centre in the northwest and the southwest directions, but are not confirmed by the velocity field. These clumps are, however, kinematically bound to the main structure of Abell 1942. X-ray spectroscopic analysis of Chandra data resulted in a temperature kT = 5.5 ± 0. 5k eV and metal abundance Z = 0.33 ± 0.15 Z� . The velocity dispersion corresponding to this temperature using the TX–σ scaling relation is in good agreement with the measured galaxy velocities. Our photometric redshift analysis suggests that the weak lensing signal observed to the south of the cluster and previously attributed to a “dark clump” is produced by background sources, possibly distributed as a filamentary structure.
A Voltage Based Maximum Power Point Tracker for Low Power and Low Cost Photovoltaic Applications

This paper describes the design of a voltage based maximum power point tracker (MPPT) for photovoltaic (PV) applications. Of the various MPPT methods, the voltage based method is considered to be the simplest and cost effective. The major disadvantage of this method is that the PV array is disconnected from the load for the sampling of its open circuit voltage, which inevitably results in power loss. Another disadvantage, in case of rapid irradiance variation, is that if the duration between two successive samplings, called the sampling period, is too long there is a considerable loss. This is because the output voltage of the PV array follows the unchanged reference during one sampling period. Once a maximum power point (MPP) is tracked and a change in irradiation occurs between two successive samplings, then the new MPP is not tracked until the next sampling of the PV array voltage. This paper proposes an MPPT circuit in which the sampling interval of the PV array voltage, and the sampling period have been shortened. The sample and hold circuit has also been simplified. The proposed circuit does not utilize a microcontroller or a digital signal processor and is thus suitable for low cost and low power applications. Keywords—Maximum power point tracker, Sample and hold amplifier, Sampling interval, Sampling period.
Specification and Analysis of NCL Circuits

Analysis Toolkit (PAT) to model and verify behavior of NCL circuits. A few useful constructs, such as Boolean logic gates, binary half adder and pipeline ring, are successfully modeled and verified by using PAT. The flexibility and simplicity of modeling, simulation and verification show the usefulness and applicability of PAT for NCL circuit design and verification.
Analysis of the interaction with the hepatitis C virus mRNA reveals an alternative mode of RNA recognition by the human La protein

Human La protein is an essential factor in the biology of both coding and non-coding RNAs. In the nucleus, La binds primarily to 3′ oligoU containing RNAs, while in the cytoplasm La interacts with an array of different mRNAs lacking a 3′ UUUOH trailer. An example of the latter is the binding of La to the IRES domain IV of the hepatitis C virus (HCV) RNA, which is associated with viral translation stimulation. By systematic biophysical investigations, we have found that La binds to domain IV using an RNA recognition that is quite distinct from its mode of binding to RNAs with a 3′ UUUOH trailer: although the La motif and first RNA recognition motif (RRM1) are sufficient for high-affinity binding to 3′ oligoU, recognition of HCV domain IV requires the La motif and RRM1 to work in concert with the atypical RRM2 which has not previously been shown to have a significant role in RNA binding. This new mode of binding does not appear sequence specific, but recognizes structural features of the RNA, in particular a double-stranded stem flanked by single-stranded extensions. These findings pave the way for a better understanding of the role of La in viral translation initiation.
Automatic Transition From Client-Server To Peer-to-Peer Download

In traditional web client-server downloads, when the number of clients increases, the available server bandwidth decreases. This causes servers to become overloaded or to serve files slowly. This proposal addresses this problem by integrating peer-to-peer swarming with traditional client-server downloads. Clients initially attempt to download the original file. If this is too slow, they ask their peers for pieces of the file, and then begin to offer those pieces to other peers. II. PROBLEM INTRODUCTION In the traditional Internet architecture, a server handles incoming client requests. This is referred to as the client-server paradigm. The bottleneck in such systems tends to be the bandwidth at the server [16], as this bandwidth is split N ways among the accessing clients (see Fig. 1). When an increasing number of users access a web page, that page therefore loads more and more slowly. This predicament is common, and occurs whenever server bandwidth is low, a server experiences a spike in load, or when clients download very large files. A dramatic example of this problem is the " slashdot " effect, in which a sudden " flash crowd " of unanticipated clients may suddenly request certain pages, overwhelming the unexpectant server. This can happen when sites are suddenly linked to by popular sites, such as slashdot.com. These situations cause web servers to become overwhelmed and web users to have a less than favorable experience. This problem is most commonly solved by distributing the load among a set of servers that mirror the content of the original server (see Fig. 2). A company establishes mirrors by locating a set of servers in many different places on the Internet, then automatically redirecting clients to these servers thus distributing the load to the various edge servers to provide better performance for users. An example of this is the commercial CDN run by Akamai [10], which is employed by Apple to distribute their popular program iTunes TM. This solution requires a dedicated pool of servers to provide the extra bandwidth, which can be expensive. Not all sites can afford a CDN, and mirrors require cooperation, configuration, maintenance, and bandwidth. As an alternative, many web sites are relying on peer-to-peer content distribution, or swarming, with BitTorrent. In BitTorrent, clients download only some blocks of a file from a central server, and get the other blocks from their peers in the system. While a client participates in BitTorrent, it is …
Functional Regression

Functional data analysis (FDA) involves the analysis of data whose ideal units of observation are functions defined on some continuous domain, and the observed data consist of a sample of functions taken from some population, sampled on a discrete grid. Ramsay and Silverman’s 1997 textbook sparked the development of this field, which has accelerated in the past 10 years to become one of the fastest growing areas of statistics, fueled by the growing number of applications yielding this type of data. One unique characteristic of FDA is the need to combine information both across and within functions, which Ramsay and Silverman called replication and regularization, respectively. This article will focus on functional regression, the area of FDA that has received the most attention in applications and methodological development. First will be an introduction to basis functions, key building blocks for regularization in functional regression methods, followed by an overview of functional regression methods, split into three types: [1] functional predictor regression (scalar-on-function), [2] functional response regression (function-on-scalar) and [3] function-on-function regression. For each, the role of replication and regularization will be discussed and the methodological development described in a roughly chronological manner, at times deviating from the historical timeline to group together similar methods. The primary focus is on modeling and methodology, highlighting the modeling structures that have been developed and the various regularization approaches employed. At the end is a brief discussion describing potential areas of future development in this field.
Towards a detailed OpenFlow emulator

Software-Defined Networking (SDN) is an emerging network architecture that enables network programmability. Recent research activities on SDN make it important to develop an emulator that accurately emulates OpenFlow-enabled SDN networks. However, existing emulators and simulators focus on either data plane performance or software switches. This motivates us to develop a network emulator that provides accurate emulation on both control plane and data plane performance of an OpenFlow network and supports all types of OpenFlow switches. In this paper, we design a configurable emulator that allows users to input configurations and performance characteristics of different OpenFlow switches. Based on the performance measurement results from OpenFlow switches, we derive the configurable parameters and propose an accurate control plane performance model. Our implementation is based on a popular opensource OpenFlow emulator, Mininet with OpenvSwitch (OVS). The evaluation results show that the emulator we developed provides better performance fidelity than original Mininet/OVS.