Search results for: combination coefficients

Authors: Saeid Mehvari, Yolanda Sanchez-Vicente, Sergio González Sánchez, Khalid Lafdi

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Abstract- Materials with a combination of transparency, electrical conductivity, and flexibility are required in the ‎growing electronic sector. In this research, electrically conductive and flexible films have been prepared. These ‎composite films consist of dispersing micro-copper particles into polyurethane (PU) matrix. Two sets of samples were ‎made using both spin coating technique (sample thickness lower than 30 μm) and materials casting (sample thickness ‎lower than 100 μm). Copper concentrations in the PU matrix varied from 0.5 to 20% by volume. The dispersion of ‎micro-copper particles into polyurethane (PU) matrix were characterised using optical microscope and scanning electron ‎microscope. The electrical conductivity measurement was carried out using home-made multimeter set up under ‎pressures from 1 to 20 kPa through thickness and in plane direction. It seems that samples made by casting were not ‎conductive. However, the sample made by spin coating shows through-thickness conductivity when they are under ‎pressure. The results showed that spin-coated films with higher concentration of 2 vol. % of copper displayed a ‎significant increase in the conductivity value, known as percolation threshold. The maximum conductivity of 7.2 × 10-1 ‎S∙m-1 was reached at concentrations of filler with 20 vol. % at 20kPa. A semi-empirical model with adjustable ‎coefficients was used to fit and predict the electrical behaviour of composites. For the first time, the finite element ‎method based on the representative volume element (FE-RVE) was successfully used to predict their electrical ‎behaviour under applied pressures. ‎

Keywords: electrical conductivity, micro copper, numerical simulation, percolation threshold, polyurethane, RVE model

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Authors: Sabrina M. Wang, Rameen Qamar, Fahad Manzar Qureshi, Laura La Chance, Nathan J. Kolla, Barna Konkolÿ Thege

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Elevated level of aggressive behaviour in children and youth can lead to impairments in family, social or academic functioning. The aim of the present study was to critically review the evidence on the effectiveness of nutritional supplements in reducing aggression in children and youth. The Cochrane Library, EMBASE, MEDLINE, ProQuest Dissertations & Theses, PsycINFO, and PubMed data bases were searched for relevant studies. Altogether, 22 studies met inclusion criteria; 13 investigated the effect of macronutrients (fatty acids and amino acids), 6 studies investigated the effect of micronutrients (vitamins and minerals), while 3 studies investigated a combination of macro and micronutrients. Out of the 22 studies, 7 reported a beneficial effect of nutritional supplementation (vitamins and minerals, essential fatty acids, or a certain combination of these). Eight studies did not report a significant beneficial effect of nutritional supplementation (essential fatty acids, vitamin D, and L-tryptophan), while 7 studies reported mixed effects (vitamin B6, essential fatty acids alone and in combination with vitamins and minerals, and carnitine). The results overall suggest that there may be a role for broad-range vitamin and mineral supplements in the treatment of aggression in youth and children.

Keywords: aggression, children, youth, nutritional supplementation, micronutrient, macronutrient

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Authors: Mahmoud Abu-Ghoush, Murad Al Holy

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Our main goal in this project is to study the causes and finding solutions for both the hydrolytic and the oxidative rancidity that can be produced during condensed yoghurt production. The re pasteurization of the pasteurized milk and the addition of different types of antioxidants (ascorbic acid and propyl gallate) were used to achieve this goal. Chemical, physical, microbial and sensory tests were done to evaluate the product. It was found that there were significant differences between the different treatments and the control regarding the peroxide value. This means that the addition of both types of antioxidants have a positive effect in decreasing the rancidity value. However, it was found that there were some samples have hydrolytic rancidity flavour without any type of oxidative rancidity (low peroxide value). To overcome this problem the re pasteurization step was used to destroy all the vegetative form of microbes. It was found that this treatment was very useful in controlling the rancidity flavour according to the sensory evaluation of the condensed yoghurt products for several batches. The best condensed yoghurt which contains 0.25% ascorbic acid exhibited the highest sensory properties values. Also, it has the ability in lowering the oxidative rancidity in the combination with the re pasteurization step of the pasteurized milk. This suggests that a higher quality and stable condensed yoghurt can be obtained upon using this combination. These results may help producers in selecting the best treatment methods to overcome the rancidity flavor in this type of condensed yoghurt.

