Miracle-dz/UniFAR-FTUs huggingface dataset:
Smoothed N-best-based speaker adaptation for speech recognition

Smoothed estimation and utterance verification are introduced into the N-best-based speaker adaptation method. That method is effective even for speakers whose decodings using speaker-independent (SI) models are error-prone, that is, for speakers for whom adaptation techniques are truly needed. The smoothed estimation improves the performance for such speakers, and the utterance verification reduces the required amount of calculation. Performance evaluation using connected-digit (four-digit strings) recognition experiments performed over actual telephone lines showed a reduction of 36.4% in the error rates for speakers whose decodings using SI models are error-prone. To try and find an effective model-transformation for speaker adaptation, we discuss replacing mixture-mean bias estimation by the widely used mixture-mean linear-regression-matrix estimation.
Generation of interval‐valued fuzzy and atanassov's intuitionistic fuzzy connectives from fuzzy connectives and from Kα operators: Laws for conjunctions and disjunctions, amplitude

In this paper, we study in‐depth certain properties of interval‐valued fuzzy sets and Atanassov's intuitionistic fuzzy sets (A‐IFSs). In particular, we study the manner in which to construct different interval‐valued fuzzy connectives (or Atanassov's intuitionistic fuzzy connectives) starting from an operator. We further study the law of contradiction and the law of excluded middle for these sets. Furthermore, we analyze the following properties: idempotency, absorption, and distributiveness. We conclude relating idempotency with the capacity that some of the connectives studied have for maintaining, in certain conditions, the amplitude (or Atanassov's intuitionistic index) of the intervals on which they act. © 2008 Wiley Periodicals, Inc.
Differential Expression of miRNAs in Brassica napus Root following Infection with Plasmodiophora brassicae

Canola (oilseed rape, Brassica napus L.) is susceptible to infection by the biotrophic protist Plasmodiophora brassicae, the causal agent of clubroot. To understand the roles of microRNAs (miRNAs) during the post-transcriptional regulation of disease initiation and progression, we have characterized the changes in miRNA expression profiles in canola roots during clubroot disease development and have compared these to uninfected roots. Two different stages of clubroot development were targeted in this miRNA profiling study: an early time of 10-dpi for disease initiation and a later 20-dpi, by which time the pathogen had colonized the roots (as evident by visible gall formation and histological observations). P. brassicae responsive miRNAs were identified and validated by qRT-PCR of miRNAs and the subsequent validation of the target mRNAs through starBase degradome analysis, and through 5′ RLM-RACE. This study identifies putative miRNA-regulated genes with roles during clubroot disease initiation and development. Putative target genes identified in this study included: transcription factors (TFs), hormone-related genes, as well as genes associated with plant stress response regulation such as cytokinin, auxin/ethylene response elements. The results of our study may assist in elucidating the role of miRNAs in post-transcriptional regulation of target genes during disease development and may contribute to the development of strategies to engineer durable resistance to this important phytopathogen.
Grand Unification and Time Variation of the Gauge Couplings

Astrophysical indications that the fine structure constant is time dependent are discussed in the framework of grand unification models. A variation of the electromagnetic coupling constant could either be generated by a corresponding time variation of the unified coupling constant or by a time variation of the unification scale, or by both. The case in which the time variation of the electromagnetic coupling constant is caused by a time variation of the unification scale is of special interest. It is supported in addition by recent hints towards a time change of the proton-electron mass ratio. Possible implications for baryogenesis are discussed. The study of a possible time variation of the fundamental parameters like for example the fine structure constant, has a long history that can be traced back to Dirac [1]. Some extensions of the standard model of particle physics and in particular models that couple gravity to the standard model, e.g. quintessence [2], require or at least allow a time dependence of the parameters of the model. Our motivation to study the implications of a time dependence of the fundamental parameters for particle physics is not that much of a theoretical origin but rather because there are indications [3, 4, 5, 6, 7, 8] coming from different astrophysical measurements that the parameters of the standard model could be time dependent. We shall consider the implications of Webb et al.’s result which indicate a possible time dependence of "
Optimal separations between concurrent-write parallel machines

We obtain tight bounds on the relative powers of the Priority and Common models of parallel random-access machines (PRAMs). Specifically we prove that:<list><item>The Element Distinctness function of <italic>n</italic> integers, though solvable in constant time on a Priority PRAM with <italic>n</italic> processors, requires &OHgr;(<italic>A</italic>(<italic>n,p</italic>)) time to solve on a Common PRAM with <italic>p</italic> ≥ <italic>n</italic> processors, where <italic>A</italic>(<italic>n</italic>,<italic>p</italic>) = <italic>n</italic> log <italic>n</italic>/<italic>p</italic> log (<italic>n</italic>/<italic>p</italic> log <italic>n</italic> + 1). </item><item>One step of a Priority PRAM with <italic>n</italic> processors can be simulated on a Common PRAM with <italic>p</italic> processors in <italic>&Ogr;</italic>(<italic>A</italic>(<italic>n</italic>,<italic>p</italic>)) steps. </item></list> As an example, the results show that the time separation between Priority and Common PRAMs each with <italic>n</italic> processors is &THgr;(log <italic>n</italic>/log log <italic>n</italic>).
Pruning algorithm for Multi-objective optimization

