Search results for: sandwich technique

Authors: Abdolreza Esmaeilzadeh, Mehri Mirzaei

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Objective: Rheumatic disease is a chronic disease that causes pain, stiffness, swelling and limited motion and function of many joints. RA is the most common form of autoimmune arthritis, affecting more than 1.3 million Americans. Of these, about 75% are women. Materials and Methods: This study was formed due to the misconception about ANA test, which is frequently performed with methods based upon solid phase as ELISA. This experiment was conducted on 430 patients, with clinical symptoms that are likely affected with rheumatic diseases, simultaneously by means of ANA and FANA. Results: 36 cases (8.37%) of patients, despite positive ANA, have demonstrated negative results via Indirect Immunofluorescence Assay (IIFA), (false positive). 116 cases (27%) have demonstrated negative ANA results, by means of the ELISA technique, although they had positive IIFA results. Conclusion: Other advantages of IIFA are antibody titration and specific pattern detection that have the capability of distinguishing positive dsDNA results. According to the restrictions and false negative cases, in patients, IIFA test is highly recommended for these disease's diagnosis.

Keywords: autoimmune disease, IIFA, EIA, rheumatic disease

Procedia PDF Downloads 499

Authors: Ashkan Zakaryazad, Ekrem Duman

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A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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Authors: L. Hamsaveni, Navya Prakash, Suresha

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Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

Procedia PDF Downloads 377

Authors: Michael Koblischka, Anjela Koblischka-Veneva, XianLin Zeng, Essia Hannachi, Yassine Slimani

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Superconducting foams of YBa2Cu3O7 (abbreviated Y-123) were produced using the infiltration growth (IG) technique from Y2BaCuO5 (Y-211) foams. The samples were investigated by SEM (scanning electron microscopy) and electrical resistivity measurements. SEM observations indicated the specific microstructure of the foam struts with numerous tiny Y-211 particles (50-100 nm diameter) embedded in channel-like structures between the Y-123 grains. The investigation of the excess conductivity of different prepared composites was analyzed using Aslamazov-Larkin (AL) model. The investigated samples comprised of five distinct fluctuation regimes, namely short-wave (SWF), one-dimensional (1D), two-dimensional (2D), three-dimensional (3D), and critical (CR) fluctuations regimes. The coherence length along the c-axis at zero-temperature (ξc(0)), lower and upper critical magnetic fields (Bc1 and Bc2), critical current density (Jc) and numerous other superconducting parameters were estimated from the data. The analysis reveals that the presence of the tiny Y-211 particles alters the excess conductivity and the fluctuation behavior observed in standard YBCO samples.

Keywords: Excess conductivity, Foam, Microstructure, Superconductor YBa2Cu3Oy

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Authors: M. A. Ansari, A. Hussain, A. Uddin

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A side weir is a flow diversion structure provided in the side wall of a channel to divert water from the main channel to a branch channel. The trapezoidal labyrinth weir is a special type of weir in which crest length of the weir is increased to pass higher discharge. Experimental and numerical studies related to the coefficient of discharge of trapezoidal labyrinth weir in an open channel have been presented in the present study. Group Method of Data Handling (GMDH) with the transfer function of quadratic polynomial has been used to predict the coefficient of discharge for the side trapezoidal labyrinth weir. A new model is developed for coefficient of discharge of labyrinth weir by regression method. Generalized models for predicting the coefficient of discharge for labyrinth weir using Group Method of Data Handling (GMDH) network have also been developed. The prediction based on GMDH model is more satisfactory than those given by traditional regression equations.

Keywords: discharge coefficient, group method of data handling, open channel, side labyrinth weir

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Authors: Frank Frimpong Opuni, Michael Mba Allan, Kwame Adu-Gyamfi, Michael Sarkodie Baffoe

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This paper assesses the effect of relationship marketing on service quality and customer satisfaction from the perspective of the moderating role of emotional intelligence in the insurance industry in Ghana. A descriptive quantitative research technique was employed. A random sample of 384 each of customers and service providers in 3 insurance firms in Accra were used as the source of data. According to findings, emotional intelligence makes a strong positive effect on relationship marketing at 5% significance level, r (283) = .817, p = .000. Though relationship marketing makes a strong positive effect on service quality (r = .767, p < .05) and customer satisfaction (r = .647, p < .05), this effect becomes insignificant (p > .05) when the effect of emotional intelligence on relationship marketing is controlled for. It is therefore recommended that insurance firms give priority to equipping their relationship employees with emotional intelligence to maximise service quality and customer satisfaction.

