Search results for: twin delayed deep deterministic policy gradient.

Authors: Ahmet Güven, Ö. Özgür Bozkurt, Oya Kalıpsız

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Number of documents being created increases at an increasing pace while most of them being in already known topics and little of them introducing new concepts. This fact has started a new era in information retrieval discipline where the requirements have their own specialties. That is digging into topics and concepts and finding out subtopics or relations between topics. Up to now IR researches were interested in retrieving documents about a general topic or clustering documents under generic subjects. However these conventional approaches can-t go deep into content of documents which makes it difficult for people to reach to right documents they were searching. So we need new ways of mining document sets where the critic point is to know much about the contents of the documents. As a solution we are proposing to enhance LSI, one of the proven IR techniques by supporting its vector space with n-gram forms of words. Positive results we have obtained are shown in two different application area of IR domain; querying a document database, clustering documents in the document database.

Keywords: Document clustering, Information Extraction, Information Retrieval, LSI, n-gram.

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Authors: Anjana Goen, D. C. Tiwari

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Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.

Keywords: Evolvable hardware (EHW), Functional Electrical Simulation (FES), Hidden Markov Model (HMM), Hjorth Time Domain (HTD).

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Authors: Nidhal Jamia, Sami El-Borgi

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In this paper, the problem of a mixed-Mode crack embedded in an infinite medium made of a functionally graded piezoelectric material (FGPM) with crack surfaces subjected to electro-mechanical loadings is investigated. Eringen’s non-local theory of elasticity is adopted to formulate the governing electro-elastic equations. The properties of the piezoelectric material are assumed to vary exponentially along a perpendicular plane to the crack. Using Fourier transform, three integral equations are obtained in which the unknown variables are the jumps of mechanical displacements and electric potentials across the crack surfaces. To solve the integral equations, the unknowns are directly expanded as a series of Jacobi polynomials, and the resulting equations solved using the Schmidt method. In contrast to the classical solutions based on the local theory, it is found that no mechanical stress and electric displacement singularities are present at the crack tips when nonlocal theory is employed to investigate the problem. A direct benefit is the ability to use the calculated maximum stress as a fracture criterion. The primary objective of this study is to investigate the effects of crack length, material gradient parameter describing FGPMs, and lattice parameter on the mechanical stress and electric displacement field near crack tips.

Keywords: Functionally graded piezoelectric material, mixed-mode crack, non-local theory, Schmidt method.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

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A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

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Authors: M. V. A. Raju Bahubalendruni, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

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Achieving an appropriate assembly sequence needs deep verification for its physical feasibility. For this purpose, industrial engineers use several assembly predicates; namely, liaison, geometric feasibility, stability and mechanical feasibility. However, testing an assembly sequence for these predicates requires huge assembly information. Extracting such assembly information from an assembled product is a time consuming and highly skillful task with complex reasoning methods. In this paper, computer aided methods are proposed to extract all the necessary assembly information from computer aided design (CAD) environment in order to perform the assembly sequence planning efficiently. These methods use preliminary capabilities of three-dimensional solid modelling and assembly modelling methods used in CAD software considering equilibrium laws of physical bodies.

Keywords: Assembly automation, assembly attributes, assembly sequence generation, computer aided design.

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Authors: V. Vargas-Alejo, L. E. Montero-Moguel

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Understanding the concept of function has been important in mathematics education for many years. In this study, the models built by a group of five business administration and accounting undergraduate students when carrying out a population growth activity are analyzed. The theoretical framework is the Models and Modeling Perspective. The results show how the students included tables, graphics, and algebraic representations in their models. Using technology was useful to interpret, describe, and predict the situation. The first model, the students built to describe the situation, was linear. After that, they modified and refined their ways of thinking; finally, they created exponential growth. Modeling the activity was useful to deep on mathematical concepts such as covariation, rate of change, and exponential function also to differentiate between linear and exponential growth.

Keywords: Covariation reasoning, exponential function, modeling, representations.

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: Causal relation identification, convolutional neural networks, natural Language Processing, Machine Learning.

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Authors: S. A. Moeini, M. T.Ahmadian

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Structural behavior of ring stiffened thick walled cylinders made of functionally graded materials (FGMs) is investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture of metal and ceramic. The gradient compositional variation of the constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction. A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and modal behavior of stiffened FGM thick walled cylinders. By using this super-element the number of elements, which are needed for modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by comparison to finite element formulation with conventional elements. Comparison indicates a good conformity between results.

