Miracle-dz/UniFAR-FTUs huggingface dataset:
AN IMPROVED STEP IN MULTICAST CONGESTION CONTROL OF COMPUTER NETWORKS

In the advent of all kinds of services on the Internet that deal with broadcasting streams of data(voice and video) with a limited bandwidth, managing multicast flows from multiple sources to multiple destinations becomes critical. TCP (Transmission Control Protocol) is for point-to-point communication. In the multicasting there is a group of receivers. All the receivers may not response at the same time. So it is very difficult to manage all the receivers. In this paper I have written some proposed step which can co-exist with the TCP protocol to manage the receivers for smoothly sending the packet by sender.
Edukace žáků s poruchami chování

Problematika diferenciace žaka problemoveho od žaka s poruchami chovani. Rizikove faktory v osobnosti žaka pro vznik a rozvoj poruchy chovani. Podpora žaka s problemy, poruchami chovani ve skolach hlavniho proudu.
The development and partial testing of the psychometric properties of a measurement scale of organizational agility

This article focuses on organizational agility, useful concept for organizations having to cope with a complex, uncertain, and turbulent environment. Defined as an organization’s ability to adapt to meet the opportunities of change, organizational agility represents a promising line of research in theory and practice. Unfortunately, no measurement scale exists to reflect the complexity of this phenomenon. This paper is based on a qualitative and quantitative study. It presents and discusses the results of exploratory and confirmatory analyses of an organizational agility scale, which exhibits good psychometric qualities at this stage of its development.
The Abstract Mac Layer Publisher Association for Computing Machinery Accessed Terms of Use Detailed Terms the Abstract Mac Layer

A diversity of possible communication assumptions complicates the study of algorithms and lower bounds for radio networks. We address this problem by defining an Abstract MAC Layer. This service provides reliable local broadcast communication, with timing guarantees stated in terms of a collection of abstract delay functions applied to the relevant contention. Algorithm designers can analyze their algorithms in terms of these functions, independently of specific channel behavior. Concrete implementations of the Abstract MAC Layer over basic radio network models generate concrete definitions for these delay functions, automatically adapting bounds proven for the abstract service to bounds for the specific radio network under consideration. To illustrate this approach, we use the Abstract MAC Layer to study the new problem of Multi-Message Broadcast, a generalization of standard single-message broadcast, in which any number of messages arrive at any processes at any times. We present and analyze two algorithms for Multi-Message Broadcast in static networks: a simple greedy algorithm and one that uses regional leaders. We then indicate how these results can be extended to mobile networks.
Frontal fasciculi and psychotic symptoms in antipsychotic-naive patients with schizophrenia before and after 6 weeks of selective dopamine D2/3 receptor blockade.

BACKGROUND Psychotic symptoms are core clinical features of schizophrenia. We tested recent hypotheses proposing that psychotic, or positive, symptoms stem from irregularities in long-range white matter tracts projecting into the frontal cortex, and we predicted that selective dopamine D2/3 receptor blockade would restore white matter. METHODS Between December 2008 and July 2011, antipsychotic-naive patients with first-episode schizophrenia and matched healthy controls underwent baseline examination with 3 T MRI diffusion tensor imaging and clinical assessments. We assessed group differences of fractional anisotropy (FA) using voxelwise tract-based spatial statistics (TBSS) and anatomic region of interest (ROI)-based analyses. Subsequently, patients underwent 6 weeks of antipsychotic monotherapy with amisulpride. We repeated the examinations after 6 weeks. RESULTS We included 38 patients with first-episode schizophrenia and 38 controls in our analysis, and 28 individuals in each group completed the study. At baseline, whole brain TBSS analyses revealed lower FA in patients in the right anterior thalamic radiation (ATR), right cingulum, right inferior longitudinal fasciculus and right corticospinal tract (CT). Fractional anisotropy in the right ATR correlated with positive symptoms (z = 2.64, p= 0.008). The ROI analyses showed significant associations between positive symptoms and FA of the frontal fasciculi, specifically the right arcuate fasciculus (z = 2.83, p= 0.005) and right superior longitudinal fasciculus (z = -3.31, p= 0.001). At re-examination, all correlations between positive symptoms and frontal fasciculi had resolved. Fractional anisotropy in the ATR increased more in patients than in controls (z = -4.92, p< 0.001). The amisulpride dose correlated positively with FA changes in the right CT (t= 2.52, p= 0.019). LIMITATIONS Smoking and a previous diagnosis of substance abuse were potential confounders. Long-term effects of amisulpride on white matter were not evaluated. CONCLUSION Antipsychotic-naive patients with schizophrenia displayed subtle deficits in white matter, and psychotic symptoms appeared specifically associated with frontal fasciculi integrity. Six weeks of amisulpride treatment normalized white matter. Potential remyelinating effects of dopamine D2/3 receptor antagonism warrant further clarification.
Six reasons why supply‐oriented indicators systematically overestimate service quality in public transport

