Search results for: Markov chain Monte Carlo method

Authors: Abdelazim Makki Ibrahim, Esamaldeen Ali

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This study aims at analysing the load settlement behavior and predict the bearing capacity of piled raft foundation a series of finite element models with different foundation configurations and stiffness were established. Numerical modeling is used to study the behavior of the piled raft foundation due to the complexity of piles, raft, and soil interaction and also due to the lack of reliable analytical method that can predict the behavior of the piled raft foundation system. Simple analytical models are developed to predict the average settlement and the load sharing between the piles and the raft in piled raft foundation system. A simple example to demonstrate the applications of these charts is included.

Keywords: finite element, pile-raft foundation, method, PLAXIS software, settlement

Procedia PDF Downloads 543

Authors: Nur Azilina Abdul Aziz, Tuti Katrina Abdullah, Ahmad Azmin Mohamad

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Lithium-transition metals and some of their oxides, such as LiCoO2, LiMn2O2, LiFePO4, and LiNiO2 have been used as cathode materials in high performance lithium-ion rechargeable batteries. Among the cathode materials, LiCoO2 has potential to been widely used as a lithium-ion battery because of its layered crystalline structure, good capacity, high cell voltage, high specific energy density, high power rate, low self-discharge, and excellent cycle life. This cathode material has been widely used in commercial lithium-ion batteries due to its low irreversible capacity loss and good cycling performance. However, there are several problems that interfere with the production of material that has good electrochemical properties, including the crystallinity, the average particle size and particle size distribution. In recent years, synthesis of nanoparticles has been intensively investigated. Powders prepared by the traditional solid-state reaction have a large particle size and broad size distribution. On the other hand, solution method can reduce the particle size to nanometer range and control the particle size distribution. In this study, LiCoO2 was synthesized using the sol–gel preparation method, which Lithium acetate and Cobalt acetate were used as reactants. The stoichiometric amounts of the reactants were dissolved in deionized water. The solutions were stirred for 30 hours using magnetic stirrer, followed by heating at 80°C under vigorous stirring until a viscous gel was formed. The as-formed gel was calcined at 700°C for 7 h under a room atmosphere. The structural and morphological analysis of LiCoO2 was characterized using X-ray diffraction and Scanning electron microscopy. The diffraction pattern of material can be indexed based on the α-NaFeO2 structure. The clear splitting of the hexagonal doublet of (006)/(102) and (108)/(110) in this patterns indicates materials are formed in a well-ordered hexagonal structure. No impurity phase can be seen in this range probably due to the homogeneous mixing of the cations in the precursor. Furthermore, SEM micrograph of the LiCoO2 shows the particle size distribution is almost uniform while particle size is between 0.3-0.5 microns. In conclusion, LiCoO2 powder was successfully synthesized using the sol–gel method. LiCoO2 showed a hexagonal crystal structure. The sample has been prepared clearly indicate the pure phase of LiCoO2. Meanwhile, the morphology of the sample showed that the particle size and size distribution of particles is almost uniform.

Keywords: cathode material, LiCoO2, lithium-ion rechargeable batteries, Sol-Gel method

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Hankyu Lee, Seoung Bum Kim

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The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Ma Chaoyang

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This article starts from the perspective of environmental justice theory and analyzes the accessibility and regional equity of park green spaces in the central urban area of Chengdu in 2022 based on the improved Gaussian 2SFCA analysis method and Gini coefficient method. Then, according to the relevant analysis model, it further explores the correlation between the spatial distribution of park green spaces and the socio-economic conditions of residents in order to provide a reference for the construction and research of Chengdu's park city under the guidance of fairness and justice. The results show that: (1) Overall, the spatial distribution of parks and green spaces in Chengdu shows a significantly uneven distribution of extreme core edge, with a certain degree of unfairness; that is, there is an environmental injustice pattern. (2) The spatial layout of urban parks and green spaces is subject to strong guiding interference from the socio-economic level; that is, there is a high correlation between housing prices and the tendency of parks. (3) Green space resources Gini coefficient analysis shows that residents of the three modes of transportation in the study area have unequal opportunities to enjoy park and green space services, and the degree of unfairness in walking is much greater than that in cycling and cycling.

Keywords: parks and green spaces, environmental justice, two step mobile search method, Gini coefficient, spatial distribution

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Authors: Bi Yan-Qiang, Shang Yonghong, Lin Boying, Ji Xinyan, Li Xiyuan

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The heat-resistant material has important application in the aerospace field. The reliability of the connection between the heat-resisting material and the body determines the success or failure of the project. In this paper, lock-in infrared thermography non-destructive testing technology is used to detect the stability of the thermal-resistant structure. The phase relationship between the temperature and the heat flow is calculated by the numerical method, and the influence of the heating frequency and power is obtained. The correctness of the analysis is verified by the experimental method. Through the research, it can provide the basis for the parameter setting of heat flux including frequency and power, improve the efficiency of detection and the reliability of connection between the heat-resisting material and the body.