Keywords: antioxidants, condensed yoghurt, repasturization, condensed milk

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Authors: Z. O. Apotiola, J. F. Fashakin

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This project studied the production and evaluation of jam produced from pineapple and grape at different level of ratio (90:10, 80:20, 70:30, 60:40, 50:50, and 100%). The proximate and sensory properties were determined using standard methods. The (GDZ) was the highest for protein, moisture, fat and ash, (KFJ) was the highest for carbohydrate. There were significant differences (p<0.05) in samples (PAB, GDZ, BEN) for moisture. Also, there were significant differences (p<0.05) in samples (PAB, BBL, GDZ, KFJ) for protein. There were significant differences (p<0.05) in samples (PAB, BBL, BEN) for carbohydrate. Also, there were significant differences (p<0.05) in samples (PAB, BBL, QCM, GDZ, BEN) for fat and there were significant differences (p<0.05) in samples (PAB, BBL, GDZ) for ash. (KFJ) was the highest for pH, (BBL and QCM) was the highest for Vitamin C; (GDZ) was the highest for titratable acidity. For sensory properties, for aroma, colour, flavour, and overall acceptability were tested using panellists; the result showed that (KFJ) had the highest for all samples. From the results of chemical and sensory characteristics sample BBL was the best combination.

Keywords: chemical, characteristic, combination, titratable, sensory, significant

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Clara Shenderey, Helena Vitoshkin, Mordechai Barak, Avraham Arbel

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Greenhouse cultivation is an energy-intensive process due to the high demands on cooling or heating according to external climatic conditions, which could be extreme in the summer or winter seasons. The thermal radiation rate inside a greenhouse depends mainly on the type of covering material and greenhouse construction. Using additional thermal screens under a greenhouse covering combined with a dehumidification system improves the insulation and could be cost-effective. Greenhouse covering material usually contains protective ultraviolet (UV) radiation additives to prevent the film wear, insect harm, and crop diseases. This paper investigates the overall heat transfer coefficient, or U-value, for greenhouse polyethylene covering contains UV-additives and glass covering with or without a thermal screen supplement. The hot-box method was employed to evaluate overall heat transfer coefficients experimentally as a function of the type and number of the thermal screens. The results show that the overall heat transfer coefficient decreases with increasing the number of thermal screens as a hyperbolic function. The overall heat transfer coefficient highly depends on the ability of the material to reflect thermal radiation. Using a greenhouse covering, i.e., polyethylene films or glass, in combination with high reflective thermal screens, i.e., containing about 98% of aluminum stripes or aluminum foil, the U-value reduces by 61%-89% in the first case, whereas by 70%-92% in the second case, depending on the number of the thermal screen. Using thermal screens made from low reflective materials may reduce the U-value by 30%-57%. The heat transfer coefficient is an indicator of the thermal insulation properties of the materials, which allows farmers to make decisions on the use of appropriate thermal screens depending on the external and internal climate conditions in a greenhouse.

Keywords: energy-saving thermal screen, greenhouse cover material, heat transfer coefficient, hot box

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Authors: Abdullah Ansari, Sinika Rambaran, Sirpaul Jaikishun

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Vermiwash could be used to enhance plant productivity and resistance to some harmful plant pathogens, as well as provide benefit through the disposal of waste matter. Alternaria rot caused by the fungus Alternaria alternata (Fr.) Keissl., is a common soil-borne pathogen that results in postharvest fruit rot of cucumbers, peppers and other cash crops. The production and distribution of Cucumis sativus L. (cucumber) could be severely affected by Alternaria rot. Fungicides are the traditional treatment however; they are not only expensive but can also cause environmental and health problems. Vermiwash was prepared from various medicinal plants (Ocimum tenuiflorum L. {Tulsi}, Azadirachta indica A. Juss. {neem}, Cymbopogon citratus (DC. ex Nees) Stapf. {lemon grass} and Oryza sativa L. {paddy straw} and applied, in vitro, to A. alternata to investigate their effectiveness as organic alternatives to traditional fungicides. All of the samples of vermiwash inhibited the growth of A. alternata. The inhibitive effects on the fungus appeared most effective when A. indica and O. tenuiflorum were used in the production of the vermiwash. Using the serial dilution method, vermiwash from O. tenuiflorum showed the highest percent of inhibition (93.2%), followed by C. citratus (74.7%), A. indica (68.7%), O. sativa, combination, and combination without worms. Using the sterile disc diffusion method, all of the samples produced zones of inhibition against A. alternata. Vermiwash from A. indica produced a zone of inhibition, averaging 15.3mm, followed by O. tenuiflorum (14.0mm), combination without worms, combination, C. citratus and O. sativa. Nystatin produced a zone of inhibition of 10mm. The results indicate that vermiwash is not simply an organic alternative to more traditional chemical fungicides, but it may in fact be a better and more effective product in treating certain fungal plant infections, particularly A. alternata.

