Miracle-dz/UniFAR-FTUs huggingface dataset:
Detailed description of triphone model using SSS-free algorithm

The triphone model is frequently used as an acoustic model. It is effective for modeling phonetic variations caused by coarticulation. However, it is known that acoustic features of phonemes are also affected by other factors such as speaking style and speaking speed. In this paper, a new acoustic model is proposed. All training data which have the same phoneme context are automatically clustered into several clusters based on acoustic similarity, and a “sub-triphones” is trained using training data corresponding to a cluster. In experiments, the sub-triphone model achieved about 5% higher phoneme accuracy than the triphone model.
A Strategic Framework For Value Enhancing Enterprise Risk Management

Enterprise risk management (ERM) is a new management concept fast ascending the corporate agenda globally. Its relevancy and popularity as a management technique are abetted by the changing business practices and burgeoning regulatory requirements on risk management. The shift in paradigm in heightened risk awareness in the wake of several high profile and deep impact corporate governance scandal and financial mismanagement cases as well as increased terrorist threat on the physical assets of firms has compelled firms to be more pro-active in addressing risk issues
Fast Error Decoding with Binary VLSI Logic

Maximal distance binary codes that are composed of individual characters from the residues of pairwise prime polynomials are constructed and compared to Reed-Solomon codes. Although these binary residue codes are not as efficient as R-S codes in that codeword lengths are shorter, error decoding involves only binary and not finite field operations and thus allows faster decoding and greater data rates. Data rates of hundreds of megabits per second are feasible if decoding is implemented with VLSI array logic. Constructions of array logic for use in decoding are described. These codes lend themselves for use in a concatenated coding scheme.
PROACT: a phase II randomized trial of recombinant pro-urokinase by direct arterial delivery in acute middle cerebral artery stroke. PROACT Investigators. Prolyse in Acute Cerebral Thromboembolism.

BACKGROUND AND PURPOSE To test the safety and recanalization efficacy of intra-arterial local delivery of plasminogen activators in acute ischemic stroke, a randomized trial of recombinant pro-urokinase (rpro-UK) versus placebo was undertaken in patients with angiographically documented proximal middle cerebral artery occlusion. METHODS After exclusion of intracranial hemorrhage by CT scan, patients with abrupt onset of symptoms of focal ischemia likely to receive treatment within 6 hours who satisfied all clinical eligibility criteria underwent carotid angiography. Patients displaying Thrombolysis in Acute Myocardial Infarction grade 0 or 1 occlusion of the M1 or M2 middle cerebral artery were randomized 2:1 to receive rpro-UK (6 mg) or placebo over 120 minutes into the proximal thrombus face. All patients received intravenous heparin. Recanalization efficacy was assessed at the end of the 2-hour infusion, and intracerebral hemorrhage causing neurological deterioration was assessed at 24 hours. RESULTS Of 105 patients who underwent angiography, 59 were excluded from randomization. Among the 46 patients randomized, 40 were treated with rpro-UK (n=26) or placebo (n=14) a median of 5.5 hours from symptom onset. Recanalization was significantly associated with rpro-UK (2P=.017). Hemorrhagic transformation causing neurological deterioration within 24 hours of treatment occurred in 15.4% of the rpro-UK-treated patients and 7.1% of the placebo-treated patients (2P=.64). Both recanalization and hemorrhage frequencies were influenced by heparin dose. CONCLUSIONS Intra-arterial local rpro-UK infusion was associated with superior recanalization in acute thrombotic/ thromboembolic stroke compared with placebo. In this regimen, heparin dose influenced hemorrhage frequency and recanalization. Although symptomatic hemorrhage remains a concern, this study suggests that recanalization is enhanced with rpro-UK and heparin.
Adaptive batching of streams to enhance throughput and to support dynamic load balancing

As data permeates all disciplines, the role of big data becomes increasingly important. Sensors, IoT devices, social networks, and online transactions are all generating data that can be monitored constantly to enable a business to identify opportunity to enhance customer service and increase revenue. This need for real-time processing of big data has led to the development of frameworks for distributed stream processing in clusters. It is important for such frameworks to be resilient against variable operating conditions such as server load variation, changes in data ingestion rates, and workload characteristics. In this thesis, we explore the effects of the batch size on the performance of streaming workloads by developing an adaptive batching framework and building load-balancing algorithms on top of this framework. We explore the idea of using a combination of adaptive batching of tuples and dynamic tuple dispatching to improve the throughput and load-distribution of the workload. We show through experiments that the system is able to be resilient and robust under varying operating conditions.
Identifying Quora question pairs having the same intent