Supply‐oriented measures of quality lead to a systematic overestimate of quality as experienced by travellers in public transport. An example is a train with an average occupation rate for seats being 50%, where, nevertheless, the occupation rate observed by travellers is much higher when some parts of the trajectory are busy. Similar examples are discussed for waiting times at stops, probabilities of arriving in time, probabilities of getting a connection and walking distances to bus stops. A plea is then made for putting more effort in measuring demand‐oriented quality measures.
A Hash Table for Line-Rate Data Processing

FPGA-based data processing is becoming increasingly relevant in data centers, as the transformation of existing applications into dataflow architectures can bring significant throughput and power benefits. Furthermore, a tighter integration of computing and network is appealing, as it overcomes traditional bottlenecks between CPUs and network interfaces, and dramatically reduces latency. In this article, we present the design of a novel hash table, a fundamental building block used in many applications, to enable data processing on FPGAs close to the network. We present a fully pipelined design capable of sustaining consistent 10Gbps line-rate processing by deploying a concurrent mechanism to handle hash collisions. We address additional design challenges such as support for a broad range of key sizes without stalling the pipeline through careful matching of lookup time with packet reception time. Finally, the design is based on a scalable architecture that can be easily parameterized to work with different memory types operating at different access speeds and latencies. We have tested the proposed hash table in an FPGA-based memcached appliance implementing a main-memory key-value store in hardware. The hash table is used to index 2 million entries in 24GB of external DDR3 DRAM while sustaining 13 million requests per second, the maximum packet rate that can be achieved with UDP packets on a 10Gbps link for this application.
Low-Cost, Wide-Area Tracking for Virtual Environments

In virtual, augmented and mixed reality applications, the position and orientation of the participating people or objects is often needed. In most cases this problem is solved by using expensive and not always that accurate special-purpose hardware. We propose an alternative position and orientation tracking system that only uses cheap off-the-shelf components like cameras and LED ropes. The construction of the scene doesn’t require any off-line calibration or absolute positioning, which makes it easy to build and indefinitely scalable. There is also no restriction on the number of cameras participating. We will show that we can calculate the orientation independent from the translation or position by using vanishing points of parallel lines. We also propose a new parameterization of the Hough transformation to make the calculations of the line detector sufficiently fast. The proposed algorithms have been implemented and tested in a virtual set-up. The first results from our tracker are promising and can compete with many (expensive) commercial trackers. The construction of a room-sized lab set-up is in progress.
Investment support system using the EVOLINO recurrent neural network ensemble

The chaotic and largely unpredictable conditions that prevail in exchange markets are of considerable interest to speculators because of the potential for profit. The creation and development of a support system using artificial intelligence algorithms provides new opportunities for investors in financial markets. Therefore, the authors have developed a support system that processes historical data, makes predictions using an ensemble of EVOLINO recurrent neural networks, assesses these predictions using a composition of high-low distributions, selects an orthogonal investment portfolio, and verifies the outcome on the real market. The support system requires multi-core hardware resources to allow for timely data processing using anMPI library-based parallel computation approach. A comparison of daily and weekly predictions reveals that weekly forecasts are less accurate than daily predictions, but are still accurate enough to trade successfully on the currency markets. Information obtained from the support system gives investors an advantage over uninformed market players in making investment decisions.
The Development of Stable Party Preferences

This article investigates to what extent party preferences learned during adolescence are stable over time. Using a recently administered two-wave panel survey among 15- and 16-year-old adolescents and their parents in Belgium (Parent–Child Socialization Study, 2012–13), we find that more than 50 per cent of the adolescents intends to vote for exactly the same party in both waves. The data suggest that the traditional explanations for this stability that apply for adult voters do not apply for younger adolescents. The strength of one’s party preference and the consistency between attitudes and a vote choice do play a role in explaining party preference stability in this age group, but the main explanation can be found in the correspondence with one’s parents. Adolescents who have the same party preference as their parents, are far more likely to have a stable preference than those who formed their initial preference independently.
Robust Estimation of Camera Motion using Local Invariant Features

Most of existing techniques to estimate camera motion are based on analysis of the optical flow. However, the estimation of the optical flow supports only a limited amount of scene motion. In this report, we present a novel approach to estimate camera motion based on analysis of local invariant features. Such features are robust across a substantial range of affine distortion. Experiments on synthesized video clips with a fully controlled environment show that our technique is more effective than the optical flowbased approaches for estimating camera motion with a large amount of scene motion.
SNAP-1D: a computer program for qualitative and quantitative powder diffraction pattern analysis using the full pattern profile

