Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Labeling of Talker Identity Using Short Speech Segments in a Microphone-Array Environment

The problem addressed is generally in the family of speaker verification, but its conditions and requirement s are very different from what has been published in this area. We want to label approximately five to ten moving talkers in the reverberant and noisy focal area of a large-aperture microphone array, in real time, from short segments of conversational audio. Current real-time systems use only spatial informat ion, which is inadequate when talkers move while silent. Given th e dynamic noise conditions in this kind of environment, it is very difficult to collect sufficient training data for a conventional algorithm. The proposed algorithm is easily implementablein real time and is trained offline using only noise-free data. This is possible because a set of robust features is used that represent the differences between a pair of speech segments . Also, the output of the algorithm is a probability, rather th an a measure requiring threshold tuning, which makes on-the-fly decisions straightforward. The algorithm is introduced and its properties are demonstrated. While quite simple, the algor ithm has been shown to outperform some commonly-used talkerdistance metrics for real data taken from a noisy-environment, array system. This microphone-array dataset is available t o other researchers at www.lems. brown.edu/array/data/movingta lkers/. EDICS Categories: SPE-SPKR, AUD-LMAP
Measuring Semantic Relatedness Across Languages

Measures of Semantic Relatedness are well established in Natural Language Processing. Their purpose is to determine the degree of relatedness between two words without specifying the nature of their relationship. Most of these measures work only between pairs of words in a single language. We propose a novel method of measuring semantic relatedness between pairs of words in two different languages. This method does not use a parallel corpus but is rather seeded with a set of known translations. For evaluation we construct a data set of cross-language word pairs with similarity scores from French and English versions of Rubenstein & Goodenough’s data set. We found that our new cross-language measure correlates more closely with averaged human scores than our unilingual baselines.
3 HGPF in Tissue Subsurface Scattering : Chronology and Problems

Despite the significant advances in rendering, we are far from being able to automatically generate realistic and predictable images of organic materials such as plant and human tissues. Creating convincing pictures of these materials is usually accomplished by carefully adjusting rendering parameters. A key issue in this context is the simulation of subsurface scattering. Current algorithmic models usually rely on scattering approximations based on the use of phase functions, notably the Henyey-Greenstein phase function and its variations, which were not derived from biophysical principles of any organic material, and whose parameters have no biological meaning. In this report, we challenge the validity of this approach for organic materials. Initially, we present an original chronology of the use of these phase functions in tissue optics simulations, which highlights the pitfalls of this approach. We then demonstrate that a significant step toward predictive subsurface scattering simulations can be given by replacing it by a more efficient and accurate data oriented approach. Our investigation is supported by comparisons involving the original measured data that motivated the application of phase functions in tissue subsurface scattering simulations. We hope that the results of our investigation will help strengthen the biophysical basis required for the predictive rendering of organic materials.
Hybrid decoding of irregular LDPC codes

Time-invariant hybrid (HTI) decoding of irregular low-density parity-check (LDPC) codes is studied. Focusing on HTI algorithms with majority-based (MB) binary message-passing constituents, we use density evolution and finite-length simulation to analyze the performance and the convergence properties of these algorithms. Tight upper bounds on the threshold of MB HTI algorithms are derived, and it is proven that the asymptotic error probability for these algorithms tends to zero at least exponentially with the number of iterations. We devise optimal MB HTI algorithms for irregular LDPC codes, and show that these algorithms outperform Gallager's algorithm A applied to optimized irregular LDPC codes. We also show that compared to switch-type algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different MB algorithms, MB HTI algorithms are more robust, and can better cope with unknown channel conditions, and thus can be practically more attractive
Do campaign spending limits diminish competition? An experiment

This paper experimentally investigates the effect of limits on campaign expenditure and outcome in an electoral contest where two candidates, an incumbent and a challenger, compete for office in terms of the amount of campaign expenditure. The candidates are asymmetric only in that the incumbent wins the contest in case of a tie. Theory predicts that in the presence of such asymmetry spending limits put the challenger at a disadvantage and tightening the limits leads to further entrenchment of the incumbent. The experimental results confirmed the theoretical predictions.
Non-supervised technique to adapt spatial filters for ECoG data analysis