Keywords: FGMs, Modal analysis, Static analysis, Stiffened cylinders.

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Authors: Sudip Dasgupta, Debosmita Pani, Kanchan Maji

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Calcium Phosphate Cement (CPC) due to its high bioactivity and optimum bioresorbability shows excellent bone regeneration capability. Despite it has limited applications as bone implant due to its macro-porous microstructure causing its poor mechanical strength. The reinforcement of apatitic CPCs with biocompatible fibre glass phase is an attractive area of research to improve upon its mechanical strength. Here, we study the setting behaviour of Si-doped and un-doped α tri calcium phosphate (α - TCP) based CPC and its reinforcement with addition of E-glass fibre. Alpha Tri calcium phosphate powders were prepared by solid state sintering of CaCO3 , CaHPO4 and Tetra Ethyl Ortho Silicate (TEOS) was used as silicon source to synthesize Si doped α-TCP powders. Both initial and final setting time of the developed cement was delayed because of Si addition. Crystalline phases of HA (JCPDS 9- 432), α-TCP (JCPDS 29-359) and β-TCP (JCPDS 9-169) were detected in the X-ray diffraction (XRD) pattern after immersion of CPC in simulated body fluid (SBF) for 0 hours to 10 days. As Si incorporation in the crystal lattice stabilized the TCP phase, Si doped CPC showed little slower rate of conversion into HA phase as compared to un-doped CPC. The SEM image of the microstructure of hardened CPC showed lower grain size of HA in un-doped CPC because of premature setting and faster hydrolysis of un-doped CPC in SBF as compared that in Si-doped CPC. Premature setting caused generation of micro and macro porosity in un-doped CPC structure which resulted in its lower mechanical strength as compared to that in Si-doped CPC. It was found that addition of 10 wt% of E-glass fibre into Si-doped α-TCP increased the average DTS of CPC from 8 MPa to 15 MPa as the fibres could resists the propagation of crack by deflecting the crack tip. Our study shows that biocompatible E-glass fibre in optimum proportion in CPC matrix can enhance the mechanical strength of CPC without affecting its biocompatibility. 

Keywords: Calcium phosphate cement, biocompatibility, e-glass fibre, diametral tensile strength.

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Authors: Paitoon Kraipornsak

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The recent global financial problem urges government to play role in stimulating the economy due to the fact that private sector has little ability to purchase during the recession. A concerned question is whether the increased government spending crowds out private consumption and whether it helps stimulate the economy. If the government spending policy is effective; the private consumption is expected to increase and can compensate the recent extra government expense. In this study, the government spending is categorized into government consumption spending and government capital spending. The study firstly examines consumer consumption along the line with the demand function in microeconomic theory. Three categories of private consumption are used in the study. Those are food consumption, non food consumption, and services consumption. The dynamic Almost Ideal Demand System of the three categories of the private consumption is estimated using the Vector Error Correction Mechanism model. The estimated model indicates the substituting effects (negative impacts) of the government consumption spending on budget shares of private non food consumption and of the government capital spending on budget share of private food consumption, respectively. Nevertheless the result does not necessarily indicate whether the negative effects of changes in the budget shares of the non food and the food consumption means fallen total private consumption. Microeconomic consumer demand analysis clearly indicates changes in component structure of aggregate expenditure in the economy as a result of the government spending policy. The macroeconomic concept of aggregate demand comprising consumption, investment, government spending (the government consumption spending and the government capital spending), export, and import are used to estimate for their relationship using the Vector Error Correction Mechanism model. The macroeconomic study found no effect of the government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP. Therefore no crowding out effect of the government spending is found on the private consumption but it is ineffective and even inefficient expenditure as found reducing growth of the GDP in the context of Thailand.

Keywords: government consumption spending, governmentcapital spending, private consumption on food, non food, andservices, Vector Error Correction Mechanism, Almost Ideal DemandSystem, substitution effect, complementary effect, consumer demand, aggregate demand

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Prevent abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behaviour analysis, LSTM

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: Edge network, embedded network, MMA, matrix multiplication accelerator and semantic segmentation network.