This paper presents a system which uses a combination of multiple text similarity measures of varying complexities to classify Quora question pairs as duplicate or different. The solution uses a support vector classifier model trained using the precomputed features ranging from longest common sub-string and sub sequences to word similarity based on lexical and semantic resources. The scope of this project is to tackle the short text similarity classification problem by applying Natural Language Processing techniques. The approach and methodologies used in this paper can be further extended to implement automatic short answer grading systems, essay grading system and textual entailment detection problems as well.
Driving forces in small-firm investment in local environmental management systems

The aim in this study has been to investigate the driving forces and stakeholders involved small firms’ environmental investment decision making. Slow adoption of environmental management systems among SME has been noted throughout Europe, yet it is recognized that SMEs account for well over half of environmental pollution. Major driving forces are identified from previous SME research and are combined with stakeholder theory to map key environmental stakeholders. The empirical evidence is based on a case study of the food service industry in Gothenburg, Sweden, using in- depth personal interviews with restaurant managers as the main source of data. The study results identify distinctly different driving forces behind middle and smaller restaurants’ motivation to invest in environmental measures. The middle size restaurant, which were typically more dependent on single business customers, were motivated by their external stakeholders; whereas smaller restaurants, which were typically more consumer oriented, were more motivated by the internal stakeholders. These results suggests an extension to stakeholder theory, where it is noted that firms are influenced by different sets of stakeholders depending on their size and their customer orientation.
Profitability in an Electronic Foreign Exchange Market: Informed Trading or Differences in Valuation?

Fundamental spot exchange rate models preclude the existence of asymmetric information in foreign exchange markets. This article critically investigates the possibility that private information arises in the spot foreign exchange market. Using a rich dataset, we first empirically detect transaction behavior consistent with the informed trading hypothesis. We then work within the theoretical framework of a high-frequency version of a structural microstructure trade model, which directly measures the market makerâ€™s beliefs. We find that the time-varying pattern of the probability of informed trading is rooted in the strategic arrival of informed traders on a particular hour-of-day, day-of-week, or geographic location (market).
Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications

Information overload has made it increasingly difficult to analyze large amounts of data and generate appropriate management decisions. Furthermore, data is often imprecise and will include both quantitative and qualitative elements. For these reasons, it is important to extend traditional decision making processes by adding intuitive reasoning, human subjectivity, and imprecision. Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies. This book covers a variety of possible fuzzy logic approaches to customer relationship management and marketing, making it a valuable resource for not only students and researchers but also executives, managers, marketing experts, and project leaders who are interested in applying fuzzy classification to managerial decisions.
Optimal estimation for fault sections in power systems based on differential harmony search

In this paper, the nonlinear optimal control problem is formulated as a multi-objective mathematical optimization problem. Differential Harmony search (DHS) algorithm is one of the new heuristic algorithms. The DHS optimization algorithm is introduced for the first time in solving the fault sections estimation performance in power systems. A case on optimal estimation for fault section in the part of the 230KV Southern Brazilian electric power system is presented to show the methodology's feasibility and efficiency. Compared with the existing fault section estimation in power system methods, the search time of the DHS optimization algorithm is shorter and the result is close to the ideal solution.
Categorizing genetically modified food products: Effects of labelling on information processing

Purpose – The purpose of this paper is to provide insight into whether GM‐labelling leads to different processing behaviour of food stimuli compared to when products are not labelled.Design/methodology/approach – A task was designed to investigate people's categorization behaviour as a function of information provided. In two studies each participant was randomly allocated to either the experimental “GM‐labelled condition”, or the control “non‐labelled condition”. Findings – Different processing strategies and different characteristics are used to judge products that are labelled as genetically modified or not. GM labelling of foods is interpreted to induce analytical processing of information and therefore the products are classified relatively more often on the basis of verifiable categorization criteria compared to when they were not labelled as GM. When products are not labelled as GM, information is more likely to be automatically processed and non‐verifiable categorization criteria are used.Originali.
CUSTOMER PREFERENCES FOR TRANSIT ATIS: RESEARCH REPORT

This Customer Preferences for Transit ATIS (Advanced Traveler Information System) report reflects federal interest in (1) understanding the extent to which transit agencies are currently trying innovative, advanced ways of offering transit information to their ridership, especially real-time information and (2) what transit riders prefer regarding the use of high technology tools to access this information. This peer reviewed report documents the findings from a customer preference survey conducted through a series of 12 workshops covering 284 transit customers in four cities to determine: what type of transit information customers prefer; how they want to receive it; where and when they want to receive it, and what the critical human factors issues are in presenting transit information. Key findings indicate that customers prefer: accurate and up to date information as a first priority; high quality static information including traditional wayside signage; realtime information at as many stops as cost-effectively possible; while on vehicles, automated next stop announcements, and better marketing agencies.
The Effect of Section 404 of the Sarbanes-Oxley Act on Financial Reporting Quality