Keywords: relationship marketing, service quality, customer satisfaction, emotional intelligence

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Authors: Rais Yusoh, Rosli Saad, Mokhtar Saidin, Fauzi Andika, Sabiu Bala Muhammad

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Resistivity and seismic refraction profiling have become a common method in pre-investigations for visualizing subsurface structure. The integration of the methods could reduce an interpretation ambiguity. Both methods have their individual software packages for data inversion, but potential to combine certain geophysical methods are restricted; however, the research algorithms that have this functionality was existed and are evaluated personally. The interpretation of subsurface were improve by combining inversion data from both methods by influence each other models using closure coupling; thus, by implementing both methods to support each other which could improve the subsurface interpretation. These methods were applied on a field dataset from a pre-investigation for archeology in finding the ancient river. There were no major changes in the inverted model by combining data inversion for this archetype which probably due to complex geology. The combine data analysis provides an additional technique for interpretation such as an alluvium, which can have strong influence on the ancient river findings.

Keywords: ancient river, combine inversion, resistivity, seismic refraction

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Authors: Tung-Hui Hsu, Wen-Yuh Jywe

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Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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Authors: Hanna Mamo Ergando

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Climate change is already having a severe influence on agriculture, affecting crop yields, the nutritional content of main grains, and livestock productivity. Significant adaptation investments will be necessary to sustain existing yields and enhance production and food quality to fulfill demand. Climate-smart agriculture (CSA) provides numerous potentials in this regard, combining a focus on enhancing agricultural output and incomes while also strengthening resilience and responding to climate change. To improve agriculture production and productivity, the Ethiopian government has adopted and implemented a series of strategies, including the recent agricultural cluster farming that is practiced as an effort to change, improve, and transform subsistence farming to modern, productive, market-oriented, and climate-smart approach through farmers production cluster. Besides, greater attention and focus have been given to wheat production and productivity by the government, and wheat is the major crop grown in cluster farming. Therefore, the objective of this assessment was to examine various opportunities and challenges farmers face in a cluster farming system. A qualitative research approach was used to generate primary and secondary data. Respondents were chosen using the purposeful sampling technique. Accordingly, experts from the Federal Ministry of Agriculture, the Ethiopian Agricultural Transformation Institute, the Ethiopian Agricultural Research Institute, and the Ethiopian Environment Protection Authority were interviewed. The assessment result revealed that farming in clusters is an economically viable technique for sustaining small, resource-limited, and socially disadvantaged farmers' agricultural businesses. The method assists farmers in consolidating their products and delivering them in bulk to save on transportation costs while increasing income. Smallholders' negotiating power has improved as a result of cluster membership, as has knowledge and information spillover. The key challenges, on the other hand, were identified as a lack of timely provision of modern inputs, insufficient access to credit services, conflict of interest in crop selection, and a lack of output market for agro-processing firms. Furthermore, farmers in the cluster farming approach grow wheat year after year without crop rotation or diversification techniques. Mono-cropping has disadvantages because it raises the likelihood of disease and insect outbreaks. This practice may result in long-term consequences, including soil degradation, reduced biodiversity, and economic risk for farmers. Therefore, the government must devote more resources to addressing the issue of environmental sustainability. Farmers' access to complementary services that promote production and marketing efficiencies through infrastructure and institutional services has to be improved. In general, the assessment begins with some hint that leads to a deeper study into the efficiency of the strategy implementation, upholding existing policy, and scaling up good practices in a sustainable and environmentally viable manner.

Keywords: cluster farming, smallholder farmers, wheat, challenges, opportunities

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

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Authors: Nermin Mahmoud Gohar, Aisha Tarek Noour

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Learner satisfaction has been a vital field of interest in the literature. Accordingly, the paper will explore the reasons behind individual differences in motivation and satisfaction. This study examines the effect of both; Herzberg’s and Maslow’s theories on learners satisfaction. A self-administered questionnaire was used to collect data from learners who were geographically widely spread around the College of Maritime Transport and Technology (CMTT) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. One hundred and fifty undergraduates responded to a questionnaire survey. Respondents were drawn from two branches in Alexandria and Port Said. The data analysis used was SPSS 22 and AMOS 18. Factor analysis technique was used to find out the dimensions under study verified by Herzberg’s and Maslow’s theories. In addition, regression analysis and structural equation modeling were applied to find the effect of the above-mentioned theories on maritime transport learners’ satisfaction. Concerning the limitation of this study, it used the available number of learners in the CMTT due to the relatively low population in this field.