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Authors: S. E. Musa, N. E. Mohamed, N. A. Ahmed

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In this study, several crossplots of the P-impedance with the lithology logs (gamma ray, neutron porosity, deep resistivity, water saturation and Vp/Vs curves) were made in three available wells, which were drilled in central part of the Blue Nile basin in depths varies from 1460m to 1600m. These crossplots were successful to discriminate between sand and shale when using PImpedance values, and between the wet sand and the pay sand when using both P-impedance and Vp/Vs together. Also some impedance sections were converted to porosity sections using linear formula to characterize the reservoir in terms of porosity. The used crossplots were created on log resolution, while the seismic resolution can identify only the reservoir, unless a 3D seismic angle stacks were available; then it would be easier to identify the pay sand with great confidence; through high resolution seismic inversion and geostatistical approach when using P-impedance and Vp/Vs volumes.

Keywords: Basin, Blue Nile, Inversion, Seismic.

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Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

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Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: Sanitation systems, nano membrane toilet, LCA, stochastic uncertainty analysis, Monte Carlo Simulations, artificial neural network.

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Authors: Treepon Kirdnark

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This paper examines the depiction of Muslim militants in Thai newspapers in 2004. Stuart Hall-s “representation" and “public idioms" are used as theoretical frameworks. Critical Discourse Analysis is employed as a methodology to examine 240 news articles from two leading Thai language newspapers. The results show that the militants are usually labeled as “southern bandits." This suggests that they are just a culprit of the violence in the deep south of Thailand. They are usually described as people who cause turbulence. Consequently, the military have to get rid of them. However, other aspects of the groups such as their political agenda or the failures of the Thai state in dealing with the Malay Muslims were not mention in the news stories. In the time of violence, the researcher argues that this kind of newspaper coverage may help perpetuate the discourse of Malay Muslim, instead of providing fuller picture of the ongoing conflicts.

Keywords: News Discourse, Newspapers, Thailand, Thai Muslims.

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: BERT, chatbot, cryptocurrency, deep learning.

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Authors: Thandokazi Nyangiwe, Christopher Amoah, Charles P. Mukumba

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The South African construction sector is threatened by emerging black business forums called construction mafias. The emergence of the construction mafia has culminated in the disruptions and abandonment of construction sites resulting in the loss of jobs for construction workers. The paper examines the origin of construction mafias and their impact on the construction sector, including the potential ways to cope with their operations. A qualitative research approach was adopted for this study using open-ended interview questions to gather information from 30 key construction industry stakeholders, including contractors, subcontractors, consultants, and the construction project communities. Content and thematic analyses were used to analyses the data collected. The findings suggest that most participants do not fully understand the existence and operations of construction mafias in the construction industry. Construction mafias claim to be part of the local business forums. They disrupt construction projects and demand a certain amount, usually 30% of the construction value. Construction mafias frequently resort to intimidation and violence if their demands are unmet. Their operations have resulted in delayed completion of construction projects, abandonment of projects, and loss of income for the contractor and jobs for the construction workers. The interviews were limited to construction stakeholders. Because of the nature of the mafias’ operations, they could not be accessed for interviews for fear of being identified because of the connotation attached to their role as construction mafias. Construction project owners face disruptions of projects resulting in loss of equipment, materials, and income. Therefore, there is a need to sensitize the construction stakeholders in the construction industry regarding the existence and operations of the construction mafia and the implications on construction project performance and delivery. The findings will give insight into the operations of the construction mafias in the South African construction industry, which has caused disruptions in construction project sites. Stakeholders must find solutions to address the construction mafias’ disruptive actions on construction projects. The study presents an initial inquiry that will come up with how to manage and cope with the growing operations of construction mafias in the South African construction industry.

Keywords: Black business forums, construction mafia, South African construction industry.

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Authors: M. Maronek, J. Barta, P. Palcek, K. Ulrich

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Low carbon deep drawing steel DC 01 according to EN 10130-91 was nitrooxidized in dissociated ammonia at 580°C/45 min and consequently oxidised at 380°C/5 min in vapour of distilled water. Material after nitrooxidation had 54 % increase of yield point, 34 % increase of strength and 10-times increased resistance to atmospheric corrosion in comparison to the material before nitrooxidation. The microstructure of treated material consisted of thin ε-phase layer connected to layer containing precipitated massive needle shaped Fe4N - γ' nitrides. This layer passed to a diffusion layer consisting of fine irregular shaped Fe16N2 - α'' nitrides regularly dispersed in ferritic matrix. Fatigue properties were examined under bending load with frequency of 20 kHz and sinusoidal symmetric cycle. The results confirmed positive influence of nitrooxidation on fatigue properties as fatigue limit of treated material was double in comparison to untreated material.