Keywords: infrared non-destructive, thermal insulation material, reliability, connection

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Authors: U. Ravi Babu, Mohd Mastan

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The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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Authors: Feng Yin

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Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Husnil Khatimah, Fairol Halim

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This research examines the moderating impact of security on intention to use e-money that adapted from some variables of the TAM (Technology Acceptance Model) and TPB (Theory of Planned Behavior). This study will use security as moderating variable and finds these relationship depends on customer intention to use e-money as payment tools. The conceptual framework of e-money transactions was reviewed to understand behavioral intention of consumers from perceived usefulness, perceived ease of use, perceived behavioral control and security. Quantitative method will be utilized as sources of data collection. A total of one thousand respondents will be selected using quota sampling method in Medan, Indonesia. Descriptive analysis and Multiple Regression analysis will be conducted to analyze the data. The article ended with suggestion for future studies.

Keywords: e-money transaction, TAM & TPB, moderating variable, behavioral intention, conceptual paper

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Authors: K. Akhil, J. Jayakumar, S. Sudheer Khan

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Zinc oxide nanoparticles (ZnO NPs) are extensively used in a wide variety of commercial products including sunscreen, textile and paints. The present study evaluated the effect of surface capping agents including polyethylene glycol (EG), gelatin, polyvinyl alcohol(PVA) and poly vinyl pyrrolidone(PVP) on photocatalytic activity of ZnO NPs. The particles were also tested for its antibacterial and antibiofilm activity against Staphylococcus aureus (MTCC 3160) and Pseudomonas aeruginosa (MTCC 1688). Preliminary characterization was done by UV-Visible spectroscopy. Electron microscopic analysis showed that the particles were hexagonal in shape. The hydrodynamic size distribution was analyzed by using dynamic light scattering method and crystalline nature was determined by X-Ray diffraction method.

Keywords: antibacterial, antibiofilm, capping agents, photodegradation, surface coating, zinc oxide nanoparticles

Procedia PDF Downloads 259

Authors: M. R. Haji Hajikolaei, A. A. Nikvand, A. R. Ghadrdan, M. Ghorbanpoor, B. Mohammadian

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This study was carried out on water buffalo for detection of Leptospira interrogans in kidney and urine and its relationship with serological findings. Blood, urine and kidney samples were taken immediately after slaughter from 353 water buffalos at Ahvaz abattoir in Khouzestan province, Iran. Sera were initially screened at serum dilution of 1:100 against seven live antigens of Leptospira interrogans: pomona, hardjo, ballum, icterohemorrhagiae, tarasovi, australis and grippotyphosa using the microscopic agglutination test (MAT) and sera with positive results were titrated against reacting antigens in serial twofold dilution from 1:100 to 1:800. The samples of kidney were embedded in paraffin wax and 5µm thick sections were stained routinely with Haematoxylin and Eosin (H&E). Polymerase chain reaction (PCR) examination was done on urine and kidney by using LipL32 gene primers. Antibodies against one or more serovars at dilution >:100 were detected in sera. The most frequent reactor was hardjo (56.2%), followed by pomona (52.3%), australis (9.8%), tarassovi (5.9%), grippotyphosa (4.5%) and icterohaemorrhagiae (3.9%). The L. interrogans were detected in 43 (12.2%) of examined buffaloes, so that 26 (8.2%) of kidney tissues, 14 (4.8%) of urine samples separately and 3 (0.84%) of both kidney and urine samples were positive in PCR. From 153 (43.3%) buffaloes with positive MAT, 24 cases were positive by PCR of kidney and/or urine samples, synchronously. Renal lesions such as interstitial nephritis, acute tubular necrosis (ATN), pyelonephritis, glomerolonephritis, renal fibrosis and hydronephrosis were found in 128 (36.3%) cases. Statistical analysis indicated that there was no significant association between results of MAT, PCR and interstitial nephritis.