SNAP-1D is a computer program for the qualitative and quantitative analysis of powder diffraction data using the full measured data set. As measures of similarity between patterns, non-parametric statistical tests based on Spearman's correlation coefficient and the Kolmogorov–Smirnov test are used. Traditional correlation coefficients based on the Pearson formalism are also employed. This combination, suitably weighted, gives a reliable measure of qualitative pattern similarity. The method can be extended to the quantitative analysis of mixtures by using the above methods in conjunction with singular value decomposition techniques. A full description of the theory with suitable examples has been published elsewhere [Gilmore et al. (2004). J. Appl. Cryst. 37, 231–242]; here the focus is on the computer software itself. The program is commercially available, and runs on PCs under the Windows 2000 and XP operating systems with modest hardware requirements. An easy to use graphical interface is supplied.
Multi-Stream Asynchrony Dynamic Bayesian Network Model for Audio-Visual Continuous Speech Recognition

How best to describe the asynchrony of the speech and lip motion is a key problem of audio-visual speech recognition model. A multi-stream asynchrony dynamic Bayesian network (MS-ADBN) model is brought forward for audio-visual speech recognition, and in this model, audio stream and visual stream are synchronous in word node, while between the word nodes, each stream has its own independent phone, phone transition and observation vector node, and word transition probability is determined by audio stream and visual stream together. For each stream, each word is composed of its corresponding phones, and each phone is associated with observation feature (audio feature for audio stream and visual feature for visual stream), with some probability modeled by Gaussian mixed model. Compare with general multi-stream HMM, MS-ADBN model describes the asynchrony of audio stream and visual stream to the word level. The experiment results on continuous digit audio visual database show that: compare with multi-stream HMM, in the mismatch noise environment, an average improvement of 10.07% are obtained for MS-ADBN model.
A knowledge-rich approach to feature-based opinion extraction from product reviews

Feature-based opinion extraction is a task related to information extraction, which consists of extracting structured opinions on features of some object from reviews or other subjective textual sources. Over the last years, this problem has been studied by some researchers, generally in an unsupervised, domain-independent manner. As opposed to that, in this work we propose a redefinition of the problem from a more practical point of view, and describe a domain-specific, resource-based opinion extraction system. We focus on the description and generation of those resources, and briefly report the extraction system architecture and a few initial experiments. The results suggest that domain-specific knowledge is a valuable resource in order to build precise opinion extraction systems.
Epithelioid hemangioendothelioma in the thorax: Clinicopathologic, CT, PET, and prognostic features

AbstractLittle is known about prognostic factors in epithelioid hemangioendothelioma (EHE). We aimed to identify prognostic factors among various clinicopathologic and imaging features of thoracic EHEs.Forty-two patients (male:female = 20:22; median age, 49 years) of EHEs with (n = 19) and without (n = 23) thoracic involvement were included. We reviewed electronic medical records for clinical information and computed tomography (CT) features for thoracic involvement. Differences in demographics and survival outcomes of patients with and without thoracic involvement were assessed. We also estimated overall survival.The most common pattern of thoracic involvement was multiple pulmonary nodules (n = 10), followed by parenchymal tumor with pleural invasion (n = 4), reticulonodular opacities (n = 3), and diffuse pleural thickening (n = 2). No significant difference in survival was found between the thoracic EHE group and nonthoracic EHE group (P = 0.68). Among 4 different thoracic involvement types, the lung multinodular pattern tended to demonstrate longer median survival (8.5 months) than other patterns, whereas the shortest median survival (1 month) was observed for the nodule/mass with pleural involvement pattern (P = 0.038). CT manifestations of thoracic EHEs are classified into 4 patterns, of which lung multinodular pattern is associated with longer survival. Survival is not different between patients with and without thoracic involvement.
Overcoming Occlusion-Problems on Touch Screens

In this paper I want to elaborate on common problems and disadvantages on touch-based interfaces like smartphones and tablets. I will talk about occlusion-problems caused by the hand, arm, and the finger of the user and about touch imprecision caused by finger occlusion. Further I will describe different methods that have been researched to handle occlusion caused by the hand and arm of the user, as well as methods that deal with avoiding finger occlusion and the resulting touch imprecision.
Ligand-binding site prediction using ligand-interacting and binding site-enriched protein triangles

