Search results for: experimental test

Authors: Sh.Khalilarya, H.Oryani, S.Jafarmadar, H.Khatamnezhad, A.Nemati

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Understanding of how and where NOx formation occurs in industrial burner is very important for efficient and clean operation of utility burners. Also the importance of this problem is mainly due to its relation to the pollutants produced by more burners used widely of gas turbine in thermal power plants and glass and steel industry. In this article, a numerical model of an industrial burner operating in MILD combustion is validated with experimental data.. Then influence of air flow rate and air temperature on combustor temperature profiles and NOX product are investigated. In order to modification this study reports on the effects of fuel and air dilution (with inert gases H2O, CO2, N2), and also influence of lean-premixed of fuel, on the temperature profiles and NOX emission. Conservation equations of mass, momentum and energy, and transport equations of species concentrations, turbulence, combustion and radiation modeling in addition to NO modeling equations were solved together to present temperature and NO distribution inside the burner. The results shows that dilution, cause to a reduction in value of temperature and NOX emission, and suppresses any flame propagation inside the furnace and made the flame inside the furnace invisible. Dilution with H2O rather than N2 and CO2 decreases further the value of the NOX. Also with raise of lean-premix level, local temperature of burner and the value of NOX product are decreases because of premixing prevents local “hot spots" within the combustor volume that can lead to significant NOx formation. Also leanpremixing of fuel with air cause to amount of air in reaction zone is reach more than amount that supplied as is actually needed to burn the fuel and this act lead to limiting NOx formation

Keywords: Mild combustion, Flameless, Numerical simulation, Burner, CFD.

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluates the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: lexical semantics, feature representation, semantic decision, convolutional neural network, electronic medical record

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Authors: David Halley, Tyra Oseng-Rees, Luca Pagano, Juan A Ferriz-Papi

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Recycled glass material is made from 100% recycled bottle glass and consumes less energy than re-melt technology. It also uses no additives in the manufacturing process allowing the recycled glass material, in principal, to go back to the recycling stream after end-of-use, contributing to the circular economy with a low ecological impact. The aim of this paper is to investigate the procedure for testing the recycled glass material for impact resistance, so it can be applied to pavements and other surfaces which are at risk of impact during service. A review of different impact test procedures for construction materials was undertaken, comparing methodologies and international standards applied to other materials such as natural stone, ceramics and glass. A drop weight impact testing machine was designed and manufactured in-house to perform these tests. As a case study, samples of the recycled glass material were manufactured with two different thicknesses and tested. The impact energy was calculated theoretically, obtaining results with 5 and 10 J. The results on the material were subsequently discussed. Improvements on the procedure can be made using high speed video technology to calculate velocity just before and immediately after the impact to know the absorbed energy. The initial results obtained in this procedure were positive although repeatability needs to be developed to obtain a correlation of results and finally be able to validate the procedure. The experiment with samples showed the practicality of this procedure and application to the recycled glass material impact testing although further research needs to be developed.

Keywords: Construction materials, drop weight impact, impact testing, recycled glass.

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: Stacking, multi-layers, ensemble, multi-class.

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Authors: Yahia Salah, Med Lassaad Kaddachi, Rached Tourki

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This paper presents the design, implementation and evaluation of a micro-network, or Network-on-Chip (NoC), based on a generic pipeline router architecture. The router is designed to efficiently support traffic generated by multimedia applications on embedded multi-core systems. It employs a simplest routing mechanism and implements the round-robin scheduling strategy to resolve output port contentions and minimize latency. A virtual channel flow control is applied to avoid the head-of-line blocking problem and enhance performance in the NoC. The hardware design of the router architecture has been implemented at the register transfer level; its functionality is evaluated in the case of the two dimensional Mesh/Torus topology, and performance results are derived from ModelSim simulator and Xilinx ISE 9.2i synthesis tool. An example of a multi-core image processing system utilizing the NoC structure has been implemented and validated to demonstrate the capability of the proposed micro-network architecture. To reduce complexity of the image compression and decompression architecture, the system use image processing algorithm based on classical discrete cosine transform with an efficient zonal processing approach. The experimental results have confirmed that both the proposed image compression scheme and NoC architecture can achieve a reasonable image quality with lower processing time.

Keywords: Generic Pipeline Network-on-Chip Router Architecture, JPEG Image Compression, FPGA Hardware Implementation, Performance Evaluation.