Keywords: leptospiral infection, PCR, MAT, histopathology, river buffalo

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Authors: Shubham Jaiswal

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During modelling of many physical problems and engineering processes, fractional calculus plays an important role. Those are greatly described by fractional differential equations (FDEs). So a reliable and efficient technique to solve such types of FDEs is needed. In this article, a numerical solution of a class of fractional differential equations namely space fractional order reaction-advection dispersion equations subject to initial and boundary conditions is derived. In the proposed approach shifted Jacobi polynomials are used to approximate the solutions together with shifted Jacobi operational matrix of fractional order and spectral collocation method. The main advantage of this approach is that it converts such problems in the systems of algebraic equations which are easier to be solved. The proposed approach is effective to solve the linear as well as non-linear FDEs. To show the reliability, validity and high accuracy of proposed approach, the numerical results of some illustrative examples are reported, which are compared with the existing analytical results already reported in the literature. The error analysis for each case exhibited through graphs and tables confirms the exponential convergence rate of the proposed method.

Keywords: space fractional order linear/nonlinear reaction-advection diffusion equation, shifted Jacobi polynomials, operational matrix, collocation method, Caputo derivative

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Authors: Dyah Purwaningsih, Roto Roto, Hari Sutrisno

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Manganese dioxide (MnO₂) and its derivatives are among the most widely used materials for the positive electrode in both primary and rechargeable lithium batteries. The MnO₂ derivative compound of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) is one of the leading candidates for positive electrode materials in lithium batteries as it is abundant, low cost and environmentally friendly. Over the years, synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) has been carried out using various methods including sol-gel, gas condensation, spray pyrolysis, and ceramics. Problems with these various methods persist including high cost (so commercially inapplicable) and must be done at high temperature (environmentally unfriendly). This research aims to: (1) synthesize LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) by reflux technique; (2) develop microstructure analysis method from XRD Powder LiMₓMn₂₋ₓO₄ data with the two-stage method; (3) study the electrical conductivity of LiMₓMn₂₋ₓO₄. This research developed the synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) with reflux. The materials consisting of Mn(CH₃COOH)₂. 4H₂O and Na₂S₂O₈ were refluxed for 10 hours at 120°C to form β-MnO₂. The doping of Co, Ni and Cr were carried out using solid-state method with LiOH to form LiMₓMn₂₋ₓO₄. The instruments used included XRD, SEM-EDX, XPS, TEM, SAA, TG/DTA, FTIR, LCR meter and eight-channel battery analyzer. Microstructure analysis of LiMₓMn₂₋ₓO₄ was carried out on XRD powder data by two-stage method using FullProf program integrated into WinPlotR and Oscail Program as well as on binding energy data from XPS. The morphology of LiMₓMn₂₋ₓO₄ was studied with SEM-EDX, TEM, and SAA. The thermal stability test was performed with TG/DTA, the electrical conductivity was studied from the LCR meter data. The specific capacity of LiMₓMn₂₋ₓO₄ as lithium battery cathode was tested using an eight-channel battery analyzer. The results showed that the synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) was successfully carried out by reflux. The optimal temperature of calcination is 750°C. XRD characterization shows that LiMn₂O₄ has a cubic crystal structure with Fd3m space group. By using the CheckCell in the WinPlotr, the increase of Li/Mn mole ratio does not result in changes in the LiMn₂O₄ crystal structure. The doping of Co, Ni and Cr on LiMₓMn₂₋ₓO₄ (x = 0.02; 0.04; 0; 0.6; 0.08; 0.10) does not change the cubic crystal structure of Fd3m. All the formed crystals are polycrystals with the size of 100-450 nm. Characterization of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) microstructure by two-stage method shows the shrinkage of lattice parameter and cell volume. Based on its range of capacitance, the conductivity obtained at LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) is an ionic conductivity with varying capacitance. The specific battery capacity at a voltage of 4799.7 mV for LiMn₂O₄; Li₁.₀₈Mn₁.₉₂O₄; LiCo₀.₁Mn₁.₉O₄; LiNi₀.₁Mn₁.₉O₄ and LiCr₀.₁Mn₁.₉O₄ are 88.62 mAh/g; 2.73 mAh/g; 89.39 mAh/g; 85.15 mAh/g; and 1.48 mAh/g respectively.

Keywords: LiMₓMn₂₋ₓO₄, solid-state, reflux, two-stage method, ionic conductivity, specific capacity

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Authors: Amira Mabrouk, Chokri Abdennadher

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The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: willingness to pay, contingent valuation, time value, city toll

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Authors: Hayrettin Eroglu, Adem Kara

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Recently there has been significant attention given to imaging of the biological tissues via microwave imaging techniques. In this study, a phantom for the test and calibration of Microwave imaging used in detecting unhealthy breast structure or tumors was produced by using sol gel method. The liquid and gel phantoms being used nowadays are not durable due to evaporation and their organic ingredients, hence a new design was proposed. This phantom was fabricated from materials that were widely available (water, salt, gelatin, and glycerol) and was easy to make. This phantom was aimed to be better from the ones already proposed in the literature in terms of its durability and stability. S Parameters of phantom was measured with 1-18 GHz Probe Kit and permittivity was calculated via Debye method in “85070” commercial software. One, three, and five-week measurements were taken for this phantom. Finally, it was verified that measurement results were very close to the real biological tissue measurement results.

