Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved tone modeling for Mandarin broadcast news speech recognition

Tone has a crucial role in Mandarin speech in distinguishing ambiguous words. Most state-of-the-art Mandarin automatic speech recognition systems adopt embedded tone modeling, where tonal acoustic units are used and F0 features are appended to the spectral feature vector. In this paper, we combine the embedded aproach (using improved F0 smoothing) with explicit tone modeling in rescoring the output lattices. Oracle experiments indicate 32% relative improvement can be achieved by rescoring with perfect tone information. Recognition experiments on Mandarin broadcast news show that, even with an accuracy of only 70%, the explicit tone classifier offers complementary knowledge and improves performance significantly. Through the combination of tone modeling techniques, the character error rate on the CTV test set can be improved from 13.0% to 11.5%.
Checking Consistency between UML Class and State Models Based on CSP and B

The B Abstract Machine Notation (AMN) and the notation of Commu- nicating Sequential Processes (CSP) have previously been applied to formalise the UML class and state diagrams, respectively. This paper discusses their integrated use in checking the consistency between the two kinds of UML diagrams based on some recent results of research in integrated formal methods. Through a small information system example, the paper illustrates a clear-cut separation of concerns in employing the two formal methods. Of particular interest is the treatment of recursive calls within a single class of objects.
Performance evaluation of MySQL, Cassandra and HBase for heavy write operation

NoSQL databases have gained prominence in recent years because of their ability to scale easily and provide support for large amount of structured as well as unstructured data. User applications that need to perform heavy write operations have started making a paradigm shift to NoSQL databases with the overall intention to enhance performance. Eventually, various types of NoSQL databases have come up that have several features that suit different user specific needs. In this paper, the authors evaluate the performance of MySQL, Cassandra and HBase for heavy write operations by a Web based REST application.
A Trust Model Considering the Aspects of Time

Today, many trust models do exist which are based on bayesian systems, discrete values or the probability theory. Some of them are generic while others are specifically designed for certain applications such as p2p or ecommerce. What all these models have in common is the intention to map the human understanding of trust in a computational model. Some aspects of trust such as the direct trust towards another member or the reputation of said member have already been considered by fellow researchers while aspects such as sympathy or gut feeling will probably never be sufficiently integrated. The aspect, that experiences may age or be forgotten are currently incorporated in only few models. However, to our understanding the current approaches to aging are not satisfactory. We will point out the weak spot of the current aging approaches and present a refined version including the not yet discussed aspect of inactivity. Our proposed trust model incorporates this new approach, including methods on how to handle temporarily inactive members as well as the context-dependent computation of trust and reputation resulting in the valuation of a member's trustworthiness. Due to the generic approach, our proposed trust model can both be used for centralized and decentralized applications.
REPRESENTATION THEORY OF THE STABILIZER SUBGROUP OF THE POINT AT INFINITY IN Diff(S1)

The group Diff(S1) of the orientation-preserving diffeomorphisms of the circle S1 plays an important role in conformal field theory. We consider a subgroup B0 of Diff(S1) whose elements stabilize "the point at infinity. " This subgroup is of interest for the actual physical theory that lives on the punctured circle, or the real line. We investigate the unique central extension $\mathcal{K}$ of the Lie algebra of that group. We determine the first and second cohomologies, its ideal structure and the automorphism group. We define a generalization of Verma modules and determine when these representations are irreducible. Its endomorphism semigroup is investigated and some unitary representations of the group which do not extend to Diff(S1) are constructed.
The Quest for Wireless Gigabit: Recent Advances in the Wireless Physical Layer

A number of recent advances in the physical layer are enabling wireless communications devices to reach ever-greater speeds. These developments in modulation techniques, coding, and radio architecture enable better spectrum allocation, more power-efficient, error-resistant transmissions, and more flexible architectures for receiving signals. Many of the advances are being included in upcoming standards, like 802.16 and 802.11n, and will likely improve the already-fast adoption of wireless networking equipment. See Also: A Review of Key Wireless Physical Layer Concepts | Wireless Networking: Issues and Trends
Research on stack-allocation based JVM garbage collection

In order to reduce the costs of Java virtual machine garbage collector, a stack-allocation based on garbage collection algorithm is proposed in this paper. The stack frame is improved to support the object storage, and the stackable objects are identified with expanded byte code when the compiler compiles the Java source code. The stackable objects are allocated to Java stack and released instantly when they leave their scope, and the other objects are still allocated to heap and released by garbage collector. Experimental result shows, compared to traditional garbage collector, that new algorithm improves the performance of memory allocating and releasing, reduces the burden of garbage collector, and runs faster.
Pain following Craniotomy: Reassessment of the Available Options