Keywords: steel sheet, fatigue, nitrooxidation, S-N diagram

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Authors: Michele V. Carbinatto, Wagner Wey Moreira, Myrian Nunomura; Mariana H. C. Tsukamoto, VilmaLeni Nista-Piccolo

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Sports Sciences has been historically supported by the positivism idea of science, especially by the mechanistic/reductionist and becomes a field that views experimentation and measurement as the mayor research domains. The disposition to simplify nature and the world by parts has fragmented and reduced the idea of bodyathletes as machine. In this paper we intent to re-think this perception lined by Complexity Theory. We come with the idea of athletes as a reflexive and active being (corporeity-body). Therefore, the construction of a training that considers the cultural, biological, psychological elements regarding the experience of the human corporal movements in a circumspect and responsible way could bring better chances of accomplishment. In the end, we hope to help coaches understand the intrinsic complexity of the body they are training, how better deal with it, and, in the field of a deep globalization among the different types of knowledge, to respect and accepted the peculiarities of knowledge that comprise this area.

Keywords: Sport science, body, complexity theory, corporeity.

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Authors: Saeed Delara, Kendra MacKay

Abstract:

Varying methodologies are considered for pile design for both Russian and Western approaches. Although both approaches rely on toe and side frictional resistances, different calculation methods are proposed to estimate pile capacity. The Western approach relies on compactness (internal friction angle) of soil for cohesionless soils and undrained shear strength for cohesive soils. The Russian approach relies on grain size for cohesionless soils and liquidity index for cohesive soils. Though most recommended methods in the Western approaches are relatively simple methods to predict pile settlement, the Russian approach provides a detailed method to estimate single pile and pile group settlement. Details to calculate pile axial capacity and settlement using the Russian and Western approaches are discussed and compared against field test results.

Keywords: Pile capacity, pile settlement, Russian approach, western approach.

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Authors: Azam Akbari, Mohammadreza Omidkhah, Jafar Toufighi Darian

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The mesoporous MoO3/γ-Al2O3 catalyst was prepared by incipient wetness impregnation method aiming to investigate the effect of drying method and molybdenum content on the catalyst property and performance towards the oxidation of benzothiophene (BT), dibenzothiophene (DBT) and 4,6-dimethyle dibenzothiophene (4,6-DMDBT) with H2O2 for deep oxidative desulfurization of diesel fuel. The catalyst was characterized by XRD, BET, BJH and SEM method. The catalyst with 10wt.% and 15wt.% Mo content represent same optimum performance for DBT and 4,6-DMDBT removal, but a catalyst with 10wt.% Mo has higher efficiency than 15wt.% Mo for BT conversion. The SEM images show that use of rotary evaporator in drying step reaches a more homogenous impregnation. The oxidation reactivity of different sulfur compounds was studied which followed the order of DBT>4,6-DMDBT>>BT.

Keywords: desulfurization, oxidation, MoO3/Al2O3 catalyst

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Authors: James Patrick A. Diaz, Raul E. Ramboyong

Abstract:

Background: Hypertensive response during maximal exercise test provides important information on the level of blood pressure control and evaluation of treatment. Method: A single center retrospective descriptive study was conducted among 117 young (aged 20 to 40) and middle age (aged 40 to 65) hypertensive patients, who underwent treadmill stress test. Currently on maintenance frontline medication either monotherapy (Angiotensin-converting enzyme inhibitor/Angiotensin receptor blocker [ACEi/ARB], Calcium channel blocker [CCB], Diuretic - Hydrochlorthiazide [HCTZ]) or combination therapy (ARB+CCB, ARB+HCTZ), who attained a maximal exercise on treadmill stress test (TMST) with hypertensive response (systolic blood pressure: male >210 mm Hg, female >190 mm Hg, diastolic blood pressure >100 mmHg, or increase of >10 mm Hg at any time during the test), on Bruce and Modified Bruce protocol. Exaggerated blood pressure response during exercise (systolic [SBP] and diastolic [DBP]), peak exercise blood pressure (SBP and DBP), recovery period (SBP and DBP) and test for ischemia and their antihypertensive medication/s were investigated. Analysis of variance and chi-square test were used for statistical analysis. Results: Hypertensive responses on maximal exercise test were seen mostly among female population (P < 0.000) and middle age (P < 0.000) patients. Exaggerated diastolic blood pressure responses were significantly lower in patients who were taking CCB (P < 0.004). A longer recovery period that showed a delayed decline in SBP was observed in patients taking ARB+HCTZ (P < 0.036). There were no significant differences in the level of exaggerated systolic blood pressure response and during peak exercise (both systolic and diastolic) in patients using either monotherapy or combination antihypertensives. Conclusion: Calcium channel blockers provided lower exaggerated diastolic BP response during maximal exercise test in hypertensive middle age patients. Patients on combination therapy using ARB+HCTZ exhibited a longer recovery period of systolic blood pressure.