Keywords: phantom, breast tissue, cancer, microwave imaging

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Authors: M. M. Atashi, P. Malekzadeh

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A first known formulation for the out-of-plane free vibration analysis of functionally graded (FG) circular curved beams in thermal environment and with temperature dependent material properties is presented. The formulation is based on the first order shear deformation theory (FSDT), which includes the effects of shear deformation and rotary inertia due to both torsional and flexural vibrations. The material properties are assumed to be temperature dependent and graded in the direction normal to the plane of the beam curvature. The equations of motion and the related boundary conditions, which include the effects of initial thermal stresses, are derived using the Hamilton’s principle. Differential quadrature method (DQM), as an efficient and accurate numerical method, is adopted to solve the thermoelastic equilibrium equations and the equations of motion. The fast rate of convergence of the method is investigated and the formulations are validated by comparing the results in the limit cases with the available solutions in the literature for isotropic circular curved beams. In addition, for FG circular curved beams with soft simply supported edges, the results are compared with the obtained exact solutions. Then, the effects of temperature rise, boundary conditions, material and geometrical parameters on the natural frequencies are investigated.

Keywords: out of plane, free vibration, curved beams, functionally graded, thermal environment

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Authors: Abderazak Guettaf

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The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

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Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

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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: Abdenour Achour, Kan Chen, Mike Reece, Zhaorong Huang

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Here we report the synthesis of pure and cost effective of BiCuSeO by a flux method in air, and the enhancement of the thermoelectric performance by Cs doping. The comparison between our synthesis and the usual vacuum furnace method has been studied for the pristine oxyselenides BiCuSeO. We report for very high Seebeck coefficients up to 516 μV K⁻¹ at room temperature with the electrical conductivity of 5.20 S cm⁻¹ which lead to a high power factor of 140 µWm⁻¹K⁻². We also report at the high temperatures the lowest thermal conductivity value of 0.42 µWm⁻¹K⁻¹. Upon doping with Cs, enhanced electrical conductivity coupled with a moderate Seebeck coefficient lead to a power factor of 338 µWm⁻¹K⁻² at 682 K. Moreover, it shows a very low thermal conductivity in the temperature range of 300 to 682 K (0.75 to 0.35 Wm⁻¹K⁻¹). By optimizing the power factor and reducing the thermal conductivity, this results in a high ZT of ~ 0.66 at 682 K for Bi0.995Cs0.005CuSeO.

Keywords: BiCuSeO, Cs doping, thermoelectric, oxyselenide

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Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Hossein Mottaghi T., Amir R. Masoodi

Abstract:

This study presents a finite curved element for analyzing the static behavior of curved beams within the elastic range. The objective is to enhance accuracy while reducing the number of elements by incorporating first-order shear deformations of Timoshenko beams. Initially, finite element formulations are developed by considering polynomial initial functions for axial, shear, and rotational deformations for a three-node element. Subsequently, nodal interpolation functions for this element are derived, followed by the construction of the element stiffness matrix. To enable the utilization of the stiffness matrix in the static analysis of curved beams, the constructed matrix in the local coordinates of the element is transformed to the global coordinate system using the rotation matrix. A numerical benchmark example is investigated to assess the accuracy and effectiveness of this method. Moreover, the influence of spring stiffness on the rotation of the endpoint of a clamped beam is examined by substituting each support reaction of the beam with a spring. In the parametric study, the effect of the central angle of the beam on the rotation of the beam's endpoint in a cantilever beam under a concentrated load is examined. This research encompasses various mechanical, geometrical, and boundary configurations to evaluate the static characteristics of curved beams, thus providing valuable insights for their analysis and examination.

Keywords: curved beam, finite element method, first-order shear deformation theory, elastic support

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Authors: M. Nemer, E. I. Konukseven

Abstract:

In this paper, a motion generation algorithm for a six Degrees of Freedom (DoF) robotic hand in a static environment is presented. The purpose of developing this method is to be used in the path generation of the end-effector for edge finishing and inspection processes by utilizing the CAD model of the considered workpiece. Nonetheless, the proposed algorithm may be extended to be applicable for other similar manufacturing processes. A software package programmed in the application programming interface (API) of SolidWorks generates tool path data for the robot. The proposed method significantly simplifies the given problem, resulting in a reduction in the CPU time needed to generate the path, and offers an efficient overall solution. The ABB IRB2000 robot is chosen for executing the generated tool path.