Pain following craniotomy has frequently been neglected because of the notion that postcraniotomy patients do not experience severe pain. However a gradual change in this outlook is observed because of increased sensitivity of neuroanaesthesiologists and neurosurgeons toward acute postcraniotomy pain. Multiple modalities exist for treating this variety of pain each with its own share of advantages and disadvantages. However, individually none of these modalities has been proclaimed as the best and applicable universally. A considerable amount of dispute remains to ascertain the appropriate therapeutic regimen for treating postcraniotomy pain in spite of numerous trials using different drugs and their combinations. This review aims to highlight the genesis, characteristics, and different strategies that are undertaken for management of acute postcraniotomy pain. Chronic postcraniotomy pain which can be debilitating sequelae is also discussed concisely.
Profile Aggregation and Dissemination: A Framework for Personalized Service Provisioning

This paper presents a framework for aggregating, updating and disseminating user-related profiles where each part of the profile comes from a different source. A user-related profile, called a “Personalized Profile” in this study, consists not only of time and location, but also various kinds of activities in daily life. We also present personalized service scenarios based on this “Personalized Profile”.
Fetching instruction streams

Fetch performance is a very important factor because it effectively limits the overall processor performance. However there is little performance advantage in increasing front-end performance beyond what the back-end can consume. For each processor design, the target is to build the best possible fetch engine for the required performance level. A fetch engine will be better if it provides better performance, but also if it takes fewer resources, requires less chip area, or consumes less power. In this paper we propose a novel fetch architecture based on the execution of long streams of sequential instructions, taking maximum advantage of code layout optimizations. We describe our architecture in detail, and show that it requires less complexity and resources than other high performance fetch architectures like the trace cache, while providing a high fetch performance suitable for wide-issue superscalar processors. Our results show that using our fetch architecture and code layout optimizations obtains 10% higher performance than the EV8 fetch architecture, and 4% higher than the FTB architecture using state-of-the-art branch predictors, while being only 1.5% slower than the trace cache. Even in the absence of code layout optimizations, fetching instruction streams is still 10% faster than the EV8, and only 4% slower than the trace cache. Fetching instruction streams effectively exploits the special characteristics of layout optimized codes to provide a high fetch performance, close to that of a trace cache, but has a much lower cost and complexity, similar to that of a basic block architecture.
What a Country Must Do to Catch-Up to the Industrial Leaders

What, if anything, can a country today do to catch-up with the industrial leaders? This paper reviews a theory of the evoluti on of international income levels and examines its predictions for catch-up. The main pol icy implication of this theory is that a country will catch-up to the industrial leaders if it eliminates policies that constrain the choice of technologies and work practices of its ci tizenry. Most often these policies exist to protect specialized factor suppliers and corpora te interests. We examine the record of catch-up over the twentieth century and conclude th at joining a free trade club is an effective way by which a country can eliminate thes e constraints.
Approximation algorithms for submodular set cover with applications

The main problem considered is submodular set cover, the problem of minimizing a linear function under a nondecreasing submodular constraint, which generalizes both wellknown set cover and minimum matroid base problems. The problem is NP-hard, and two natural greedy heuristics are introduced along with analysis of their performance. As applications of these heuristics we consider various special cases of submodular set cover, including partial cover variants of set cover and vertex cover, and node-deletion problems for hereditary and matroidal properties. An approximation bound derived for each of them is either matching or generalizing the best existing bounds. key words: submodular function, set cover, approximation algorithms, greedy heuristics
GALOIS CONNECTIONS WITH HEDGES ∗

We introduce (fuzzy) Galois connections with hedges. Fuzzy Galois connections are basic structures behind so-called formal concept analysis of data with fuzzy attributes. Introducing hedges to Galois connections means introducing two parameters. The parameters influence the size of the set of all the fixpoints of a Galois connection. In the sense of formal concept analysis, the fixpoints, called formal concepts, are just the clusters extracted from data. The role of hedges is thus to control the number of extracted clusters. Stronger hedges lead to less clusters. We present definition, examples, and basic properties of Galois connections with hedges. In addition to that, we provide their axiomatization: Galois connections with hedges are exactly mappings induced by object-attribute data with fuzzy attributes. The effect of a parameterized reduction of the number of clusters from object-attribute data is demonstrated by examples.
An Examination of Socioeconomic Determinants of Average Body Mass Indices in Rwanda

