Spectral analysis of pathological acoustic speech waveforms

Biomedical engineering is the application of engineering principles and techniques to the medical field. The design and problem solving skills of engineering are combined with medical and biological science, which improves medical disorder diagnosis and treatment. The purpose of this study is to develop an automated procedure for detecting excessive jitter in speech signals, which is useful for differentiating normal from pathologic speech. The fundamental motivation for this research is that tools are needed by speech pathologists and laryngologists for use in the early detection and treatment of laryngeal disorders. Acoustical analysis of speech was performed to analyze various features of a speech signal. Earlier research established a relation between pitch period jitter and harmonic bandwidth. This concept was used for detecting laryngeal disorders in speech since pathologic speech has been found to have larger amounts of jitter than normal speech. Our study was performed using vowel samples from the voice disorder database recorded at the Massachusetts Eye and Ear Infirmary (MEEI) in1994. The KAYPENTAX company markets this database. Software development was conducted using MATLAB, a user-friendly programming language which has been applied widely for signal processing. An algorithm was developed to compute harmonic bandwidths for various speech samples of sustained vowel sounds. Open and closed tests were conducted on 23 samples of pathologic and normal speech samples each. Classification results showed 69.56% probability of correct detection of pathologic speech samples during an open test

Cost-Effective Allocation Of Nested Routing Relay Node Resources

By implementing an overlay routing system, the ability to adjust various routing features (such as latency or TCP throughput) is available, without requiring any changes to the underlying standards. However, laying the groundwork for overlays involves setting up the overlay infrastructure. Here we have an optimization challenge that arises: The smallest set of overlay nodes to find is one that is sufficient to provide the necessary routing features. To prove that in a thorough manner, we analyze this optimization issue here. This paper shows that it is hard to approximate and so provides a nontrivial approximation approach. The details of the plan are examined in the context of numerous actual scenarios to measure the benefit that may be realized. Here, we examine a wide range of BGP-enabled routers to see how few required less than 100 BGP-enabled servers to implement BGP routing policy across the shortest pathways to all autonomous systems (ASs), hence lowering the average path length of routed pathways by 40%. The study is able to prove the scheme's many uses, the first of which is for TCP performance improvement, with results that achieve nearly optimal placement of overlay nodes. Also, when using Voice-over-IP (VoIP) applications, where a small number of overlay nodes can have a significant impact on maximum peer-to-peer delay, the study shows that the scheme's many functions are useful

A Proficient Method For High Eminence And Cohesive Relevant Phrase Mining

A sentence is an integral unit of semantic nature, context and significance. Visualizing sentences for each topic is an important way to investigate and interpret unstructured corporate texts in subject modeling. Usually the term mining method is double: mining phrases and modeling theme. Current methods also suffer from order-sensitive and improper segmentation problems for phrase mining, which often lead to phrases of low content. The limitations of sentences, which may undermine continuity, are not entirely taken into account by standard topic models for topic modeling. In addition, current methods are frequently subject to domain terminology loss as the effect of topical domain dissemination is disregarded. We suggest an effective approach for high-quality and coherent topical sentence mining in this article. A high-quality sentence must meet the requirements for frequency, phrasing, integrity and suitability. In order to increase the both phrase consistency and topical cohesion, we combine the quality assured phrase mining process, a novel subject models that incorporate phrasing restriction, and a novel text clustering method into an iterative system. Effective algorithm designs to perform these methods effectively are often defined

Willingness To Pay Pengunjung Wisatawan Andeman Boonpring Dalam Upaya Pelestarian Lingkungan

Desa wisata Andeman Boonpring sebagai tujuan wisata sebelumnya merupakan daerah perlindungan sebagai embung yang digunakan sebagai cadangan air Kecamatan Turen. Keadaan alam ini harus dilindungi agar terus menjadi daya tarik wisatawan, sehingga lingkungan wisata tersebut selalu dalam keadaan bersih, salah satunya dengan menerapkan Willingness to Pay (WTP) kepada pengunjung. Tujuan penelitian ini adalah untuk menganalisis besarnya nilai WTP yang mampu dibayarkan wisatawan guna menjaga lingkungan desa wisata serta untuk dianalisis beberapa faktor yang melatarbelakangi nilai WTP para wisatawan dalam pelestarian desa wisata. Metode yang digunakan dalam penelitian ini menggunakan kuantitatif korelasional yang menghubungkan empat variabel independent. Teknik pengumpulan data dilakukan dengan teknik kuesioner. Hasil penelitian menunjukkan bahwa besaran nilai WTP yang mampu dibayarkan oleh wisatawan Andeman Boonpring berada pada nilai rata-rata sebesar Rp.2.593,7 (Rp.2.500). Sedangkan faktor yang mempengaruhi WTP menunjukkan bahwa variabel asal wisatawan (X1), pendapatan (X3), dan variabel biaya (X4) memiliki koefisien poritif. Artinya, variabel ini berpengaruh besar terhadap WTP. Sedangkan Koefisien variabel pendidikan (X2) berkoefisien negatif dengan hal ini variabel tersebut tidak berpengaruh signifikan terhadap WTP