Keywords: vermiwash, earthworms, soil, bacteria, alternaria alternata, antifungal, antibacterial

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: Ananya Ananya, Karthik Rao

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Accurate segmentation of knee cartilage in 3-D magnetic resonance (MR) images for quantitative assessment of volume is crucial for studying and diagnosing osteoarthritis (OA) of the knee, one of the major causes of disability in elderly people. Radiologists generally perform this task in slice-by-slice manner taking 15-20 minutes per 3D image, and lead to high inter and intra observer variability. Hence automatic methods for knee cartilage segmentation are desirable and are an active field of research. This paper presents design and experimental evaluation of 2D convolutional neural networks based fully automated methods for knee cartilage segmentation in 3D MRI. The architectures are validated based on 40 test images and 60 training images from SKI10 dataset. The proposed methods segment 2D slices one by one, which are then combined to give segmentation for whole 3D images. Proposed methods are modified versions of U-net and dilated convolutions, consisting of a single step that segments the given image to 5 labels: background, femoral cartilage, tibia cartilage, femoral bone and tibia bone; cartilages being the primary components of interest. U-net consists of a contracting path and an expanding path, to capture context and localization respectively. Dilated convolutions lead to an exponential expansion of receptive field with only a linear increase in a number of parameters. A combination of modified U-net and dilated convolutions has also been explored. These architectures segment one 3D image in 8 – 10 seconds giving average volumetric Dice Score Coefficients (DSC) of 0.950 - 0.962 for femoral cartilage and 0.951 - 0.966 for tibia cartilage, reference being the manual segmentation.

Keywords: convolutional neural networks, dilated convolutions, 3 dimensional, fully automated, knee cartilage, MRI, segmentation, U-net

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Rebecca Dunne, Cormac Small, Geraldine O'Boyle, Nazir Ibrahim, Anisha

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Prostate cancer is the most common cancer among men, excluding non-melanoma skin cancers. It is estimated that approximately 12% of men will develop prostate cancer during their lifetime. Patients with intermediate, high risk, and very-high risk prostate cancer often undergo a combination of radiation treatments. These treatments include external beam radiotherapy with a low-dose rate or high-dose rate brachytherapy boost, often with concomitant androgen deprivation therapy. The literature on follow-up of patients that receive brachytherapy is scarce, particularly follow-up of patients that undergo high-dose rate brachytherapy. This retrospective study aims to investigate the biochemical failure and toxicities associated with triple therapy and external beam radiotherapy given in combination with brachytherapy. Reported toxicities and prostate specific antigen (PSA) were retrospectively evaluated in eighty patients that previously underwent external beam radiotherapy with a low-dose rate or high dose-rate brachytherapy boost. The severity of toxicities were correlated with intra-operative dosing during brachytherapy on ultrasound and CT scan. The results of this study will provide further information for clinicians and patients when considering treatment options.

Keywords: toxicities, combination, brachytherapy, intra-operative dosing, biochemical failure

