Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimum Latency Broadcasting with Conflict Awareness in Wireless Sensor Networks

In this paper, we will illustrate a practice of pipeline process to maximize the parallelization of all possible interference-free relays in the broadcasting of wireless sensor networks (WSNs), in order to optimize the end-to-end delay performance in both the (synchronous) round-based systems and the (asynchronous) duty cycle systems. Broadcasting is one of the fundamental communications in WSNs. Existing delay-sensitive broadcasting schemes adopt an approximation approach that is based on counting the hop distance to the source. They require all relays in each 1-hop propagation to be synchronized together in order to avoid any interference, but this also incurs the block of the interference free relays from those 1-hop neighbors that have received the message. In the duty cycle system, such a block can cause the relay to miss the wake-up time of the successor node which incurs the extra delay. In our approach, a heuristic information model enumerating all the possible future sequences in terms of delay time is adopted first to achieve the optimal relay selection, initiating the study of global impact of local interference. Then, a lightweight model estimating the hop distance to the edge of network of the unaccomplished relay work is adopted with the well known greedy color scheme to achieve the close-to-optimal relay selection. The analytical and experimental results show the substantial improvement by our pipeline practice, compared with the best results known to date.
Application of Partial Directed Coherence to the Analysis of Resting-State EEG-fMRI Data

The simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data potentially allows measurement of brain signals with both high spatial and temporal resolution. Partial directed coherence (PDC) is a Granger causality measure in the frequency domain, which is often used to infer the intensity of information flow over the brain from EEG data. In the current study, we propose a new approach to investigate functional connectivity in resting-state (RS) EEG-fMRI data by combining time-varying PDC with the analysis of blood oxygenation level-dependent (BOLD) signal fluctuations. Basically, we aim to identify brain circuits that are more active when the information flow is increased between distinct remote neuronal modules. The usefulness of the proposed method is illustrated by application to simultaneously recorded EEG-fMRI data from healthy subjects at rest. Using this approach, we decomposed the nodes of RS networks in fMRI data according to the frequency band and directed flow of information provided from EEG. This approach therefore has the potential to inform our understanding of the regional characteristics of oscillatory processes in the human brain.
Single microphone wind noise reduction using techniques of artificial bandwidth extension

In this contribution, we propose a method to enhance single channel speech signals which are degraded by wind noise. In contrast to common speech enhancement systems, a special processing is required due to the highly non-stationary characteristics of wind signals. The basic idea is to exploit the fact that wind noise is mainly located at low frequencies and thus, a large frequency range of the speech is almost noise free. Techniques which artificially extend the bandwidth of telephone speech towards lower frequencies are applied to replace the highly disturbed low frequency parts. Here, the discrete model of speech production is used to reconstruct the required parts of the speech signal. Important parameters for this model are pitch frequency, the spectral envelope and a spectral gain. In this context, an evaluation is carried out which determines the robustness of several pitch estimators against wind noise. The frequency range of the reconstructed speech is finally adapted to the actual level of wind noise. Based on realistic scenarios it is shown that the influence of the wind noise can greatly be reduced by the proposed concept. This includes a comparison with a state-of-the-art speech enhancement system and an algorithm specially designed to reduce wind noise.
Ownership and Firm Performance: Evidence from 25 Countries in Central and Eastern Europe and the Former Soviet Union

Using the joint World Bank and EBRD Business Environment and Enterprise Performance Survey (BEEPS), compiled in 1999, this paper explores the relationship between firm performance and ownership in Central and Eastern Europe (CEE) and the Former Soviet Union (FSU). The literature on privatization and performance has been largely inconclusive, especially now that sample selection bias is taken into account. This paper provides evidence that foreign owned firms perform the best, performing significantly better than state owned enterprises, while firms whose owners are domestic outside companies or individuals also perform better than state owned enterprises but the result is somewhat sensitive to the specification of the model. The more significant, albeit puzzling result, is that insider owned firms perform worse than state owned firms. This result is not significant when looking at manager and worker owned firms separately. In further work, I will explore the determinants of this puzzling result.
MULTI-WAVELENGTH OBSERVATIONS OF THE 2002 OUTBURST OF GX 339–4: TWO PATTERNS OF X-RAY–OPTICAL/NEAR-INFRARED BEHAVIOR