Electrical Brain signals can be used for developing non-muscular communication and control systems, Brain-Computer Interfaces (BCIs) for people with motor disabilities. The performance of a BCI relies on the measured components of the brain activity, and on the feature extraction achieved by the spatial and temporal filtering methods applied prior to its translation into commands. In the present study we proposed a non-supervised technique based on the steepest descent method with a minimization cost function given by the variance on differences of the linear combination of the electrodes in order to adapt filter's coefficients to the most appropriate spatial filter. Results of applying this technique to electrocorticographic (ECoG) signals of five subjects performing finger flexion task are shown. Adapted filters were compared with Common Average Reference Filter (CAR) when mean square error (MSE) between channels significantly correlated and the power of filtered data was computed; results proved that adapted filters have better performance. Paired t-test was conducted to prove that results from CAR and the proposed technique are significantly different.
Bit loading-based irregular LDPC coded-modulation for high-speed optical communications

In state-of-the-art fibre-optics communication systems, the forward error correction (FEC) and high-order constellation formats are employed. It is important to approach the Shannon limit by using turbo product codes (TPC) and low-density parity-check (LDPC) codes with soft-decision decoding (SDD) algorithms. In this paper, we first study the rate-adaptive irregular LDPC coding technique in wide range of code rates enabling the flexible adjustment according to channel conditions and the simulation results show an improved SNR gain of 0.15 ~ 0.44 dB compared with regular LDPC codes under BPSK transmission. Then we propose a bit-loading rule for irregular LDPC codes combined with 16QAM and demonstrate additional 0.3 dB SNR improvements in low code rate regime, making it a viable solution for next generation high-speed optical communication systems.
Implementing concurrent object-oriented languages on multicomputers

The implementations of ABCL (an object-based concurrent language) on two different types of multicomputers-Electrotechnical Laboratories' EM-4 extended dataflow computer, and Fujitsu's experimental AP1000-are described. ABCL/EM-4 takes advantage of that machine's packet-driven architecture to achieve very good preliminary performance results. The AP1000 does not have special hardware support for message passing, so ABCL/AP1000 includes several software technologies that are general enough for conventional parallel or concurrent languages, again yielding promising performance. It is concluded that the results demonstrate the viability of attaining good performance with concurrent object-oriented languages on current multicomputers, whether experimental or commercial. <<ETX>>
Estimating Betas and Stock-Return Correlations From Monthly Data: A Warning Note

The empirical finance literature makes extensive use of 'monthly' stock returns, where a monthly return is the change in stock price between one particular day of the calendar month - which we term the reference day - and the corresponding day of the following month. We show that estimates of betas and stock-market correlations are highly sensitive to the choice of reference day and we suggest that studies based on such estimates can be unreliable. We support this claim by carrying out two small-scale empirical studies showing in each case that the results of critical tests are dependent upon the choice of reference day.
Time-Aware Exploratory Search: Exploring Word Meaning through Time

With more longitudinal archives becoming digitized and publicly available, new uses emerge. Collections that span centuries call for a time-aware exploration approach, a coordinated environment supporting understanding the development of word usage and meaning through time, with the means to leverage this for exploration. We present ongoing work on a coordinated time-aware exploratory search approach and present a case study on a prototype system. With this approach, a user is able to gain a deeper understanding of the relevant parts of the collection.
On the asymptotic spatial behaviour of the solutions of the nerve system

In this paper we investigate the asymptotic spatial behavior of the solutions for several models for the nerve fibers. First, our analysis deals with the coupling of two parabolic equations. We prove that, under suitable assumptions on the coefficients and the nonlinear function, the decay is similar to the one corresponding to the heat equation. A limit case of this system corresponds to the coupling of a parabolic equation with an ordinary differential equation. In this situation, we see that for suitable boundary conditions the solution ceases to exist for a finite value of the spatial variable. Next two sections correspond to the coupling of a hyperbolic/parabolic and hyperbolic/ordinary differential problems. For the first one we obtain that the decay is like an exponential of a second degree polynomial in the spatial variable. In the second one, we prove a similar behaviour to the one corresponding to the wave equation. In these two sections we use in a relevant way an exponentially weighted Poincare inequality which has been revealed very useful in several thermal and mechanical problems. This kind of results have relevance to understand the propagation of perturbations for nerve models.
Requirements for Service Architecture Modeling