Involving Common Media to Export Product Recommendation Using Existing Data

There is an increasingly blurred line between e-commersce and social networking. Many e-commerce platforms support the social authentication process through which users can sign in using their social network identity, for example, on Facebook or Twitter. In addition, users can also post new items on microblogs with links to the website of the product for e-commerce. The purpose of this paper is to recommend goods for e-commerce web pages to users on social networking sites under "cold-start," an issue that was scarcely investigated before, in an innovative approach to the cold-start product advice. One of the main challenges for the advice is how to use the information derived from social networking platforms. We suggest using connected users through social networking websites and e-commerce websites as a bridge to map the functionality of social networking users to another feature for product suggestion and for social networking. In particular, we suggest learning the user and product characteristics of data obtained from e-commerce sites using recurring neural networks (known as the user embedding and the goods embedding), and then implement a revamped system of gradients boosting trees to turn user social networking features into user embedding

Poder Executivo - Medida Provisória nº 474/2009 24/12/2009

MEDIDA PROVISÓRIA Nº 474, DE 23 DE DEZEMBRO DE 2009 DOU 24.12.2009 Dispõe sobre o salário mínimo a partir de 1º de janeiro de 2010 e estabelece diretrizes para a política de valorização do salário mínimo entre 2011 e 2023

Machine-Learning-Augmented Predictive Modeling of Turbulent Separated Flows over Airfoils

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143090/1/1.J055595.pd

Correlation-based Transition Modeling for External Aerodynamic Flows

Conventional turbulence models calibrated for fully turbulent boundary layers often over-predict drag and heat transfer on aerodynamic surfaces with partially laminar boundary layers. A robust correlation-based model is developed for use in Reynolds-Averaged Navier-Stokes simulations to predict laminar-to-turbulent transition onset of boundary layers on external aerodynamic surfaces. The new model is derived from an existing transition model for the two-equation k-omega Shear Stress Transport (SST) turbulence model, and is coupled with the one-equation Spalart-Allmaras (SA) turbulence model. The transition model solves two transport equations for intermittency and transition momentum thickness Reynolds number. Experimental correlations and local mean flow quantities are used in the model to account for effects of freestream turbulence level and pressure gradients on transition onset location. Transition onset is triggered by activating intermittency production using a vorticity Reynolds number criterion. In the new model, production and destruction terms of the intermittency equation are modified to improve consistency in the fully turbulent boundary layer post-transition onset, as well as ensure insensitivity to freestream eddy viscosity value specified in the SA model. In the original model, intermittency was used to control production and destruction of turbulent kinetic energy. Whereas, in the new model, only the production of eddy viscosity in SA model is controlled, and the destruction term is not altered. Unlike the original model, the new model does not use an additional correction to intermittency for separation-induced transition. Accuracy of drag predictions are improved significantly with the use of the transition model for several two-dimensional single- and multi-element airfoil cases over a wide range of Reynolds numbers. The new model is able to predict the formation of stable and long laminar separation bubbles on low-Reynolds number airfoils that is not captured with conventional turbulence models. The validated transition model is successfully applied to rotating blade configurations in axial flow conditions to study the effects of transitional boundary layers on rotor thrust and torque. In helicopter rotors, inclusion of transition effects increased thrust prediction by 2% and decreased torque by as much as 8% at lower collective angles, due to reduced airfoil profile drag. In wind turbine rotors, transition model predicted a 7%--70% increase in generated shaft torque at lower wind speeds, due to lower viscous drag. This has important implications for CFD analysis of small wind turbines operating at low values of rated power. Transition onset locations along upper and lower surfaces of rotor blades are analyzed in detail. A new crossflow transition onset criterion is developed to account for crossflow instability effects in three-dimensional boundary layers. Preliminary results for swept wing and rotating blade flows demonstrate the need to account for crossflow transition in three-dimensional simulations of wings, rotating blades, and airframes. Inclusion of crossflow effects resulted in accelerated transition in the presence of favorable pressure gradients and yawed flow. Finally, a new correction to the wall damping function in the Spalart-Allmaras turbulence model is proposed to improve sensitivity of the model to strong adverse pressure gradients (APG). The correction reduces turbulence production in the boundary layer when the ratio of magnitudes of local turbulent stress to the wall shear stress exceeds a threshold value, therefore enabling earlier separation of boundary layer. Improved prediction of static and dynamic stall on two-dimensional airfoils is demonstrated with the APG correction

Closest Keyword Search in Dynamic Multidimensional Data Sets

Adding text to databases opens up many different innovations and functionalities that can be made feasible for keyword-based quests. The application in question focuses on search results that are keyword-marked and that are located in a geographical area. For these datasets, our main goal is to locate groups of points that satisfy search queries. Our team's recommendation is a process we call Projection and Multi Scale Hashing that combines random projection and hashing to provide great scalability and efficiency. This example illustrates how to present algorithms in both an exact and approximate manner. Analyses that take into account experimental and analytical studies show that, with regard to overall efficiency, multi-dimensional hashing offers up to 65 times better results. A point in a dynamic connection multi-dimensional feature space is a typical way to classify an object, and we often describe various objects as a point in a multi-dimensional feature space. In other words, for example, images are described using feature vectors that are comprised of colour components, and a textual description of the image is typically correlated with it (such as tags or keywords)