Keywords: CAD-based tools, edge deburring, edge scanning, offline programming, path generation

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Authors: Bhavita S. Dave, Chandresh H. Solanki, Atul K. Desai

Abstract:

Soils of Greater Himalayas mostly pertain to Leh & Ladakh, Lahaul & Sppiti, & high reaches to Uttarakhand. The moisture regime is aridic. The arid zone starts from Baralacha pass in Lahaul and covers the entire Spiti valley in the district of Lahaul & Spiti, Himachal Pradesh of India. Here, the present study is an attempt to determine the suction value of soil collected from the arid zone of Spiti valley for different freezing-thawing cycles considering the climate ranges of Spiti valley. Suction is the basic and most important parameter which influences the behavior of unsaturated soil. It is essential to determine the suction value of unsaturated soil before other tests like shear test, and permeability. Basically, it is the negative pore water pressure in partially saturated soil measured in terms of the height of the water column. The filter paper method has been used for the study as an economical approach to evaluate suction. It is the only method from which both contact and non-contact suction can be deduced. In this study, soil specimens were subjected to 0, 1, 3, & 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and soil freezing characteristic curves (SFCC) were formulated for all F-T cycles. The result data collected from the experiments have shown best-fitted values using Fredlund & Xing model for each SFCC.

Keywords: suction, arid region soil, soil freezing characteristic curve, freezing-thawing cycle

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Izian Abd. Karim, Kachalla Mohammed, Nora Farah Abd Aznieta Aziz, Law Teik Hua

Abstract:

The economic use and ease of construction of profiled deck composite slab is marred with the complex and un-economic strength verification required for the serviceability and general safety considerations. Beside these, albeit factors such as shear span length, deck geometries and mechanical frictions greatly influence the longitudinal shear strength, that determines the ultimate strength of profiled deck composite slab, and number of methods available for its determination; partial shear and slope-intercept are the two methods according to Euro-code 4 provision. However, the complexity associated with shear behavior of profiled deck composite slab, the use of these methods in determining the load carrying capacities of such slab yields different and conflicting values. This couple with the time and cost constraint associated with the strength verification is a source of concern that draws more attentions nowadays, the issue is critical. Treating some of these known shear strength influencing factors as random variables, the load carrying capacity violation of profiled deck composite slab from the use of the two-methods defined according to Euro-code 4 are determined using reliability approach, and comparatively studied. The study reveals safety values from the use of m-k method shows good standing compared with that from the partial shear method.

Keywords: composite slab, first order reliability method, longitudinal shear, partial shear connection, slope-intercept

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Authors: Warjito, Kevin Geraldo, Budiarso, Muhammad Mizan, Rafi Adhi Pranata, Farhan Rizqi Syahnakri

Abstract:

According to data from 2021, the number of households in Indonesia that have access to on-grid electricity is claimed to have reached 99.28%, which means that around 0.7% of Indonesia's population (1.95 million people) still have no proper access to electricity and 38.1% of it comes from remote areas in Nusa Tenggara Timur. Remote areas are classified as areas with a small population of 30 to 60 families, have limited infrastructure, have scarce access to electricity and clean water, have a relatively weak economy, are behind in access to technological innovation, and earn a living mostly as farmers or fishermen. These people still need electricity but can’t afford the high cost of electricity from national on-grid sources. To overcome this, it is proposed that a hydroelectric power plant driven by a pico-hydro turbine with an undershot water wheel will be a suitable pico-hydro turbine technology because of the design, materials and installation of the turbine that is believed to be easier (i.e., operational and maintenance) and cheaper (i.e., investment and operating costs) than any other type. The comparative study of the angle of the undershot water wheel blades will be discussed comprehensively. This study will look into the best variation of curved blades on an undershot water wheel that produces maximum hydraulic efficiency. In this study, the blade angles were varied by 180 ̊, 160 ̊, and 140 ̊. Two methods of analysis will be used, which are analytical and numerical methods. The analytical method will be based on calculations of the amount of torque and rotational speed of the turbine, which is used to obtain the input and output power of the turbine. Whereas the numerical method will use the ANSYS application to simulate the flow during the collision with the designed turbine blades. It can be concluded, based on the analytical and numerical methods, that the best angle for the blade is 140 ̊, with an efficiency of 43.52% for the analytical method and 37.15% for the numerical method.

Keywords: pico hydro, undershot waterwheel, blade angle, computational fluid dynamics

Procedia PDF Downloads 65