The development of large and complex software intensive systems, among other issues, means various stakeholders related to software architecture modeling. Various stakeholders concern different aspects of software development, e.g. management, testing, component engineering or product marketing. Therefore, fluent communication between various stakeholders may become a difficult and confusing issue in software development. This paper introduces the requirements for service architecture modeling. The requirements include definitions of four viewpoints at two levels of abstraction. The rationale for two levels and four viewpoints required in service architecture modeling are introduced first. In addition, this paper also defines the viewpoints by means of concerns, stakeholders and artifacts. This paper also maps the service architecture description approach to the OMG’s model driven architecture approach. The service architecture modeling approach introduced here improves communication among different stakeholders and increases reusability of higher-level architecture descriptions.
On the Cell Coverage Area of Overlap Area-Based Cellular Model in Wireless Cellular Systems: Base Station Locations

Under wireless cellular system, the Cell Coverage Area (CCA) is the essential indicator for supporting customers. In this paper, an analysis of CCA concerned with location of base station and log-normal propagation are considered. The outage probability from numerical results with uniform traffic shows that the proper base station location can give optimum CCA.
International Journal of Advances in Electrical and Electronics Engineering

— With the easy availability of internet facility number of its user are increasing day by day. Most of the servers provide different type of services to users. But this leads to one problem which is related to user data security. So keeping this goal in mind server will get perturbed data then perform classification on that perturbed data. Once classification done then result send back to the user. Security is maintained at sender and receiver side, by using cryptosystem, where textual data is send to the server for classification. Results are compare with previous approach on different parameters, which shows that proposed work is efficient.
Enhancing multimedia processing by wave-pipelining integer units and floating point units in whole

A ubiquitous processor, HCgorilla followed Java CPU for multimedia processing and was built in RNG (random number generators) for cipher processing. Then, HCgorilla had an execution stage composed of several units for those sophisticated processing. Since the execution stage kept physical separation, each function took different latency. This required instruction scheduling similarly to regular super scalar processors. We describe, in this paper, the improvement of HCgorilla to solve this issue. Specifically, the execution stage composed of arithmetic units is wave-pipelined in whole. This completely merges the parallel structure without physical separation. The waved multifunctional execution unit is effective to realize wide-range dynamic ILP (instruction level parallelism) at a rate higher than regular superscalar processors.
Univariate Modelling Using Periodic and Non-Periodic Analysis: Inbound Tourism to Japan, Australia and New Zealand Compared

This paper examines three hypotheses using the time-series between 1978 and 1995 of quarterly tourist flows into Japan, Australia and New Zealand. First, whether periodic models can be used to successfully forecast tourism arrival series. Second, whether the Basic Structural Model (BSM) can forecast as accurately as the Box Jenkins (ARIMA) model. Third, whether the integrated seasonal univariate models forecast more accurately than the naive process. The paper concludes that the periodic model does not improve forecast accuracy. The BSM model performs at least as well as the ARIMA model, and the naive process is not a substitute for seasonal integrated models.
Flame-driven Deflagration-to-Detonation Transitions in Type Ia Supernovae?

Although delayed detonation models of thermonuclear explosions of white dwarfs seem promising for reproducing Type Ia supernovae, the transition of the flame propagation mode from subsonic deflagration to supersonic detonation remains hypothetical. A potential instant for this transition to occur is the onset of the distributed burning regime, i.e., the moment when turbulence first affects the internal flame structure. Some studies of the burning microphysics indicate that a deflagration-to-detonation transition may be possible here, provided the turbulent intensities are strong enough. Consequently, the magnitude of turbulent velocity fluctuations generated by the deflagration flame is analyzed at the onset of the distributed burning regime in several three-dimensional simulations of deflagrations in thermonuclear supernovae. It is shown that the corresponding probability density functions fall off toward high turbulent velocity fluctuations much more slowly than a Gaussian distribution. Thus, values claimed to be necessary for triggering a detonation are likely to be found in sufficiently large patches of the flame. Although the microphysical evolution of the burning is not followed and a successful deflagration-to-detonation transition cannot be guaranteed from simulations presented here, the results still indicate that such events may be possible in Type Ia supernova explosions.
Monitoring changes in daily actigraphy patterns of free-living patients