In this paper we study the effect of Section 404 of the Sarbanes-Oxley Act on earnings quality. Using a difference-in-differences method we find that firms that were required to comply with Section 404 during the first two years of its implementation improved the quality of their financial reporting more than control firms that were not required to comply. Our testing results also provide some evidence that the reduction in intentional misstatement contributes to the improvement in financial reporting quality of complying firms. Investor confidence appears to be restored, in that they react more strongly to earnings surprises of complying firms than to those of the control firms in the post-404 period. These results are robust to various sensitivity tests. Our results suggest that Section 404 helped to achieve the main goal of the Act: protecting investors and restoring their confidence in the stock market by improving the accuracy and reliability of corporate disclosure.
Success of ERP System in Indian Industries: a Comparative Study among Selected Industries

Enterprise solutions provide a centralized framework for all data and processes of an organization. It integrates all aspects of a business from planning to inventory control, manufacturing, sales, marketing, finance, customer service and human resources. A significant part of our service portfolio is our customized ERP solutions. The SAP business and MS dynamics NAV services provided by us include: software licensing, data migration, implementation, support, consultancy and training. We deploy resources on integrated teams that work with our clients to undertake complex enterprise transformation efforts. Selection of the three organizations is based on the need to collect detailed data about the ERP implementation process in each organization. In all the three industries, questionnaires were sent to 600 end-users. A total of 202 questionnaires taken for analysis have shown that the first three dominant success factors of TI infotech, BPCL and ITTI are related to the quality dimensions, suggesting that the success of implementing ERP system is largely determined by the quality dimensions. Thus the technological newness was the most important factor in determining the quality of the system.
Corporate Governance and Corporate Social Responsibility:Emerging Markets Focus

While emerging market economies do not have a mature market structure yet, there is a need for research on corporate governance practices in these economies from different perspectives, including corporate social responsibility. Corporate Governance and Corporate Social Responsibility: Emerging Markets Focus fills the gap with a collection of high-quality research and policy-based papers addressing these issues, using various market cases as illustrations. Unlike previous books that often focused on one or several emerging markets, this book covers a much broader set of countries and tackles ethical, legal and societal aspects of corporate governance, beyond financial issues. It also discusses how companies work towards best corporate governance practices, particularly, in the aftermath of recent financial and economic crises. Readers will benefit from the wide range of theoretical, empirical, and case analyses, selected with care to reflect cutting-edge corporate governance and corporate social responsibility issues in countries with emerging markets.
Trends in coronary risk factors in the WHO MONICA project.

BACKGROUND The World Health Organization (WHO) MONICA Project was established to determine how trends in event rates for coronary heart disease (CHD) and, optionally, stroke were related to trends in classic coronary risk factors. Risk factors were therefore monitored over ten years across 38 populations from 21 countries in four continents (overall period covered: 1979-1996). METHODS A standard protocol was applied across participating centres, in at least two, and usually three, independent surveys conducted on random samples of the study populations, well separated within the 10-year study period. RESULTS Smoking rates decreased in most male populations (35-64 years) but in females the majority showed increases. Systolic blood pressure showed decreasing trends in the majority of centres in both sexes. Mean levels of cholesterol generally showed downward trends, which, although the changes were small, had large effects on risk. There was a trend of increasing body mass index (BMI) with half the female populations and two-thirds of the male populations showing a significant increase. CONCLUSIONS It is feasible to monitor the classic CHD risk factors in diverse populations through repeated surveys over a decade. In general, the risk factor trends are downwards in most populations but in particular, an increase in smoking in women in many populations and increasing BMI, especially in men, are worrying findings with significant public health implications.
Non-rigid registration of cardiac MR: application to motion modelling and atlas-based segmentation

Three-dimensional (3D) and four-dimensional (4D) imaging of the heart is a rapidly developing area of research in medical imaging. Recent advances in development of MR imaging for fast spatio-temporal cardiac imaging have led to an increased interest in the use of MR imaging for functional analysis of the cardiovascular system. Segmentation of left and right ventricle and modelling of myocardial motion provide important information for quantitative functional analysis. In this paper we show how non-rigid registration techniques can be used to solve these problems in cardiac MR images.
Comparison of Interval Constraint Propagation Algorithms for Vehicle Localization

Interval constraint propagation (ICP) algorithms allow to solve problems described as constraint satisfaction problems (CSP). ICP has been successfully applied to vehicle localization in the last few years. Once the localization problem has been stated, a large class of ICP solvers can be used. This paper compares a few ICP algorithms, using the same experimental data, in order to rank their performances in terms of accuracy and computing time.
Carpal and cubital tunnel and other, rarer nerve compression syndromes.