Keywords: motivation, satisfaction, needs, education, Herzberg’s and Maslow’s theories

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Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: M. Aruna

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Emphasis on the advancement of new materials and technology has been there for the past few decades. The global development towards using cheap and durable materials from renewable resources contributes to sustainable development. An experimental investigation of mechanical behaviour of sisal fiber-reinforced concrete is reported for making a suitable building material in terms of reinforcement. Fibre reinforced composite is one such material, which has reformed the concept of high strength. Sisal fibres are abundantly available in the hot areas. The sisal fiber has emerged as a reinforcing material for concretes, used in civil structures. In this work, properties such as hardness and tensile strength of sisal fibre reinforced cement composites with 6, 12, 18, and 24% by weight of sisal fibres were assessed. Sisal fiber reinforced cement composite slabs with long sisal fibers were manufactured using a cast hand layup technique. Mechanical response was measured under tension. The high energy absorption capacity of the developed composite system was reflected in high toughness values under tension respectively.

Keywords: sisal fibre, fiber-reinforced concrete, mechanical behaviour, composite materials

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Authors: A. A. Salisu, M. Y. Yakasai, K. M. Aujara

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Sisal leaves were subjected to enzymatic retting method to extract the sisal fibre. A portion of the fibre was pretreated with alkali (NaOH), and further treated with benzoyl chloride and silane treatment reagents. Both the treated and untreated Sisal fibre composites were used to fabricate the composite by hand lay-up technique using unsaturated polyester resin. Tensile, flexural, water absorption, density, thickness swelling and chemical resistant tests were conducted and evaluated on the composites. Results obtained for all the parameters showed an increase in the treated fibre compared to untreated fibre. FT-IR spectra results ascertained the inclusion of benzoyl and silane groups on the fibre surface. Scanning electron microscopy (SEM) result obtained showed variation in the morphology of the treated and untreated fibre. Chemical modification was found to improve adhesion of the fibre to the matrix, as well as physico-mechanical properties of the composites.

Keywords: chemical resistance, density test, polymer matrix sisal fibre, thickness swelling

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Authors: A. Hemmati, H. Mirsaeedghazi, M. Aboonajmi

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Carrot juice is one of the most nutritious foods that are consumed around the world. Large particles in carrot juice causing turbid appearance make some problems in the concentration process such as off-flavor due to the large particles burnt on the walls of evaporators. Microfiltration (MF) is a pressure driven membrane separation method that can clarify fruit juices without enzymatic treatment. Fouling is the main problem in the membrane process causing reduction of permeate flux. Ultrasound as a cleaning technique was applied at 20 kHz to reduce fouling in membrane clarification of carrot juice using dead-end MF system with polyvinylidene fluoride (PVDF) membrane. Results showed that application of ultrasound waves reduce diphasic characteristic of carrot juice and permeate flux increased. Evaluation of different membrane fouling mechanisms showed that application of ultrasound waves changed creation time of each fouling mechanism. Also, its behavior was changed with varying transmembrane pressure.

Keywords: Carrot juice, Dead end, Microfiltration, Ultrasound

Procedia PDF Downloads 319

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

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This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

Procedia PDF Downloads 324

Authors: Murtala Sale

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The use of instructional materials is an indispensable tool that enhances qualitative teaching and learning especially at the primary level. Instructional materials are used to facilitate comprehension of ideas in the learners as well as ensure long term retention of ideas and topics taught to pupils. This study examined the relevance of using instructional materials in primary schools in Katsina State, Nigeria. It employed survey design using cluster sampling technique. The questionnaire was used to gather data for analysis, and statistical and frequency tables were used to analyze the data gathered. The results show that teachers and students alike have realized the effectiveness of modern instructional materials in teaching and learning for the attainment of set objectives in the basic primary education policy. It also discovered that reluctance in the use of instructional materials will hamper the achievement of qualitative primary education. The study therefore suggests that there should be the provision of adequate and up-to-date instructional materials to all primary schools in Katsina State for effective teaching and learning process.