MOTIVATION Knowledge about the site at which a ligand binds provides an important clue for predicting the function of a protein and is also often a prerequisite for performing docking computations in virtual drug design and screening. We have previously shown that certain ligand-interacting triangles of protein atoms, called protein triangles, tend to occur more frequently at ligand-binding sites than at other parts of the protein. RESULTS In this work, we describe a new ligand-binding site prediction method that was developed based on binding site-enriched protein triangles. The new method was tested on 2 benchmark datasets and on 19 targets from two recent community-based studies of such predictions, and excellent results were obtained. Where comparisons were made, the success rates for the new method for the first predicted site were significantly better than methods that are not a meta-predictor. Further examination showed that, for most of the unsuccessful predictions, the pocket of the ligand-binding site was identified, but not the site itself, whereas for some others, the failure was not due to the method itself but due to the use of an incorrect biological unit in the structure examined, although using correct biological units would not necessarily improve the prediction success rates. These results suggest that the new method is a valuable new addition to a suite of existing structure-based bioinformatics tools for studies of molecular recognition and related functions of proteins in post-genomics research. AVAILABILITY The executable binaries and a web server for our method are available from http://sourceforge.net/projects/msdock/ and http://lise.ibms. sinica.edu. tw, respectively, free for academic users.
Utility maximization with random horizon: a BSDE approach

In this paper, we study a utility maximization problem with random horizon and reduce it to the analysis of a specific backward stochastic differential equation (BSDE), which we call BSDE with singular coefficients, when the support of the default time is assumed to be bounded. We prove existence and uniqueness of the solution for the equation under interest. Our results are illustrated by numerical simulations.
A probabilistic approach to learn activities of daily living of a mobility aid device user

The problem of inferring human behaviour is naturally complex: people interact with the environment and each other in many different ways, and dealing with the often incomplete and uncertain sensed data by which the actions are perceived only compounds the difficulty of the problem. In this paper, we propose a framework whereby these elaborate behaviours can be naturally simplified by decomposing them into smaller activities, whose temporal dependencies can be more efficiently represented via probabilistic hierarchical learning models. In this regard, patterns of a number of activities typically carried out by users of an ambulatory aid device have been identified with the aid of a Hierarchical Hidden Markov Model (HHMM) framework. By decomposing the complex behaviours into multiple layers of abstraction the approach is shown capable of modelling and learning these tightly coupled human-machine interactions. The inference accuracy of the proposed model is proven to compare favourably against more traditional discriminative models, as well as other compatible generative strategies to provide a complete picture that highlights the benefits of the proposed approach, and opens the door to more intelligent assistance with a robotic mobility aid.
Full-frame video stabilization with motion inpainting

Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. We propose a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality. While most previous methods end up with producing smaller size stabilized videos, our completion method can produce full-frame videos by naturally filling in missing image parts by locally aligning image data of neighboring frames. To achieve this, motion inpainting is proposed to enforce spatial and temporal consistency of the completion in both static and dynamic image areas. In addition, image quality in the stabilized video is enhanced with a new practical deblurring algorithm. Instead of estimating point spread functions, our method transfers and interpolates sharper image pixels of neighboring frames to increase the sharpness of the frame. The proposed video completion and deblurring methods enabled us to develop a complete video stabilizer which can naturally keep the original image quality in the stabilized videos. The effectiveness of our method is confirmed by extensive experiments over a wide variety of videos
Modeling musical attributes to characterize ensemble recordings using rhythmic audio features

In this paper, we present the results of a pre-study on music performance analysis of ensemble music. Our aim is to implement a music classification system for the description of live recordings, for instance to help musicologist and musicians to analyze improvised ensemble performances. The main problem we deal with is the extraction of a suitable set of audio features from the recorded instrument tracks. Our approach is to extract rhythm-related audio features and to apply them for regression-based modeling of eight more general musical attributes. The model based on Partial Least-Squares Regression without preceding Principal Component Analysis performed best for all of the eight attributes.
Force production and flow structure of the leading edge vortex on flapping wings at high and low Reynolds numbers

SUMMARY The elevated aerodynamic performance of insects has been attributed in part to the generation and maintenance of a stable region of vorticity known as the leading edge vortex (LEV). One explanation for the stability of the LEV is that spiraling axial flow within the vortex core drains energy into the tip vortex, forming a leading-edge spiral vortex analogous to the flow structure generated by delta wing aircraft. However, whereas spiral flow is a conspicuous feature of flapping wings at Reynolds numbers (Re) of 5000, similar experiments at Re=100 failed to identify a comparable structure. We used a dynamically scaled robot to investigate both the forces and the flows created by a wing undergoing identical motion at Re of∼ 120 and ∼1400. In both cases, motion at constant angular velocity and fixed angle of attack generated a stable LEV with no evidence of shedding. At Re=1400, flow visualization indicated an intense narrow region of spanwise flow within the core of the LEV, a feature conspicuously absent at Re=120. The results suggest that the transport of vorticity from the leading edge to the wake that permits prolonged vortex attachment takes different forms at different Re.