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Authors: Yih-Wenn Laih

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In recent times, the dependence and co-movement among international financial markets have become stronger than in the past, as evidenced by commentaries in the news media and the financial sections of newspapers. Studying the co-movement between returns in financial markets is an important issue for portfolio management and risk management. The realization of co-movement helps investors to identify the opportunities for international portfolio management in terms of asset allocation and pricing. Since the election of the new Prime Minister, Shinzo Abe, in November 2012, the yen has weakened against the US dollar from the 80 to the 120 level. The policies, known as “Abenomics,” are to encourage private investment through a more aggressive mix of monetary and fiscal policy. Given the close economic relations and competitions among Asia markets, it is interesting to discover the co-movement relations, affected by the depreciation of yen, between stock market of Japan and 5 major Asia stock markets, including China, Hong Kong, Korea, Singapore, and Taiwan. Specifically, we devote ourselves to measure the co-movement of stock markets between Japan and each one of the 5 Asia stock markets in terms of rank correlation coefficients. To compute the coefficients, return series of each stock market is first fitted by a skewed-t GARCH (generalized autoregressive conditional heteroscedasticity) model. Secondly, to measure the dependence structure between matched stock markets, we employ the symmetrized Joe-Clayton (SJC) copula to calculate the probability density function of paired skewed-t distributions. The joint probability density function is then utilized as the scoring scheme to optimize the sequence alignment by dynamic programming method. Finally, we compute the rank correlation coefficients (Kendall's  and Spearman's ) between matched stock markets based on their aligned sequences. We collect empirical data of 6 stock indexes from Taiwan Economic Journal. The data is sampled at a daily frequency covering the period from January 1, 2013 to July 31, 2015. The empirical distributions of returns indicate fatter tails than the normal distribution. Therefore, the skewed-t distribution and SJC copula are appropriate for characterizing the data. According to the computed Kendall’s τ, Korea has the strongest co-movement relation with Japan, followed by Taiwan, China, and Singapore; the weakest is Hong Kong. On the other hand, the Spearman’s ρ reveals that the strength of co-movement between markets with Japan in decreasing order are Korea, China, Taiwan, Singapore, and Hong Kong. We explore the effects of “Abenomics” on Asia stock markets by measuring the co-movement relation between Japan and five major Asia stock markets in terms of rank correlation coefficients. The matched markets are aligned by a hybrid method consisting of GARCH, copula and sequence alignment. Empirical experiments indicate that Korea has the strongest co-movement relation with Japan. The strength of China and Taiwan are better than Singapore. The Hong Kong market has the weakest co-movement relation with Japan.

Keywords: co-movement, depreciation of Yen, rank correlation, stock market

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Authors: Seunghee Park, Junkyeong Kim, Eun-Seok Shin, Sang-Hun Han

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In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of underwater concrete structures. A new methodology to estimate the underwater concrete strengths more effectively, named “artificial neural network (ANN) – based concrete strength estimation with the combination of rebound hardness and ultrasonic pulse velocity methods” is proposed and verified throughout a series of experimental works.

Keywords: underwater concrete, rebound hardness, Schmidt hammer, ultrasonic pulse velocity, ultrasonic sensor, artificial neural networks, ANN

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Authors: Muhammet Baldan, Emel Timuçin

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Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, molecular descriptors, machine learning, random forest

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Ediati Budi Cahyono, Triana Hertiani, Nauval Arrazy Asawimanda, Wahyu Puji Pratomo

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Background: Doxorubicin is widely used as a chemotherapeutic drug despite having many side effects. It may cause macrophage dysfunction and decreasing proliferation of lymphocyte. Noni (Morinda citrifolia) fruit which has rich of polysaccharide content has potential as antitumor and immunostimulant effect. The isolation of polysaccharide from Noni fruit has been optimized according to four different methods based on macrophage and lymphocyte activities. We found the highest polysaccharide content from one of the four methods isolation. A method of polysaccharide isolation which has the highest immunostimulant effect was used for further observation as co-chemotherapy. The aim of the study: was to evaluate the isolated polysaccharide from the method of choice as co-chemotherapy of doxorubicin for the growth of Vero, He-La, and T47D cell lines in vitro. The method: in vitro growth assay of Vero, He-La, and T47D cell lines was done using MTT-reduction method, and apoptosis test was done by double staining method to evaluate the induction apoptotic effect of the combination. Every group was treated with doxorubicin and isolated polysaccharide from method of choice with 4 variances of concentrations (25 µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml) a long with negative control (doxorubicin only) and normal control (without doxorubicin or polysaccharide administration). Results: The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin against He-La and T47D cell lines influenced the highest cytotoxic effect by suppressing cell viability comparing with doxorubicin only. The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin-induced apoptotic effect the He-La cell line comparing with doxorubicin only. The result of the study: it can be concluded that the combination of polysaccharide fraction and doxorubicin effect more selective toward He-La and T47D cell lines than to Vero cell line. It can be suggested isolated polysaccharide from the method of choice has co-chemotherapy activity against doxorubicin.