Because of non-existence of an ideal single solution in Multi-objective optimization frameworks, the set of optimal solutions is required to be well spread and uniformly covering wide area of Pareto front. The decision maker (DM) still work hard to compromise the trade-offs solutions based on his/her preferences. In this paper, we proposed a pruning algorithm that can filter out undesired solutions and provides more robust trade-offs solutions to the DM. Our algorithm is called adaptive angle based pruning algorithm with bias intensity tuning (ADA). The pruning rationale is increasing the dominated area for the purpose of removing solutions that only marginally improves in some objectives while being significantly worse in other objectives. The extra angles are expanded from the regular dominated area. The bias intensity parameter (W) is introduced in order to approximate the portions of desirable solutions based on DM's opinions. We chose several benchmark problems with different difficulties including two and three objectives problems. The experimental result has shown that our pruning algorithm provides robust sub-set of Pareto-optimal solutions on several benchmark problems. The pruned Pareto-optimal solutions distributed and covered multiple regions instead of single region of Pareto front. In addition, it's clearly shown in bi-objective problems that the pruned Pareto-optimal solutions are located at knee regions of the Pareto front.
Attribution Mechanisms for Ancillary Service Costs Induced by Variability in Power Delivery

The increased penetration of renewable energy sources in existing power systems has led to necessary developments in electricity market mechanisms. Most importantly, renewable energy generation is increasingly made accountable for deviations between scheduled and actual energy generation. However, there is no mechanism to enforce accountability for the additional costs induced by power fluctuations. These costs are socialized and eventually supported by electricity customers. We propose some metrics for assessing the contribution of all market participants to power regulation needs, as well as an attribution mechanism for fairly redistributing related power regulation costs. We discuss the effect of various metrics used by the attribution mechanisms, and we illustrate, in a game-theoretical framework, their consequences on the strategic behavior of market participants. We also illustrate, by using the case of Western Denmark, how these mechanisms may affect revenues of the various market participants.
Comparison of Velocity and Gravity Fields: The Mark III Tully-Fisher Catalog versus the IRAS 1.2 Jy Survey

We consider a measure of the peculiar velocity field derived from the Mark III compilation of 2900 spiral galaxies (Willick et al.), using an analysis method that is substantially free of bias (Nusser & Davis). We expand the velocity field in a set of orthogonal, smooth modes, reducing the data to a set of 56 coefficients fitted to a maximum redshift of 6000 km s–1, and maximum spherical harmonic of l = 3. The radial resolution of the modes degrades with redshift, from 800 km s–1 locally to 3000 km s–1 at 4000 km s–1 redshift. Equivalent mode coefficients can be computed for the gravity field derived from any whole-sky redshift catalog of galaxies, such as the IRAS 1.2 Jy survey (Fisher et al.). Given the coefficients of the expansions, one can compare the velocity and gravity fields on a galaxy-by-galaxy basis, or on a mode-by-mode basis. Detailed comparison shows the two independent fields to be remarkably aligned in general. There are, however, systematic discrepancies in the fields that lead to considerable coherence in the residuals between them. These residuals take the form of a dipole field in the Local Group (LG) frame that grows with distance; it is not consistent with a bulk flow residual. We perform a likelihood analysis in the mode-mode comparison to determine which value of β≡ Ω0.6/b for the IRAS gravity field is the best fit to the Mark III velocity field, considering the errors and covariance in both the velocity and gravity coefficients. We find that the most likely value lies in the range β = 0.4-0.6. However, in contrast with results we obtain using simulated galaxy catalogs, the x2 per degree of freedom for the fit is well in excess of unity, primarily because of the coherent dipole residuals at cz ≲ 3000 km s–1. Thus, despite the general alignment of the Mark III velocity and IRAS gravity fields, they do not agree in detail, precluding a firm determination of β from these data sets at present. The method is capable of measuring β to an accuracy of 10%, but without understanding these systematic discrepancies, we cannot infer a value of β from these data.
Context management for user-centric context-aware services over pervasive networks