The current development of actigraphs integrated in small and discrete devices allows noninvasive recording of patient activity over several days or even months. The information obtained by these devices allows the analysis of daily activity patterns and therefore may be a use- ful tool to monitor the status of out-patients in diseases such as major depression. However, the full exploitation of this information requires automated systems that reduce the inherent complexity of these data and facilitate their interpretation by the clinicians. Thus in this paper a Daily Activity Monitoring System (DAMS) is presented based on func- tional data analysis algorithms for signal alignment and non-linear di- mensionality reduction techniques based on manifolds. The DAMS allows robust processing of actigraphy data, and visual detection of changes or anomalies in routine activity.
Inverted Pendulum Control over an IEEE 802.15.4 Wireless Sensor and Actuator Network

Recent research efforts are considering the problem of performing control of dynamical systems over wireless sensor and actuator networks. However, existing results lack an experimental evaluation in real platforms. In this demonstration an inverted pendulum system is controlled over an IEEE 802.15. 4 wireless sensor and actuator network. This platform can evaluate several sensor networks and control algorithms and is currently used as an educational tool at KTH Royal Institute of Technology, Sweden.
Time-Bounded Positive Influence in Social Networks

The appearance of social networks provides great opportunities for people to communicate, share and disseminate information. Meanwhile, it is quite challenge for utilizing a social networks efficiently in order to increase the commercial profit or alleviate social problems. One feasible solution is to select a subset of individuals that can positively influence the maximum other ones in the given social network, and some algorithms have been proposed to solve the optimal individual subset selection problem. However, most of the existing works ignored the constraint on time. They either assume that the time is infinite or only suitable to solve the snapshot selection problems. Obviously, both of them are impractical in the real system. Due to such reason, we study the problem of selecting the optimal individual subset to diffuse the positive influence when time is bounded. We proved that such a problem is NP-hard, and a heuristic algorithm based on greedy strategy is proposed. The experimental results on both simulation and real-world social networks based on the trace data in Shanghai show that our proposed algorithm outperforms the existing algorithms significantly, especially when the network structure is sparse.
Scale-Free Network in Stock Markets

We study the cross-correlations in stock price changes among the S&P 500 companies by introducing a weighted random graph, where all vertices (companies) are fully connected via weighted edges. The weight of each edge is distributed in the range of [−1, 1] and is given by the normalized covariance of the two modified returns connected, where the modified return means the return minus the mean over all companies. We define an influence-strength at each vertex as the sum of the weights on the edges incident upon that vertex. Then we find that the influence-strength distribution in its absolute magnitude |q| follows a power-law, P (|q|) ∼ |q|−δ, with exponent δ ≈ 1.8(1).
Mapping the meanings of Cultural Leadership: The use of the term in the field of arts management

Given the (necessarily open-ended) discussion about the function of arts and culture in society, it is not surprising that there is a similar tension in deciding on the definition and content of the term ‘cultural leadership’. Most literature on the term can be seen as firmly – and problematically – rooted in Anglo-Saxon and European traditions of though. But in contrast to academic attempts to put an end to this debate by looking for a unifying definition of the term (quite impossibly, for that matter), this issue stresses the context specificity of the notion of “Cultural Leadership”. It embraces the idea that Cultural Leadership always is about relations (between people, departments within institutions, institutions and society etc.) and that the meanings of the term are relational as well, i.e. context-specific. The contri- butions of this issue reflect this diversity of meanings and show that defin- ing Cultural Leadership is like a dramatic battle for discursive hegemony on one of our central terms.
Internet of Things: Key technology, architecture and challenging problems

The development and application of the Internet of Things (IOT) and one of the key technologies “RFID technology” are introduced in detail to gain a better understanding of the IOT technology. For the working principle and mechanism of the IOT can be understood and grasped more easily, an architecture model of the IOT is established combined with the EPC global standards, and the working model of three layer consist of the sensing-layer, network-layer, and application-layer are given. To further promote the practical application of this IOT architecture model, some pressing issues are pointed out, and the smart nodes optimization problem, the information security issues and the data processing problem are emphasized, etc. The final conclusion provides some suggestions for the development of the IOT.