Obesity is increasingly becoming a common problem in Africa. Many studies have been pre-occupied with analyzing the causes of malnutrition whose effects are more pronounced. The main objective of this research was to determine the socio-economic factors that influence body mass indices in Rwanda. Inflation rate, body mass indices (bmi) for males and females (from 1960 to 2009) and food supply indices were obtained mainly from the Food and Agriculture Organization (FAOSTAT). A double log multiple regression model was used to assess the relationship between average bmi and several predictor variables. Further tests of autocorrelation, multicollinearity, heteroscedasticity and normality were carried out and subsequently corrected. Results showed that obesity is not a problem in Rwanda. However, bmi for men and women have been increasing. Food self sufficiency, fat supply and food aid had a positive and significant impact on average bmi (p<0.05) while GDP per capita and inflation rate were insignificant. These results indicate the positive impact of efforts of government of Rwanda through Vision 2020. However, food aid may be contributing to rapid bmi increases in the country.
OPTIMIZATION OF A GA AND WITHIN A GA FOR A 2-DIMENSIONAL LAYOUT PROBLEM

A GA’s performance on a specific problem is related to many factors, such as genetic operators and corresponding parameter settings and the representation of the problem on the chromosome. Optimization of these factors to improve the speed and robustness of search is essential to successful application of a GA. The work reported here uses a two-level GA system (DAGA2) to solve a practical problem: the conceptual layout of machines on a factory floor (not the detailed design), based on a matrix of positive and negative relationships of various strengths between machines. This is a difficult, high-dimensionality problem. Performances of a traditional parallel GA system and our DAGA2 system are compared. The later one is compared with and without the use of several different representations for the problem at various times and in various subpopulations, demonstrating the strong contribution which the use of multiple representations makes to solution of the problem. The authors argue the necessity of optimizing many aspects of the GA in order to obtain useful solutions on such difficult, real problems.
Contextual Feature Analysis to Improve Link Prediction for Location Based Social Networks

In recent years, people started to communicate, interact, maintain relationship and share data (image, video, note, location, etc.) with their acquaintances through varying online social network sites. Online social networks with location and time sharing/interaction among people are called Location Based Social Networks (LBSNs). Link prediction in social networks aims at predicting future possible links for representing the real life relations better. In this work, we studied the link prediction problem and proposed new contextual features that improve the link prediction performance for LBSNs.
DRIVERS OF E-BUSINESS VALUE CREATION IN BANKING SECTOR IN JORDAN : A STRUCTURAL EQUATION MODELING APPLICATION

With the development and growth of internet, its applications of e-banking, e-commerce, and e-business became irreplaceable channels regarding its fast access, rich content, and smooth interactivity. High investments are paid toward improving the quality of service offered by the banks. This paper is dedicated to empirically investigating the drivers of e-Business value creation in the Jordanian banking sector. This work summarizes the main differences among employees of Jordanian and foreign bank regarding their perspectives. Many of the competing foreign banks to the Jordanian banks are enforced with huge financial capital, having long periods of banking practices and are employing cutting-edge technologies and tools. To minimize the technological gap, Jordanian banks are working hard to develop their e-Business services. This in one hand has to enhance their trust, satisfaction, and commitment toward existing customers and entice new comers on other hand. Based on business model of Amit and Zott, i.e. the four constructs of eValue framework (efficiency, complementarities, lock-in, and novelty), four hypotheses have been formulated to test the differences in the drivers of e-Business value creation between Jordanian and foreign banks. A survey questionnaire in a form of paper-and-pencil was delivered personally to 200 employees from four main Jordanian banks and 200 employees from four foreign banks working in Jordan. The questionnaire was formed and constructed to test the proposed hypotheses. the findings in this study based on the SEM and T-test analyses, revealed important implications that will help banks’ managers to make well-informed decisions and policies regarding investments and resources allocation for implementing eBusiness strategies and ventures. The paper concludes with discussing the importance of these findings for practitioners and for future research on value accrued from e-Business services.
Extraction of parametric circuit models from scattering parameters of passive RF components

We present a new algorithm for generating passive parametric models of microwave devices from their sampled scattering responses. The proposed formulation supports a parameterization of model poles and preserves the stability and passivity of the original device for any parameter value. These combined features lead to significant improvements with respect to the state of the art. Application examples show the effectiveness of the method in modeling multiport microwave devices.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1231 Sequence based analysis of neurodevelopmental disorders