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Authors: Arshad Javaid, Syeda F. Naqvi

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Macrophomina phaseolina is a devastating soil-borne fungal plant pathogen that causes charcoal rot disease in many economically important crops worldwide. So far, no registered fungicide is available against this plant pathogen. This study was planned to examine the antifungal activity of an allelopathic grass Cenchrus pennisetiformis (Hochst. & Steud.) Wipff. for the management of M. phaseolina isolated from cowpea [Vigna unguiculata (L.) Walp.] plants suffering from charcoal rot disease. Different parts of the plants viz. inflorescence, shoot and root were extracted in methanol. Laboratory bioassays were carried out using different concentrations (0, 0.5, 1.0, …, 3.0 g mL-1) of methanolic extracts of the test allelopathic grass species to assess the antifungal activity against the pathogen. In general, extracts of all parts of the grass exhibited antifungal activity. All the concentrations of methanolic extracts of shoot and root significantly reduced fungal biomass by 20–73% and 40–80%, respectively. Methanolic shoot extract was fractionated using n-hexane, chloroform, ethyl acetate and n-butanol. Different concentrations of these fractions (3.125, 6.25, …, 200 mg mL-1) were analyzed for their antifungal activity. All the concentrations of n-hexane fraction significantly reduced fungal biomass by 15–96% over corresponding control treatments. Higher concentrations (12.5–200 mg mL-1) of chloroform, ethyl acetate and n-butanol also reduced the fungal biomass significantly by 29–100%, 46–100% and 24–100%, respectively.

Keywords: Antifungal activity, Cenchrus pennisetiformis, Macrophomina phaseolina, natural fungicides

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Authors: Nattapong Techarattanased

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The purposes of this research are to make comparisons in respect of the behaviors on the use of the services of metered taxi classified by the demographic factor and to study the influence of the recognition on service quality having the effect on usage behaviors of metered taxi services of consumers in Bangkok Metropolitan Areas. The samples used in this research were 400 metered taxi service users in Bangkok Metropolitan Areas and questionnaire was used as the tool for collecting the data. Analysis statistics are mean and multiple regression analysis. Results of the research revealed that the consumers recognize the overall quality of services in each aspect include tangible aspects of the service, responses to customers, assurance on the confidence, understanding and knowing of customers which is rated at the moderate level except the aspect of the assurance on the confidence and trustworthiness which are rated at a high level. For the result of hypothetical test, it is found that the quality in providing the services on the aspect of the assurance given to the customers has the effect on the usage behaviors of metered taxi services and the aspect of the frequency on the use of the services per month which in this connection. Such variable can forecast at one point nine percent (1.9%). In addition, quality in providing the services and the aspect of the responses to customers have the effect on the behaviors on the use of metered taxi services on the aspect of the expenses on the use of services per month which in this connection, such variable can forecast at two point one percent (2.1%).

Keywords: Consumer behavior, metered taxi, satisfaction, service quality.

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Authors: Vladyslav Povoroznyuk, Anna Musiienko, Nataliia Dzerovych, Roksolana Povoroznyuk, Oksana Ivanyk

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Deficiency and insufficiency of Vitamin D is a pandemic of the 21^st century. Obesity patients have a lower level of vitamin D, but the literature data are contradictory. The purpose of this study is to investigate deficiency and insufficiency vitamin D in postmenopausal women with obesity. We examined 1007 women aged 50-89 years. Mean age was 65.74±8.61 years; mean height was 1.61±0.07 m; mean weight was 70.65±13.50 kg; mean body mass index was 27.27±4.86 kg/m², and mean 25(OH) D levels in serum was 26.00±12.00 nmol/l. The women were divided into the following six groups depending on body mass index: I group – 338 women with normal body weight, II group – 16 women with insufficient body weight, III group – 382 women with excessive body weight, IV group – 199 women with obesity of class I, V group – 60 women with obesity of class II, and VI group – 12 women with obesity of class III. Level of 25(OH)D in serum was measured by means of an electrochemiluminescent method - Elecsys 2010 analyzer (Roche Diagnostics, Germany) and cobas test-systems. 34.4% of the examined women have deficiency of vitamin D and 31.4% insufficiency. Women with obesity of class I (23.60±10.24 ng/ml) and obese of class II (22.38±10.34 ng/ml) had significantly lower levels of 25 (OH) D compared to women with normal body weight (28.24±12.99 ng/ml), p=0.00003. In women with obesity, BMI significantly influences vitamin D level, and this influence does not depend on the season.