Keywords: Antihypertensive, exercise test, hypertension, hypertensive response.

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.

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Authors: Mohd. Hasan, Ajmal Kafeel, S. D. Pable

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Ultra-low-power (ULP) circuits have received widespread attention due to the rapid growth of biomedical applications and Battery-less Electronics. Subthreshold region of transistor operation is used in ULP circuits. Major research challenge in the subthreshold operating region is to extract the ULP benefits with minimal degradation in speed and robustness. Process, Voltage and Temperature (PVT) variations significantly affect the performance of subthreshold circuits. Designed performance parameters of ULP circuits may vary largely due to temperature variations. Hence, this paper investigates the effect of temperature variation on device and circuit performance parameters at different biasing voltages in the subthreshold region. Simulation results clearly demonstrate that in deep subthreshold and near threshold voltage regions, performance parameters are significantly affected whereas in moderate subthreshold region, subthreshold circuits are more immune to temperature variations. This establishes that moderate subthreshold region is ideal for temperature immune circuits.

Keywords: Subthreshold, temperature variations, ultralow power.

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Authors: Surita Maini

Abstract:

There are many perceived advantages of microwave ablation have driven researchers to develop innovative antennas to effectively treat deep-seated, non-resectable hepatic tumors. In this paper a coaxial antenna with a miniaturized sleeve choke has been discussed for microwave interstitial ablation therapy, in order to reduce backward heating effects irrespective of the insertion depth into the tissue. Two dimensional Finite Element Method (FEM) is used to simulate and measure the results of miniaturized sleeve choke antenna. This paper emphasizes the importance of factors that can affect simulation accuracy, which include mesh resolution, surface heating and reflection coefficient. Quarter wavelength choke effectiveness has been discussed by comparing it with the unchoked antenna with same dimensions.

Keywords: Microwave ablation, tumor, Finite Element Method, Coaxial slot antenna, Coaxial dipole antenna.

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Authors: M. Kumpugdee-Vollrath, M. Tabatabaeifar, M. Helmis

Abstract:

Shellac is a natural polyester resin secreted by insects. Pectins are natural, non-toxic and water-soluble polysaccharides extracted from the peels of citrus fruits or the leftovers of apples. Both polymers are allowed for the use in the pharmaceutical industry and as a food additive. SSB Aquagold® is the aqueous solution of shellac and can be used for a coating process as an enteric or controlled drug release polymer. In this study, tablets containing 10 mg methylene blue as a model drug were prepared with a rotary press. Those tablets were coated with mixtures of shellac and one of the pectin different types (i.e. CU 201, CU 501, CU 701 and CU 020) mostly in a 2:1 ratio or with pure shellac in a small scale fluidized bed apparatus. A stable, simple and reproducible three-stage coating process was successfully developed. The drug contents of the coated tablets were determined using UV-VIS spectrophotometer. The characterization of the surface and the film thickness were performed with the scanning electron microscopy (SEM) and the light microscopy. Release studies were performed in a dissolution apparatus with a basket. Most of the formulations were enteric coated. The dissolution profiles showed a delayed or sustained release with a lagtime of at least 4 h. Dissolution profiles of coated tablets with pure shellac had a very long lagtime ranging from 13 to 17.9 h and the slopes were quite high. The duration of the lagtime and the slope of the dissolution profiles could be adjusted by adding the proper type of pectin to the shellac formulation and by variation of the coating amount. In order to apply a coating formulation as a colon delivery system, the prepared film should be resistant against gastric fluid for at least 2 h and against intestinal fluid for 4-6 h. The required delay time was gained with most of the shellac-pectin polymer mixtures. The release profiles were fitted with the modified model of the Korsmeyer-Peppas equation and the Hixson-Crowell model. A correlation coefficient (R²)> 0.99 was obtained by Korsmeyer-Peppas equation.

Keywords: Shellac, pectin, coating, fluidized bed, release, colon delivery system, kinetic, SEM, methylene blue.