Large and various amounts of context data related to a user's environment are available from different domains including mobile devices, smarthomes, wearable sensors, and social networking services. These context domains are interconnected and the context data from them can be shared thanks to mobile, pervasive, convergent, and ubiquitous technologies. We can provide user-centric context-aware services by aggregating and associating the diverse types of context data distributed over multiple domains around a user. However, state-of-the-art research efforts have been devoted to managing context only in a single domain. In this paper, for user-centric context management, we propose 1) a flexible and extensible technology-neutral information model that can represent generic concepts of context; 2) a hierarchical context management architecture that can understand and manage complex interactions among multiple contextual entities.
Microbial Adhesion and Biofilm Formation on Microfiltration Membranes: A Detailed Characterization Using Model Organisms with Increasing Complexity

Since many years, membrane biofouling has been described as the Achilles heel of membrane fouling. In the present study, an ecological assay was performed using model systems with increasing complexity: a monospecies assay using Pseudomonas aeruginosa or Escherichia coli separately, a duospecies assay using both microorganisms, and a multispecies assay using activated sludge with or without spiked P. aeruginosa. The microbial adhesion and biofilm formation were evaluated in terms of bacterial cell densities, species richness, and bacterial community composition on polyvinyldifluoride, polyethylene, and polysulfone membranes. The data show that biofouling formation was strongly influenced by the kind of microorganism, the interactions between the organisms, and the changes in environmental conditions whereas the membrane effect was less important. The findings obtained in this study suggest that more knowledge in species composition and microbial interactions is needed in order to understand the complex biofouling process. This is the first report describing the microbial interactions with a membrane during the biofouling development.
D-branes and orientifolds of SO(3)

We study branes and orientifolds on the group manifold of SO(3). We consider particularly the case of the equatorial branes, which are projective planes. We show that a Dirac-Born-Infeld action can be defined on them, although they are not orientable. We find that there are two orientifold projections with the same spacetime action, which differ by their action on equatorial branes.
SPAM : Signal Processing to Analyze

CYBER attacks have risen in recent times. The attack on Sony Pictures by hackers, allegedly from North Korea, has caught worldwide attention. The President of the United States of America issued a statement and “vowed a US response after North Korea’s alleged cyber-attack” [1]. This dangerous malware termed “wiper” could overwrite data and stop important execution processes. An analysis by the FBI showed distinct similarities between this attack and the code used to attack South Korea in 2013, thus confirming that hackers re-use code from already existing malware to create new variants. This attack along with other recently discovered attacks such as Regin, Opcleaver give one clear message: current cyber security defense mechanisms are not sufficient enough to thwart these sophisticated attacks. Today’s defense mechanisms such as commercial Antivirus software are based on scanning systems for suspicious or malicious activity. If such an activity is found, the files under suspect are either quarantined or the vulnerable system is patched with an update. In turn, the Antivirus software are also updated with new signatures to identify such activities in future. The scanning methods are based on a variety of techniques such as static analysis, dynamic analysis and other heuristics based techniques, which are often slow to react to new attacks and threats. Static analysis is based on analyzing an executable without executing it. These techniques include searching for specific strings, computing cryptographic hashes and disassembling the executable to extract features. On the other hand, dynamic analysis executes the binary and studies its behavioral characteristics in a virtual sandboxed environment. Some of the methods include system-call level monitoring and memory snapshot comparison. Hackers are familiar with these standard methods and come up with ways to evade the current defense mechanisms. They produce new malware variants that easily evade the detection methods. These variants are created from existing malware using inexpensive easily available “factory toolkits” in a “virtual factory” like setting, which then spread over and infect more systems. Once a system is compromised, it either quickly looses control and/or the infection spreads to other networked systems. While security techniques constantly evolve to keep up with new attacks, hackers too change their ways and continue to evade defense mechanisms. As this never-ending billion dollar “cat and mouse game” continues, it may be useful to look at avenues that can bring in novel alternative and/or orthogonal defense approaches to counter the ongoing threats. The hope is to catch these new attacks using complementary methods which may not be well known to hackers, thus making it more difficult and/or expensive for them to evade all detection schemes. This paper focuses on such orthogonal approaches from Signal and Image Processing that complement standard approaches. MALWARE
LETTER TO THE EDITOR: Large- N eigenvalue distribution of randomly perturbed asymmetric matrices

The density of complex eigenvalues of random asymmetric matrices is found in the large-N limit. The matrices are of the form where A is a matrix of independent, identically distributed random variables with zero mean and variance . The limiting density is bounded. The area of the support of cannot be less than . In the case of commuting with its conjugate, is expressed in terms of the eigenvalue distribution of the non-perturbed part .
The Role of Attitudes, Family, Peer and School on Alcohol Use, Rule Breaking and Aggressive Behavior in Hispanic Delinquent Adolescents.