BACKGROUND Carpal tunnel syndrome is by far the most common peripheral nerve compression syndrome, affecting approximately one in every six adults to a greater or lesser extent. Splitting the flexor retinaculum to treat carpal tunnel syndrome is the second most common specialized surgical procedure in Germany. Cubital tunnel syndrome is rarer by a factor of 13, and the other compression syndromes are rarer still. METHODS This review is based on publications retrieved by a selective literature search of PubMed and the Cochrane Library, along with current guidelines and the authors' clinical and scientific experience. RESULTS Randomized controlled trials have shown, with a high level of evidence, that the surgical treatment of carpal tunnel syndrome yields very good results regardless of the particular technique used, as long as the diagnosis and the indication for surgery are well established by the electrophysiologic and radiological findings and the operation is properly performed. The success rates of open surgery, and the single-portal and dual-portal endoscopic methods are 91.6%, 93.4% and 92.5%, respectively. When performed by experienced hands, all these procedures have complication rates below 1%. The surgical treatment of cubital tunnel syndrome has a comparably low complication rate, but worse results overall. Neuro-ultrasonography and magnetic resonance imaging (neuro-MRI) are increasingly being used to complement the diagnostic findings of electrophysiologic studies. CONCLUSION Evidence-based diagnostic methods and treatment recommendations are now available for the two most common peripheral nerve compression syndromes. Further controlled trials are needed for most of the rarer syndromes, especially the controversial ones.
Active CMOS-MEMS conductive probes and arrays for tunneling-based atomic-level surface imaging

This paper reports on development of AFM-like active CMOS-MEMS conductive probes and arrays. The active probes are aimed for scanning tunneling microscopy (STM) imaging and field-emission (FE) assisted nanostructure formation. Two kinds of STM tip approaches compatible with CMOS-MEMS process — Electron-Induced Beam Deposition (EBID) and Spindt tip method — are presented, and their functionality is examined. Atomic-level resolution is achieved using tips in an ultra-high vacuum (UHV) STM. The MEMS probe working in ambient STM is also demonstrated. The active probe is equipped with a transimpedance amplifier (TIA) for tip FE current measurement around a nominal value of 1 nA.
Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration

Image restoration problems are often solved by finding the minimizer of a suitable objective function. Usually this function consists of a data-fitting term and a regularization term. For the least squares solution, both the data-fitting and the regularization terms are in the $\ell$2 norm. In this paper, we consider the least absolute deviation (LAD) solution and the least mixed norm (LMN) solution. For the LAD solution, both the data-fitting and the regularization terms are in the $\ell$1 norm. For the LMN solution, the regularization term is in the $\ell$1 norm but the data-fitting term is in the $\ell$2 norm. Since images often have nonnegative intensity values, the proposed algorithms provide the option of taking into account the nonnegativity constraint. The LMN and LAD solutions are formulated as the solution to a linear or quadratic programming problem which is solved by interior point methods. At each iteration of the interior point method, a structured linear system must be solved. The preconditioned conjugate gradient method with factorized sparse inverse preconditioners is employed to solve such structured inner systems. Experimental results are used to demonstrate the effectiveness of our approach. We also show the quality of the restored images, using the minimization of mixed $\ell$2-$\ell$1 and $\ell1$-$\ell$1 norms, is better than that using only the $\ell$2 norm.
Low phase noise VCO using novel harmonic control circuit based on composite right/left-handed transmission line

In this paper, a novel voltage-controlled oscillator (VCO) using the harmonic control circuit based on the composite right/left-handed (CRLH) transmission lines (TLs) is presented to reduce the phase noise without the reduction of the frequency tuning range and miniaturize the circuit size. The phase noise is reduced by the novel harmonic control circuit having the short impedances for the second- and third-harmonic components. The proposed harmonic control circuit is designed by using the CRLH TLs with the dual-band characteristic by the frequency offset and phase slope of the CRLH TLs. The high-Q resonator has been used to reduce the phase noise, but has the problem of the frequency tuning range reduction. However, the frequency tuning range of the proposed VCO has not been reduced because the phase noise has been reduced without the high-Q resonator. The miniaturization of the circuit size is achieved by using the CRLH TLs instead of the conventional right-handed (RH) TLs. The phase noise of VCO is −119.17 ∼ −117.50 dBc/Hz at 100 kHz in the tuning range of 5.731 ∼ 5.938 GHz.