We report on quasi-simultaneous Rossi X-ray Timing Explorer and optical/near-infrared (nIR) observations of the black hole candidate X-ray transient GX 339–4. Our obser vations were made over a time span of more than eight months in 2002 and cover the initial rise and transitio n fr m a hard to a soft spectral state in X-rays. Two distinct patterns of correlated X-ray–optical/nIR behavi or were found. During the hard state the optical/nIR and X-ray fluxes correlated well, with a nIR vs. X-ray flux powe r-law slope similar to that of the correlation found between X-ray and radio fluxes in previous studies of GX 339–4 and other black hole binaries. As the source went through an intermediate state the optical/nIR fl uxes decreased rapidly and once it had entered the spectrally soft state, the optical/nIR spectrum of GX 339–4 was much bluer and the ratio of X-ray to nIR flux was higher by a factor of more than 10 compared to the hard stat e. In the spectrally soft state changes in the nIR preceded those in the soft X-rays by more than two weeks, i ndicating a disk origin of the nIR emission, and providing a measure of the viscous time scale. A sudden on set f nIR flaring of∼0.5 magnitudes on a time scale of a day was also observed during this period. We presen t sp ctral energy distributions, including radio data, and discuss possible sources for the optical/nIR emis sion. We conclude that in the hard state this emission probably originates in the optically thin part of a jet and th at in none of the X-ray states X-ray reprocessing is the dominant source of optical/nIR emission. Finally, co mparing the light curves from the ASM and PCA instruments, we find that the X-ray/nIR delay depends critic ally on the sensitivity of the X-ray detector, with the delay inferred from the PCA (if present at all) being a fac tor of 3-6 times shorter than the delay inferred from the ASM; this may be important in interpreting previous ly reported X-ray-optical/nIR lags. Subject headings: accretion, accretion disks — binaries (including multiple ): close — black hole physics — ISM: jets and outflows — stars: individual (GX 339–4) — X-rays : stars
Exploring Support Vector Machines and Random Forests to Detect Advanced Fee Fraud Activities on Internet

In this study, we experiment with Support Vector Machines (SVM) and Random Forests (RF), which are two of the state-of-the-art machine learning algorithms. The purpose was to examine their suitability for detecting Advanced Fee Fraud (AFF) activities on internet, which due to its inherent vulnerability is often abused for various criminal activities. A set of cluster features was discovered using global CM algorithm to characterize AFF activities on internet. These features were used to train SVM and RF to classify an e-mail document as either containing AFF related information or not. The results of experiments performed show that both SVM and RF have a satisfactory performance in detecting AFF activities. However, SVM comparatively shows superior result than RF and can effectively detect the dynamic nature of AFF activities on internet.
Possible hydrogen, anti-hydrogen beams production in a long linear vacuum pipe

This paper presents the possible production of hydrogen and anti-hydrogen from pand ebeams merged in a long vacuum chamber (about 2500 m). In such a configuration with a beam kinetic energy for the paround 100 KeV, the two key parameters are the density of the ebeam and the temperature of the merged beams. The production rate is computed for several parameter sets and it is shown that it is possible to recombine 10p with nearly 100% efficiency. Possible experiments using this configuration are presented, including the fine structure constant measurement, the anti-hydrogen spectroscopy and the comparison of the gravitational mass for hydrogen and antihydrogen. PACS numbers: 25.43. +t (antiproton and antihydrogen), 06.20. Jr (fine structure constant, gravitational mass), 41.75. Lx (crystalline beams)
Programming with regions in the ml kit (for version 4)

2 Values and their Representation integer 32 bits, untagged. Unboxed (i.e., not region allocated). One bit is used for tagging when GC is enabled. real 64 bits, untagged. Boxed (i.e., allocated in region) string Unbounded size. Allocated in region. bool one 32-bit word. Unboxed. α list nil and :: cells unboxed (i.e., not region allocated). Auxiliary pairs in one region; elements in zero or more regions. Size of auxiliary pairs: two 32-bit words (three when GC is enabled). exn Exception values are boxed and are always stored in a global region. fn pat => exp An anonymous function is represented by a boxed, untagged closure. Its size is one 32-bit word plus one word for each free variable of the function. Free region variables also count as variables. One extra word is used when GC is enabled. fun f. Mutually recursive region-polymorphic functions share the same closure, which is region-allocated, untagged, and whose size (in words) is the number of variables that occur free in the recursive declaration. One extra word is used when GC is enabled. Regions and their Representation Finite (ρ:n) Region whose size can be determined at compile time. During compilation , a finite region size is given as a non-negative integer. After multiplicity inference, this integer indicates the number of times a value (of the appropriate type) is written into the region. Later, after physical size inference, the integer indicates the physical region size in words. At runtime, a finite region is allocated on the runtime stack. Infinite (ρ:INF) All other regions. At runtime, an infinite region consists of a stack allocated region descriptor, which contains pointers to the beginning and the end of a linked list of fixed size region pages. Storage Modes (only significant for infinite regions) atbot Reset region, then store value. sat Determine actual storage mode (attop/atbot) at runtime. attop Store at top of region, without destroying any values already in the region.
Intrusion Detection for Encrypted Web Accesses