Keywords: instructional materials, effective teaching, learning quality, indispensable aspect

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Authors: B. Hossen, Y. Helmut

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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

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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: M. M. Hlakola, E. Golovins, D. V. Nicolae

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The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the ac-dc transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ac-dc transfer measurement system was analyzed for the common-mode (CM) EMI effects. Further investigation of coupling path as well as more accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops

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Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

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Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

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Authors: Lakshminarayanan, Vijayaraghavan, Krishnamurthy

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The ever-increasing demand for high efficiency in automotive and aerospace applications requires new materials to suit to high temperature applications. The Ceramic Matrix Composites nowadays find its applications for high strength and high temperature environments. In this paper, Al2O3 and Sic ceramic materials are taken in particulate form as matrix and reinforcement respectively. They are blended together in Ball Milling and compacted in Cold Compaction Machine by powder metallurgy technique. Scanning Electron Microscope images are taken for the samples in order to find out proper blending of powders. Micro harness testing is also carried out for the samples in Vickers Micro Hardness Testing Equipment. Surface grinding of the samples is also carried out in Surface Grinding Machine in order to find out grinding force estimates. The surface roughness of the grounded samples is also taken in Surface Profilometer. These are yielding promising results.

Keywords: ceramic matrix composite, cold compaction, material characterization, particulate and surface grinding

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Authors: R. Ziaie Moayed, A. Mahigir

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Stone column technique has been successfully employed to improve the load-settlement characteristics of foundations. A series of finite element numerical analyses of harmonic dynamic loading have been conducted on strengthened raft footing to study the effects of single and group stone columns on settlement of circular footings. The settlement of circular raft footing that improved by single and group of stone columns are studied under harmonic dynamic loading. This loading is caused by heavy machinery foundations. A detailed numerical investigation on behavior of single column and group of stone columns is carried out by varying parameters like weight of machinery, loading frequency and period. The result implies that presence of single and group of stone columns enhanced dynamic behavior of the footing so that the maximum and residual settlement of footing significantly decreased. 

Keywords: finite element analysis, harmonic loading, settlement, stone column

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Authors: Wojciech Kulesza

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The north-western part of the Poland, specifically West Pomerania and Lubuskie provinces, from several years are the subject of research of the Department of Archaeology of Early Middle Ages of Institute of Archaeology of Nicolaus Copernicus University in Toruń. This area has a dense network of rivers and numerous lakes, where many of them are connected to the southern part of the Baltic Sea. During the many years of research in this area, archaeologists discovered the remains of the early Middle Ages settlement located on several islands and in most cases were encountered relics of early Middle Ages bridges linking those islands with the mainland. During the excavation, work was carried out both under water and on land for the accurate identification of islands and adjacent to them underwater areas. The result of this work is a graphic documentation, made in a three-dimensional technique, not only for the underwater trenches but also relics of bridges and objects discovered during exploration, which as the main theme will be presented in the full presentation.

Keywords: Poland, underwater archaeology, Nicolaus Copernicus University, early middle ages

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Authors: M. Saadi, S. E. H. Abaidia, M. Y. Mokeddem.

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We present the results of a systematic and comparative study of the bulk, the structural properties, and phonon calculations of aluminum alloys using several exchange–correlations functional theory (DFT) with different plane-wave basis pseudo potential techniques. Density functional theory implemented by the Vienna Ab Initio Simulation Package (VASP) technique is applied to calculate the bulk and the structural properties of several structures. The calculations were performed for within several exchange–correlation functional and pseudo pententials available in this code (local density approximation (LDA), generalized gradient approximation (GGA), projector augmented wave (PAW)). The lattice dynamic code “PHON” developed by Dario Alfè was used to calculate some thermodynamics properties and phonon dispersion relation frequency distribution of Aluminium alloys using the VASP LDA PAW and GGA PAW results. The bulk and structural properties of the calculated structures were compared to different experimental and calculated works.

Keywords: DFT, exchange-correlation functional, LDA, GGA, pseudopotential, PAW, VASP, PHON, phonon dispersion

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Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

Abstract:

The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

Procedia PDF Downloads 129

Authors: A. Chateauneuf, M. Mostoufi, D. Vyncke

Abstract:

Monte Carlo (MC) simulation is a technique that provides approximate solutions to a broad range of mathematical problems. A drawback of the method is its high computational cost, especially in a high-dimensional setting, such as estimating the Tail Value-at-Risk for large portfolios or pricing basket options and Asian options. For these types of problems, one can construct an upper bound in the convex order by replacing the copula by the comonotonic copula. This comonotonic upper bound can be computed very quickly, but it gives only a rough approximation. In this paper we introduce the Comonotonic Monte Carlo (CoMC) simulation, by using the comonotonic approximation as a control variate. The CoMC is of broad applicability and numerical results show a remarkable speed improvement. We illustrate the method for estimating Tail Value-at-Risk and pricing basket options and Asian options when the logreturns follow a Black-Scholes model or a variance gamma model.

Keywords: control variate Monte Carlo, comonotonicity, option pricing, scientific computing

Procedia PDF Downloads 515