Keywords: Obesity, body mass index, vitamin D deficiency/insufficiency, postmenopausal women, age.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: M. Javanmard

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This study was aimed at analyzing the effects of packaging (MAP) and preservation conditions on the packaged fresh walnut kernel quality. The central composite plan was used for evaluating the effect of oxygen (0–10%), carbon dioxide (0-10%), and temperature (4-26 °C) on qualitative characteristics of walnut kernels. Also, the response level technique was used to find the optimal conditions for interactive effects of factors, as well as estimating the best conditions of process using least amount of testing. Measured qualitative parameters were: peroxide index, color, decreased weight, mould and yeast counting test, and sensory evaluation. The results showed that the defined model for peroxide index, color, weight loss, and sensory evaluation is significant (p < 0.001), so that increase of temperature causes the peroxide value, color variation, and weight loss to increase and it reduces the overall acceptability of walnut kernels. An increase in oxygen percentage caused the color variation level and peroxide value to increase and resulted in lower overall acceptability of the walnuts. An increase in CO₂ percentage caused the peroxide value to decrease, but did not significantly affect other indices (p ≥ 0.05). Mould and yeast were not found in any samples. Optimal packaging conditions to achieve maximum quality of walnuts include: 1.46% oxygen, 10% carbon dioxide, and temperature of 4 °C.

Keywords: Shelled walnut, MAP, quality, storage temperature.

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Authors: O. A. Anjola, M. A. Adejobi, L. A Tijani

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This study was conducted to investigate the effects of brewer spent grain (BSG) on growth performance and serum biochemistry characteristics of blood of broilers chickens. Three hundred and fifteen (4 weeks old) Oba – Marshall Broilers were used for the experiment. Five experimental diets were formulated with diet 1 (T1) containing 100% soya bean meal as the control, Diet 2, 3, 4 and 5 had BSG as replacement for soya bean meal at 0%, 36%, 57%, 76% and 100% respectively. The birds were allocated into each dietary group in a completely randomized design with 63 chicks in 3 replicates of 21 chicks each. The birds were offered these diets ad libitum from four weeks old to nine weeks old (35 days). Feed intake, body weight, weight gain, and feed conversion ratio (FCR) were assessed. Blood samples were also collected to examine the effect of BSG waste on hematology and serum biochemistry of broilers. Result indicated that BSG did not significantly (P>0.05) affect feed intake and weight gain. However, FCR and final weight of finishing broilers differs significantly (P<0.05) among treatments. The blood hematology and serum biochemistry indices did not follow a particular trend. Cholesterol concentration reduced with increasing level of BSG in the diet. Hb, RBC, WBC, neutrophils, lymphocytes, heterophiles and MCHC were significant (P<0.05) while MHC and MVC were not significantly (P>0.05) affected by BSG in diets. serum total protein, albumin, and cholesterol concentration also showed significance (P<0.05) difference. Thus, BSG can replace soya bean meal up to 14% in the broiler finisher diet without deleterious effect on the growth, hematology and the serum biochemistry of broiler chicken.

Keywords: Broilers, growth performance, hematology, serum biochemistry.

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Authors: Mohammad Heidari

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Horizontal wells are proven to be better producers because they can be extended for a long distance in the pay zone. Engineers have the technical means to forecast the well productivity for a given horizontal length. However, experiences have shown that the actual production rate is often significantly less than that of forecasted. It is a difficult task, if not impossible to identify the real reason why a horizontal well is not producing what was forecasted. Often the source of problem lies in the drilling of horizontal section such as permeability reduction in the pay zone due to mud invasion or snaky well patterns created during drilling. Although drillers aim to drill a constant inclination hole in the pay zone, the more frequent outcome is a sinusoidal wellbore trajectory. The two factors, which play an important role in wellbore tortuosity, are the inclination and side force at bit. A constant inclination horizontal well can only be drilled if the bit face is maintained perpendicular to longitudinal axis of bottom hole assembly (BHA) while keeping the side force nil at the bit. This approach assumes that there exists no formation force at bit. Hence, an appropriate BHA can be designed if bit side force and bit tilt are determined accurately. The Artificial Neural Network (ANN) is superior to existing analytical techniques. In this study, the neural networks have been employed as a general approximation tool for estimation of the bit side forces. A number of samples are analyzed with ANN for parameters of bit side force and the results are compared with exact analysis. Back Propagation Neural network (BPN) is used to approximation of bit side forces. Resultant low relative error value of the test indicates the usability of the BPN in this area.

Keywords: Artificial Neural Network, BHA, Horizontal Well, Stabilizer.

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings (GFBs) are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional (3D) fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: Fluid structure interaction multi-physics simulations, gas foil bearing, oil-free, transient thermohydrodynamic.