Halvardson, J. 2016. Sequence based analysis of neurodevelopmental disorders. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1231. 62 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9597-8. In this thesis the main focus is the use of methods and applications of next generation sequencing in order to study three of the most common neurodevelopmental disorders: intellectual disability, epilepsy and schizophrenia. A large fraction of the genes in our genome produce several distinct transcript isoforms through the process of splicing and there is an increasing amount of evidence pinpointing mutations affecting splicing as a mechanism of disease. In Paper I we used exome capture of RNA in combination with sequencing in order to enrich for coding sequences. We show that this approach enables us to detect lowly expressed transcript and splice events that would have been missed in regular RNA sequencing using the same coverage. In Paper II we selectively depleted the different transcripts of Quaking (QKI), a gene previously associated to schizophrenia. Using RNA sequencing we show that the effects of depletion differ between transcripts and that the QKI gene is a potential regulator of the Glial Fibrillary Acidic Protein (GFAP), a gene implicated in several diseases in the central nervous system. De-novo mutations are frequently reported to be causative in neurodevelopmental disorders with a strong genetic component, such as epilepsy and intellectual disability. In Paper III we used exome sequencing in family trios where the child was diagnosed with both intellectual disability and epilepsy, focusing on finding de-novo mutations. We identified several previously unknown disease causing mutations in genes previously known to cause disease and used previously published interaction and mutation data to prioritize novel candidate genes. The most interesting result from this study are the implication of the HECW2 gene as a candidate gene in intellectual disability and epilepsy. In Paper IV we used RNA sequencing of post mortem brain tissue in a large cohort of schizophrenics and controls. In this study we could show that the immune system and more specifically the complement system was dysregulated in a large fraction of patients. Further, using co-expression network we also found some evidence suggesting genes involved in axon development and maintenance. Jonatan Halvardson, Department of Immunology, Genetics and Pathology, Rudbecklaboratoriet, Uppsala University, SE-751 85 Uppsala, Sweden. © Jonatan Halvardson 2016 ISSN 1651-6206 ISBN 978-91-554-9597-8 urn:nbn:se:uu:diva-287407 (http://urn.kb.se/resolve? urn=urn:nbn:se:uu:diva-287407)
A Unifying Approach for Disturbance Cancellation and Target Detection in Passive Radar Using OFDM

This paper addresses the problem of mobile target detection in multipath scenarios with a passive radar using DVB-T transmitters of opportunity. For such emissions, it has been shown the interest in implementing “mismatched” correlators, reducing both the zero Doppler contribution (ZDC) masking effects and the false alarm rate. A very efficient mismatched reference signal is obtained with the reciprocal filter (or inverse filter) which consists in a modulus frequential equalization of the transmitted signal. We propose here to revisit the reciprocal filter-based correlator and to reinterpret it as a so-called Doppler channel detector (CHAD). This new interpretation allows a direct rejection of the ZDC, unifying in one and the same step the main disturbance mitigation and the detector construction. We provide a statistical theoretical study of the performance and a comparison with the matched correlator, i.e., the classical cross-ambiguity function (CAF). We demonstrate that CHAD has a random pedestal (a clutter floor level) significantly lower than that of the classical CAF for low Doppler frequency shifts. Numerical experiments on simulated and real data as well validate the mathematical derivations.
Localization and Adaptation in Online Learning

We introduce a formalism of localization for online learning problems, which, similarly to statistical learning theory, can be used to obtain fast rates. In particular, we introduce local sequential Rademacher complexities and other local measures. Based on the idea of relaxations for deriving algorithms, we provide a template method that takes advantage of localization. Furthermore, we build a general adaptive method that can take advantage of the suboptimality of the observed sequence. We illustrate the utility of the introduced concepts on several problems. Among them is a novel upper bound on regret in terms of classical Rademacher complexity when the data are i.i. d.
Two rapd-scar markers in new gift Nile tilapia (Oreochromis niloticus) implication for selection tracking and strains identification.

The NEW GIFT Nile tilapia is a national certificated new strain produced through 14 years and 9 generations selection from the base strain of GIFT Nile tilapia. From NEW GIFT Nile tilapia two strain-specific RAPD bands namely S304 and S36 were identified from the amplified bands of 50 and 80 10bp-oligo-nucleotide random primers separately after gel extraction cloning and sequencing of the strain-specific RAPD bands two pairs of primer(20 base for forward primer and 21 base for reverse primer) was designed according to sequence information, then PCR amplification was carried out in NEW GIFT Nile tilapia and base strains and other 7 farmed strains. For the first primer, one 553bp SCAR was amplified showed a 86.7% appearing frequency in NEW GIFT Nile tilapia but only 17% in base strain. This marker has been used as a specific monitor marker for tracking of selection. For the second primer, one 558bp SCAR was amplified showed a 91.4% appearing frequency in NEW GIFT Nile tilapia and 0-70% in other 7 strains. This marker has been used as a specific molecular marker for identification of Nile tilapia strains. The development of these two markers indicated that the frequency of some alleles related with economically important traits might increase during selection.