Keywords: polysaccharide, noni fruit, doxorubicin, cancer cell lines, vero cell line

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Authors: K. A. Mistry, I. B. Patel, A. H. Prajapati

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In the present work, the alloy of Bismuth-lead is prepared on the basis of percentage of molecular weight 9:1, 5:5 and 1:9 ratios and grown by Zone- Refining Technique under a vacuum atmosphere. The EDAX of these samples are done and the results are reported. Micro hardness test has been used as an alternative test for measuring material’s tensile properties. The effect of temperature and load on the hardness of the grown alloy has been studied. Further the comparative studies of work hardening coefficients are reported. In the present work, the alloy of Bismuth-lead is prepared on the basis of percentage of molecular weight 9:1, 5:5 and 1:9 ratios and grown by Zone- Refining Technique under a vacuum atmosphere. The EDAX of these samples are done and the results are reported. Micro hardness test has been used as an alternative test for measuring material’s tensile properties. The effect of temperature and load on the hardness of the grown alloy has been studied. Further the comparative studies of work hardening coefficients are reported.

Keywords: EDAX, hardening coefficient, micro hardness, Bi-Pb alloy

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Authors: Emi̇ne Avşar Aydin, Nezahat Günenç Tuncel, A. Hami̇t Serbest

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The electromagnetic scattering from a canonical structure is an important issue in electromagnetic theory. In this study, the electromagnetic scattering from a dielectric sphere with oblique incidence is investigated. The incident field is considered as a plane wave with H polarized. The scattered and transmitted field expressions with unknown coefficients are written. The unknown coefficients are obtained by using exact boundary conditions. Then, the sphere is considered as having frequency dependent dielectric permittivity. The frequency dependence is shown by Cole-Cole model. The far scattered field expressions are found respect to different incidence angles in the 1-8 GHz frequency range. The observation point is the angular distance of pi from an incident wave. While an incident wave comes with a certain angle, observation point turns from 0 to 360 degrees. According to this, scattered field amplitude is maximum at the location of the incident wave, scattered field amplitude is minimum at the across incident wave. Also, the scattered fields are plotted versus frequency to show frequency-dependence explicitly. Graphics are shown for some incident angles compared with the Harrington's solution. Thus, the results are obtained faster and more reliable with reciprocal rotation. It is expected that when there is another sphere with different properties in the outer sphere, the presence and location of the sphere will be detected faster. In addition, this study leads to use for biomedical applications in the future.

Keywords: scattering, dielectric sphere, oblique incidence, reciprocal rotation

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Authors: Young-Eun Jang, Mi-Hye Ma, Yemi Kim

Abstract:

As the elderly population increases, the number of patients complaining of dry mouth is also increasing. Elderly people often use mouthwash to prevent periodontal disease. Mouthwash and saliva substitutes with low pH were reported to be able to cause enamel erosion. To the best of our knowledge, there have been no studies showing the effect of mouthwash on patients using saliva substitutes. Therefore, the purpose of this study was to evaluate the effect of the use of mouthwash in combination with saliva substitutes on tooth erosion using a quantitative light-induced fluorescence-digital (QLF-D) system. A total of 96 bovine specimens were embedded in putty blocks and randomly allocated to the following groups with n = 12 each: Group 1, application of mouthwash; Group 2, application of saliva substitutes; Group 3, application of saliva substitutes in combination with mouthwash; and control group, application of saline. The bovine samples were eroded using a demineralization solution and then saliva substitutes and mouthwash were applied according to the groups for 2 weeks. For saliva substitutes, three different products were used; Oasis (Oasis Consumer Health, Cleveland, OH, USA), Xeromia solution (Osstem Pharma Co., Seoul, Korea), and Drymund gel (Dong-A Pharma Co., Seoul, Korea). The pH values of the saliva substitutes were determined using a pH meter. Loss of enamel and root dentin was measured using the QLF-D system immediately after demineralization on the 3rd, 7th, and 14th days. The data were analyzed using repeated measures ANOVA followed by Tukey’s post hoc tests (p < 0.05). Mineral loss in enamel and root dentin was detected when mouthwash and saliva substitutes were used alone, respectively (p < 0.05). Also, when mouthwash was used with saliva substitutes, the mineral loss was observed in enamel and root dentin (p < 0.05). The use of Xeromia and Drymund gel increased mineral loss of enamel significantly compared to the use of Oasis (p < 0.05). However, when Drymund gel and Xeromia were used in combination with mouthwash, mineral loss of enamel was significantly reduced compared to when they were used alone (p < 0.05). The pH values of Drymund gel, Xeromia, Oasis, and mouthwash were 5.5, 5.52, 6.2, and 6.37, respectively. Based on these results, it can be concluded that the use of mouthwash with a higher pH value than that of saliva substitutes could help patients suffering from xerostomia avoid the risk of dental erosion.