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Authors: Oluwatoyin D. Kolawole, Oarabile Mogobe, Lapologang Magole

Abstract:

Although many factors play a significant role in agricultural production and productivity, the importance of soil fertility cannot be underestimated. The extent to which small farmers are able to manage the fertility of their farmlands is crucial in agricultural development particularly in sub-Saharan Africa (SSA).  This paper assesses the nutrient status of selected farmers’ fields in relation to how government policy addresses the allocation of and access to agricultural inputs (e.g. chemical fertilizers) in a unique social-ecological environment of the Okavango Delta in northern Botswana. It also analyses small farmers and soil scientists’ perceptions about the political economy of integrated soil fertility management (ISFM) in the area. A multi-stage sampling procedure was used to elicit quantitative and qualitative information from 228 farmers and 9 soil researchers through the use of interview schedules and questionnaires, respectively. Knowledge validation workshops and focus group discussions (FGDs) were also used to collect qualitative data from farmers. Thirty-three composite soil samples were collected from 30 farmers’ plots in three farming communities of Makalamabedi, Nokaneng and Mohembo for laboratory analysis. While meeting points exist, farmers and scientists have divergent perspectives on soil fertility management. Laboratory analysis carried out shows that most soils in the wetland and the adjoining dry-land/upland surroundings are low in essential nutrients as well as in cation exchange capacity (CEC). Although results suggest the identification and use of appropriate inorganic fertilizers, the low CEC is an indication that holistic cultural practices, which are beyond mere chemical fertilizations, are critical and more desirable for improved soil health and sustainable livelihoods in the area. Farmers’ age (t= -0.728; p≤0.10); their perceptions about the political economy (t = -0.485; p≤0.01) of ISFM; and their preference for the use of local knowledge in soil fertility management (t = -10.254; p≤0.01) had a significant relationship with how they perceived their involvement in the implementation of ISFM.

Keywords: Access, Botswana, ecology, inputs, Okavango Delta, policy, scientists, small farmers, soil fertility.

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Authors: Karanja Kibicho, Anthony Sayers

Abstract:

Due to adverse pressure gradient along the diverging walls of wide-angled diffusers, the attached flow separates from one wall and remains attached permanently to the other wall in a process called stalling. Stalled diffusers render the whole fluid flow system, in which they are part of, very inefficient. There is then an engineering need to try to understand the whole process of diffuser stall if any meaningful attempts to improve on diffuser efficiency are to be made. In this regard, this paper provides a data bank contribution for the mean flow-field in wide-angled diffusers where the complete velocity and static pressure fields, and pressure recovery data for diffusers in the fully stalled flow regime are experimentally measured. The measurements were carried out at Reynolds numbers between 1.07×105 and 2.14×105 based on inlet hydraulic diameter and centreline velocity for diffusers whose divergence angles were between 30Ôùª and 50Ôùª. Variation of Reynolds number did not significantly affect the velocity and static pressure profiles. The wall static pressure recovery was found to be more sensitive to changes in the Reynolds number. By increasing the velocity from 10 m/s to 20 m/s, the wall static pressure recovery increased by 8.31%. However, as the divergence angle was increased, a similar increase in the Reynolds number resulted in a higher percentage increase in pressure recovery. Experimental results showed that regardless of the wall to which the flow was attached, both the velocity and pressure fields were replicated with discrepancies below 2%.

Keywords: Two-dimensional, wide-angled, diffuser, stall, separated flows, subsonic flows, diffuser flow regimes

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Authors: Laveen Sundararaj, Palanisamy Vellaiyan

Abstract:

Delay and Disruption Tolerant Networking is part of the Inter Planetary Internet with primary application being Deep Space Networks. Its Terrestrial form has interesting research applications such as Alagappa University Delay Tolerant Water Monitoring Network which doubles as test beds for improvising its routing scheme. DTNs depend on node mobility to deliver packets using a store-carry-and forward paradigm. Throwboxes are small and inexpensive stationary devices equipped with wireless interfaces and storage. We propose the use of Throwboxes to enhance the contact opportunities of the nodes and hence improve the Throughput. The enhancement is evaluated using Alunivdtnsim, a desktop simulator in C language and the results are graphically presented.

Keywords: Alunivdtnsim – Alagappa University Delay TolerantNetwork Simulator, AUDTWMN- Alagappa University DelayTolerant Water Monitoring Network, DTN - Delay and DisruptionTolerant Networking, LTP – Lick Lider Transmission Protocol.

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