As various services are provided as web applications, attacks against web applications constitute a serious problem. Intrusion detection systems (IDSes) are one solution, however, these systems do not work effectively when the accesses are encrypted by protocols. Because the IDSes inspect the contents of a packet, it is difficult to find attacks by the current IDS. This paper presents a novel approach to anomaly detection for encrypted web accesses. This approach applies encrypted traffic analysis to intrusion detection, which analyzes contents of encrypted traffic using only data size and timing without decryption. First, the system extracts information from encrypted traffic, which is a set comprising data size and timing for each web client. Second, the accesses are distinguished based on similarity of the information and access frequencies are calculated. Finally, malicious activities are detected according to rules generated from the frequency of accesses and characteristics of HTTP traffic. The system does not extract private information or require enormous pre-operation beforehand, which are needed in conventional encrypted traffic analysis. We show that the system detects various attacks with a high degree of accuracy, adopting an actual dataset gathered at a gateway of a network and the DARPA dataset.
IgH-V(D)J NGS-MRD measurement pre- and early post-allotransplant defines very low- and very high-risk ALL patients.

Positive detection of minimal residual disease (MRD) by multichannel flow cytometry (MFC) prior to hematopoietic cell transplantation (HCT) of patients with acute lymphoblastic leukemia (ALL) identifies patients at high risk for relapse, but many pre-HCT MFC-MRD negative patients also relapse, and the predictive power MFC-MRD early post-HCT is poor. To test whether the increased sensitivity of next-generation sequencing (NGS)-MRD better identifies pre- and post-HCT relapse risk, we performed immunoglobulin heavy chain (IgH) variable, diversity, and joining (V[D]J) DNA sequences J NGS-MRD on 56 patients with B-cell ALL enrolled in Children's Oncology Group trial ASCT0431. NGS-MRD predicted relapse and survival more accurately than MFC-MRD (P < .0001), especially in the MRD negative cohort (relapse, 0% vs 16%; P = .02; 2-year overall survival, 96% vs 77%; P = .003). Post-HCT NGS-MRD detection was better at predicting relapse than MFC-MRD (P < .0001), especially early after HCT (day 30 MFC-MRD positive relapse rate, 35%; NGS-MRD positive relapse rate, 67%; P = .004). Any post-HCT NGS positivity resulted in an increase in relapse risk by multivariate analysis (hazard ratio, 7.7; P = .05). Absence of detectable IgH-V(D)J NGS-MRD pre-HCT defines good-risk patients potentially eligible for less intense treatment approaches. Post-HCT NGS-MRD is highly predictive of relapse and survival, suggesting a role for this technique in defining patients early who would be eligible for post-HCT interventions. The trial was registered at www.clinicaltrials. gov as #NCT00382109.
TURBULENCE IN A THREE-DIMENSIONAL DEFLAGRATION MODEL FOR TYPE Ia SUPERNOVAE. I. SCALING PROPERTIES

We analyze the statistical properties of the turbulent velocity field in the deflagration model for Type Ia supernovae. In particular, we consider the question of whether turbulence is isotropic and consistent with the Kolmogorov theory at small length scales. Using numerical data from a high-resolution simulation of a thermonuclear supernova explosion, spectra of the turbulence energy and velocity structure functions are computed. We show that the turbulent velocity field is isotropic at small length scales and follows a scaling law that is consistent with the Kolmogorov theory until most of the nuclear fuel is burned. At length scales greater than a certain characteristic scale that agrees with the prediction of Niemeyer & Woosley, turbulence becomes anisotropic. Here, the radial velocity fluctuations follow the scaling law of the Rayleigh–Taylor instability, whereas the angular component still obeys the Kolmogorov scaling. In the late phase of the explosion, this characteristic scale drops below the numerical resolution of the simulation. The analysis confirms that a subgrid-scale model for the unresolved turbulence energy is required for the consistent calculation of the flame speed in deflagration models of Type Ia supernovae, and that the assumption of isotropy on these scales is appropriate.
VERIFICATION OF CONCURRENT ENGINEERING SOFTWARE USING CSM MODELS

An engineering design process may involve software modules that can executed concurrently. Concurrent modules can be very easily subject to some synchronization errors. This paper discusses verification process for such engineering software. We present a method for verification that requires several steps. First, the state diagram models are constructed that describe the design iterations and interactions with the designer. Next, the state diagram models are transformed into concurrent state machines (CSM). After that, the CSM models are analyzed in order to verify their correctness. In this phase, the modifications are performed in necessary. In the last phase the code is generated. The tools to support our method can be called new concurrent CASE tools. Using these tools the engineering software can be created that is verified for correctness in respect to concurrent execution.
Effects of major and minor modes to emotional perceptions of ‘happy’ and ‘sad’ in piano music among students aged 9 – 17 / Nurezlin Mohd Azib