Keywords: saliva substitute, mouthwash, tooth erosion, dry mouth

Procedia PDF Downloads 63

Authors: Usman A. Usman

Abstract:

Undeniably, unlike the Classical side, the Keynesian perspective of the aggregate demand side indeed has a significant position in the policy, growth, and welfare of Nigeria due to government involvement and ineffective demand of the population living with poor per capita income. This study seeks to investigate the effect of Government Final Consumption Expenditure, Financial Deepening on Households, and NPISHs Final consumption expenditure using data on Nigeria from 1981 to 2019. This study employed the ADF stationarity test, Johansen Cointegration test, and Vector Error Correction Model. The results of the study revealed that the coefficient of Government final consumption expenditure has a positive effect on household consumption expenditure in the long run. There is a long-run and short-run relationship between gross fixed capital formation and household consumption expenditure. The coefficients cpsgdp (financial deepening and gross fixed capital formation posit a negative impact on household final consumption expenditure. The coefficients money supply lm2gdp, which is another proxy for financial deepening, and the coefficient FDI have a positive effect on household final consumption expenditure in the long run. Therefore, this study recommends that Gross fixed capital formation stimulates household consumption expenditure; a legal framework to support investment is a panacea to increasing hoodmold income and consumption and reducing poverty in Nigeria. Therefore, this should be a key central component of policy.

Keywords: government final consumption expenditure, household consumption expenditure, vector error correction model, cointegration

Procedia PDF Downloads 25

Authors: M. Abbasi

Abstract:

A spillway structure is used to pass excess water and floods from upstream or upstream to downstream or tributary. The spillway is considered one of the most key members of the dam, and the failure of many dams is attributed to the inefficiency of their spillway. Weirs should be selected as strong, reliable and high-performance structures, and weirs should be ready for use in all conditions and able to drain the flood so that we do not witness many casualties and financial losses when a flood occurs. The purpose of this study is to simulate the flow pattern passing over the peak spillway in order to optimize and adjust the height of the spillway walls. In this research, the effect of the shape of the side wings on the flow pattern over the peak spillways of the Gotvand reservoir dam was simulated and modelled using Flow3D software. In this research, side wings with rounded walls with six different approach angles were used. In addition, the different value of H/Hd was used to check the effect of the tank head. The results showed that with the constant H/Hd ratio and the increase of the approach angle of the side wing, the flow depth first decreases and then increases. These changes were the opposite regarding the depth average speed of the flow and the depth average concentration of the air entering the flow. At the same time, with the constant angle of approach of the side wing and with the increase of H/Hd ratio, the flow depth increases. In general, a correct understanding of the operation of overflows and a correct design can significantly reduce construction costs and solve flooding problems.

Keywords: effect of the shape, gotvand reservoir dam, narrowing coefficients, supports of the gates

Procedia PDF Downloads 39

Authors: Barenten Suciu

Abstract:

Classical matrix calculus and Routh-Hurwitz stability conditions, applied to the snake-like motion of the conical wheel axle, lead to the conclusion that the hunting mode is inherently unstable, and its natural frequency is a complex number. In order to analytically solve such a complicated vibration model, either the inertia terms were neglected, in the model designated as geometrical, or restrictions on the creep coefficients and yawing diameter were imposed, in the so-called dynamical model. Here, an alternative solution is proposed to solve the hunting mode, based on the observation that the bullet train wheel axle is equipped with cylindrical wheels. One argues that for such wheel treads, the geometrical hunting is irrelevant, since its natural frequency becomes nil, but the dynamical hunting is significant since its natural frequency reduces to a real number. Moreover, one illustrates that the geometrical simplification of the wheel causes the stabilization of the hunting mode, since the characteristic quartic equation, derived for conical wheels, reduces to a quadratic equation of positive coefficients, for cylindrical wheels. Quite simple analytical expressions for the damping ratio and natural frequency are obtained, without applying restrictions into the model of contact. Graphs of the time-depending hunting lateral perturbation, including the maximal and inflexion points, are presented both for the critically-damped and the over-damped wheel axles.