OBJECTIVE: The purpose of this study was to examine ecodevelopmental risk factors associated with alcohol uses, rule breaking and aggressive behaviors among Hispanic delinquent adolescents. Specifically, this study tests the effect of attitudes, family, peer, and school bonding on alcohol use, rule breaking and aggressive behaviors in Hispanic delinquent youth. METHODS: A sample of 235 heterogeneous Hispanic delinquent adolescents was recruited through referrals from the Miami-Dade County's Department of Juvenile Services and from the Miami-Dade County Public School system. Logistic regression methods were utilized to examine the independent effect of each risk factor (attitudes, family, peer, school) and to determine the extent to which these factors are associated with alcohol use, rule breaking and aggressive behaviors. RESULTS: Family functioning was inversely and significantly related to past 90-day alcohol use in univariate regression (β = -.24, p = .035) but was not significant in multiple regression (β = -0.09, p = .556). Peer alcohol use (β = 2.02, p<0.001) and poor alcohol attitudes (β =0.59, p=0.006) were positively and significantly related to past 90-day alcohol use in the final model. Poor alcohol attitudes, family functioning, peer alcohol use, and school bonding were all significantly related to both rule breaking and aggressive behaviors in the final model. CONCLUSIONS: Findings highlight the importance of identifying risk factors at multiple levels to prevent/reduce alcohol use, rule breaking and aggressive behaviors among Hispanic delinquent youth.
Online programming exercises for summative assessment in university courses

Although interactive e-learning environments are increasingly used in university courses, traditional types of examination still dominate the way how students are assessed for grades. In this paper, we examined how student data from online interactive learning environment for programming exercises can be used for summative assessment at the end of the course. Using data from three different university courses, we calibrated the two parameter logistic regression model, ranked students according to their ability of solving problems, and matched them to final grades. Results indicate we can predict grades within 0.57 to 1.02 level of accuracy, suggesting that careful use of interactive e-learning environments in university courses can substitute existing assessment methods, opening further possibilities for innovation in instructional process.
Retweets as a Predictor of Relationships among Users on Social Media

Link prediction is the problem of detecting missing links or predicting future link formation in a network. Application of link prediction to social media, such as Twitter and Facebook, is useful both for developing novel services and for sociological analyses. While most existing research on link prediction uses only the social network topology for the prediction, in social media, records of user activities such as posting, replying, and reposting are available. These records are expected to reflect user interest, and so incorporating them should improve link prediction. However, research into link prediction using the records of user activities is still in its infancy, and the effectiveness of such records for link prediction has not been fully explored. In this study, we focus in particular on records of reposting as a promising source that could be useful for link prediction, and investigate their effectiveness for link prediction on the popular social media platform Twitter. Our results show that (1) the prediction accuracy of techniques using reposting records is higher than that of popular topology-based techniques such as common neighbors and resource allocation for actively retweeting users, (2) the accuracy of link prediction techniques that use network topology alone can be improved by incorporating reposting records.
Virtual reality for palmtop computers

We are exploring how virtual reahty theories can be applied toward palmtop computers. In our prototype, called the Chameleon, a small 4-inch hand-held monitor acts as a palmtop computer with the capabihties of a Silicon graphics workstation. A 6D input device and a response button are attached to tbe small monitor to detect user gestures and input selections for issuing commands. An experiment was conducted to evaluate our design and to see how well depth could be perceived in the small screen compared to a large 21-inch screen, and the extent to which movement of the small display (in a palmtop virtual reality condition) could improve depth perception, Results show that with very little training, perception of depth in the palmtop virtual reality condition is about as good as corresponding depth perception in a large (but static) display. Variations to the initial design are also discussed, along with issues to be explored in future research, Our research suggests that palmtop virtual reality may support effective navigation and search and retrieval, in rich and portable information spaces.
Accelerating CORDIC for hough transform

CORDIC, a hardware efficient algorithm, is commonly employed to implement the linear Hough transform (HT) for detecting straight lines in images. In this paper, we exploit the properties of the CORDIC algorithm to accelerate the HT computations. Unlike the conventional approaches, where CORDIC is used for computing HT for a given set of angles, the proposed method uses CORDIC to define the angle set based on the required resolution. It is shown that with minimum number of iterations, the desired accuracy can be obtained and adjusted by just varying the register lengths. The proposed method is shown to provide 6× speed up without any additional hardware when compared with existing CORDIC based HT computation methods with 9× lesser number of computations.
Miniboosting Decision Trees

Boosting, introduced by Freund and Schapire, is a method for generating an ensemble of classiiers by successive reweightings of the training cases. We study boosting in the context of small ensembles of decision trees, showing that the reweighting procedure can be improved and that the resulting ensemble can be represented by a single decision tree. This tree is large, attesting to the complexity of boosted classiiers, but simpliications that do not aaect its performance on the training data destroy the beneets of boosting.