This quantitative study investigates the effects of major and minor modes, and contributing musical parameter of tempo, to the emotional perceptions of ‘happy’ and ‘sad’ in piano music among subjects aged 9-17 years old. Study was conducted in two phases; survey-questionnaire, and listening activity. Subjects (N=31) were sampled from piano music students’ population in Bangi, Selangor. In the survey-questionnaire, subjects answered 20 questions on demographic characteristics, music listening and preference, and understanding of emotional perception in music. In the listening activity, subjects listened to 20 untitled piano music excerpts and rated the emotion perceived for each excerpt, whether ‘happy’ or ‘sad’. Results from survey-questionnaire show that most percentage of subjects are 11 years old, in Grade 1, of 3 years of learning piano, prefer classical music, always listen to music, prefer both major and minor modes’ music, and find it easy to understand emotion in music, as well as major and minor modes. Results from listening activity show that 60 % of major mode music are perceived as ‘majorhappy’, while 60 % too, of minor mode music are perceived as ‘minor-sad’. However, Chi-square test of independence statistical analysis indicates that there are no association and significant relationship between modes (major and minor) and ‘happy’, as well as ‘sad’ perceptions (2 (1, N = 20) = 0.80, p = 0.371), at the significance level of p ≤ 0.05. Contrastingly, there are association and significant relationship between tempo (fast and slow), and ‘happy’, as well as ‘sad’ perceptions (2 (1, N = 20) = 9.899, p = 0.005). Therefore, it is concluded that tempo plays an important role in effects of major and minor mode to ‘happy’ and ‘sad’ emotional perceptions in piano music among subjects aged 9 to 17 in this study.
Performance Evaluation of AODV & DSR with Varying Pause Time & Speed Time Over TCP & CBR Connections in VANET

VANET (Vehicular Ad-hoc Network) is a new technology which has taken enormous attention in the recent years. Vehicular ad hoc network is formed by cars which are called nodes; allow them to communicate with one another without using any fixed road side unit. It has some unique characteristics which make it different from other ad hoc network as well as difficult to define any exact mobility model and routing protocols because of their high mobility and changing mobility pattern. Hence performance of routing protocols can vary with the various parameters such as speed, pause time, node density and traffic scenarios. In this research paper, the performance of two on-demand routing protocols AODV&DSR has been analyzed by means of packet delivery ratio, loss packet ratio&average end-to-end delay with varying pause time, speed time and node density under TCP&CBR connection.
MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

We present an unsupervised learning algorithm that acquires a natural-language lexicon from raw speech. The algorithm is based on the optimal encoding of symbol sequences in an MDL framework, and uses a hierarchical representation of language that overcomes many of the problems that have stymied previous grammar-induction procedures. The forward mapping from symbol sequences to the speech stream is modeled using features based on articulatory gestures. We present results on the acquisition of lexicons and language models from raw speech, text, and phonetic transcripts, and demonstrate that our algorithm compares very favorably to other reported results with respect to segmentation performance and statistical e ciency. Copyright c Massachusetts Institute of Technology, 1995 This report describes research done at the Arti cial Intelligence Laboratory of the Massachusetts Institute of Technology. This research is supported by NSF grant 9217041-ASC and ARPA under the HPCC and AASERT programs.
Mortality From Thoracic Aortic Diseases and Associations With Cardiovascular Risk Factors

Background— Temporal trends in mortality from thoracic aortic disease are unclear. This study examined trends in mortality from thoracic aortic aneurysm (TAA) and aortic dissection (AD) with the aim of identifying associations with trends in established cardiovascular risk factors. Methods and Results— TAA and AD mortality (1994–2010) using International Classification of Diseases codes was extracted from the World Health Organization mortality database and age standardized. World Health Organization InfoBase and International Mortality and Smoking Statistics provided risk factor data. Eighteen World Health Organization member states were included (Europe=13, Australasia=2, North America=2, Asia=1). Ecological regression was performed of temporal trends in cardiovascular risk factors (1946–2010) and independent correlations to mortality trends. TAA and AD mortality trends show substantial heterogeneity but are generally declining. TAA mortality has increased in Hungary, Romania, Japan, and Denmark, and AD mortality has increased in Romania and Japan; therefore, the mortality decline is not universal. A linear relationship exists between trends in systolic blood pressure, cholesterol, and body mass index and mortality from TAA. Body mass index demonstrated a negative linear association with female AD mortality, whereas trends in systolic blood pressure demonstrated a positive linear relationship with male AD mortality. Trends in smoking prevalence were not associated with TAA or AD mortality trends. Conclusions— This population-level ecological regression provides evidence that mortality secondary to TAA and mortality secondary to AD are both in decline. Differences between countries could be explained by population-level changes in common cardiovascular risk factors. Public health measures could further reduce mortality from TAA and AD.