Keywords: bullet train, creep, cylindrical wheels, damping, dynamical hunting, stability, vibration analysis

Procedia PDF Downloads 129

Authors: Sharmeelee Subramaniam, Muhd Harris Ramli, Fauziah Ahmad

Abstract:

The application of vacuum pressure to accelerate ground consolidation has been growing significantly in recent years. This ground improvement technique has its advantages, especially in areas where suitable fill is scarce, as it minimizes the surcharge fill height required for the preloading. A study was carried out to examine the response of soft subsoil subjected to vacuum consolidation in combination with embankment loading, surcharge preloading and PVD with two-way drainage. This paper shall describe a procedure to determine the optimum surcharge height and penetration depth of prefabricated vertical drains (PVD) where vacuum consolidation is combined with the use of PVD in soft clay deposits with two-way drainage.

Keywords: prefabricated vertical drain, soft soil, surcharge preload, vacuum consolidation

Procedia PDF Downloads 60

Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

Abstract:

Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

Procedia PDF Downloads 208

Authors: Abdallah H. Ramini, Alwathiqbellah I. Ibrahim, Mohammad I. Younis

Abstract:

We investigate experimentally and theoretically the dynamics of a capacitive resonator under mixed frequency excitation of two AC harmonic signals. The resonator is composed of a proof mass suspended by two cantilever beams. Experimental measurements are conducted using a laser Doppler Vibrometer to reveal the interesting dynamics of the system when subjected to two-source excitation. A nonlinear single-degree-of-freedom model is used for the theoretical investigation. The results reveal combination resonances of additive and subtractive type, which are shown to be promising to increase the bandwidth of the resonator near primary resonance frequency. Our results also demonstrate the ability to shift the combination resonances to much lower or much higher frequency ranges. We also demonstrate the dynamic pull-in instability under mixed frequency excitation.

Keywords: electrostatically actuated resonator, multi-frequency excitation, nonlinear dynamics, AC harmonic signals

Procedia PDF Downloads 593

Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

Abstract:

Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: factors of social innovation, methodological combination, social innovation process, supporting decision-making

Procedia PDF Downloads 131

Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

Abstract:

Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

Procedia PDF Downloads 309

Authors: Yogesh D. Bansod, Jiri Bursa

Abstract:

The quantitative study of cell mechanics is of paramount interest since it regulates the behavior of the living cells in response to the myriad of extracellular and intracellular mechanical stimuli. The novel experimental techniques together with robust computational approaches have given rise to new theories and models, which describe cell mechanics as a combination of biomechanical and biochemical processes. This review paper encapsulates the existing continuum-based computational approaches that have been developed for interpreting the mechanical responses of living cells under different loading and boundary conditions. The salient features and drawbacks of each model are discussed from both structural and biological points of view. This discussion can contribute to the development of even more precise and realistic computational models of cell mechanics based on continuum approaches or on their combination with microstructural approaches, which in turn may provide a better understanding of mechanotransduction in living cells.

Keywords: cell mechanics, computational models, continuum approach, mechanical models

Procedia PDF Downloads 336

Authors: Usman A. Usman

Abstract:

Undeniably, unlike the Classical side, the Keynesian perspective of the aggregate demand side indeed has a significant position in the policy, growth, and welfare of Nigeria due to government involvement and ineffective demand of the population living with poor per capita income. This study seeks to investigate the effect of Government Final Consumption Expenditure, Financial Deepening on Households, and NPISHs Final consumption expenditure using data on Nigeria from 1981 to 2019. This study employed the ADF stationarity test, Johansen Cointegration test, and Vector Error Correction Model. The results of the study revealed that the coefficient of Government final consumption expenditure has a positive effect on household consumption expenditure in the long run. There is a long-run and short-run relationship between gross fixed capital formation and household consumption expenditure. The coefficients cpsgdp financial deepening and gross fixed capital formation posit a negative impact on household final consumption expenditure. The coefficients money supply lm2gdp, which is another proxy for financial deepening, and the coefficient FDI have a positive effect on household final consumption expenditure in the long run. Therefore, this study recommends that Gross fixed capital formation stimulates household consumption expenditure; a legal framework to support investment is a panacea to increasing hoodmold income and consumption and reducing poverty in Nigeria. Therefore, this should be a key central component of policy.

Keywords: household, government expenditures, vector error correction model, johansen test

Procedia PDF Downloads 29