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Authors: U. Pangnakorn, P. Tayamanont, R. Kurubunjerdjit

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The effect of wood vinegar, entomopathogenic nematodes ((Steinernema thailandensis n. sp.) and fermented organic substances from four plants such as: Derris elliptica Roxb, Stemona tuberosa Lour, Tinospora crispa Mier and Azadirachta indica J. were tested on the five varieties of sweetpotato with potential for bioethanol production ie. Taiwan, China, PROC No.65-16, Phichit 166-5, and Phichit 129-6. The experimental plots were located at Faculty of Agriculture, Natural Resources and Environment, Naresuan University, Phitsanulok, Thailand. The aim of this study was to compare the efficiency of the five treatments for growth, yield and insect infestation on the five varieties of sweetpotato. Treatment with entomopathogenic nematodes gave the highest average weight of sweetpotato tubers (1.3 kg/tuber), followed by wood vinegar, fermented organic substances and mixed treatment with yields of 0.88, 0.46 and 0.43 kg/tuber, respectively. Also the entomopathogenic nematode treatment gave significantly higher average width and length of sweet potato (9.82 cm and 9.45 cm, respectively). Additionally, the entomopathogenic nematode provided the best control of insect infestation on sweetpotato leaves and tubers. Comparison among the varieties of sweetpotato, PROC NO.65-16 showed the highest weight and length. However, Phichit 129-6 gave significantly higher weight of 0.94 kg/tuber. Lastly, the lowest sweet potato weevil infestation on leaves and tubers occurred on Taiwan and Phichit 129-6.

Keywords: Sweetpotato (Ipomoea batatas), sweetpotato weevil (Cylas formicarius Fabr), wood vinegar, Entomopathogenic nematode (Steinernema thailandensis n. sp.), fermented organic substances.

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: Classifier ensemble, breast cancer survivability, data mining, SEER.

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Authors: Shrikant Charhate, Gayatri Deshpande

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Permeable pavements have significant benefits like managing runoff, infiltration, and carrying traffic over conventional pavements in terms of sustainability and environmental impact. Some of the countries are using this technique, especially at locations where durability and other parameters are of importance in nature; however, sparse work has been done on this concept. In India, this is yet to be adopted. In this work, the progress in the characterization and development of Permeable Articulated Concrete Blocks (PACB) pavement design is described and discussed with reference to Indian conditions. The experimentation and in-depth analysis was carried out considering conditions like soil erosion, water logging, and dust which are significant challenges caused due to impermeability of pavement. Concrete blocks with size 16.5’’x 6.5’’x 7’’ consisting of arch shape (4’’) at beneath and ½” PVC holes for articulation were casted. These blocks were tested for flexural strength. The articulation process was done with nylon ropes forming series of concrete block system. The total spacing between the blocks was kept about 8 to 10% of total area. The hydraulic testing was carried out by placing the articulated blocks with the combination of layers of soil, geotextile, clean angular aggregate. This was done to see the percentage of seepage through the entire system. The experimental results showed that with the shape of concrete block the flexural strength achieved was beyond the permissible limit. Such blocks with the combination could be very useful innovation in Indian conditions and useful at various locations compared to the traditional blocks as an alternative for long term sustainability.

Keywords: Connections, geotextile, permeable ACB, pavements, stone base.

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Authors: Tiina Brandt, Isaac Wanasika

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Culturally diverse global companies need to understand cultural differences between leaders and employees from different backgrounds. Communication is culturally contingent and has a significant impact on effective execution of leadership goals. The awareness of cultural variations related to communication and interactions will help leaders modify their own behavior, and consequently improve the execution of goals and avoid unnecessary faux pas. Our focus is on young adults that have experienced cultural integration, culturally diverse surroundings in schools and universities, and cultural travels. Our central research problem is to understand the impact of different national cultures on communication. We focus on four countries with distinct national cultures and spatial distribution. The countries are Finland, Indonesia, Russia and USA. Our sample is based on business students (n = 225) from various backgrounds in the four countries. Their responses of communication and leadership styles were analyzed using ANOVA and post-hoc test. Results indicate that culture impacts on communication behavior. Even young culturally-exposed adults with cultural awareness and experience demonstrate cultural differences in their behavior. Apparently, culture is a deeply seated trait that cannot be completely neutralized by environmental variables. Our study offers valuable input for leadership training programs and for expatriates when recognizing specific differences on leaders’ behavior due to culture.

Keywords: Culture, communication, Finland, Indonesia, Russia, USA.

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Authors: J. Prakash, K. Rajesh

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In this paper, we introduce a new method for elliptical object identification. The proposed method adopts a hybrid scheme which consists of Eigen values of covariance matrices, Circular Hough transform and Bresenham-s raster scan algorithms. In this approach we use the fact that the large Eigen values and small Eigen values of covariance matrices are associated with the major and minor axial lengths of the ellipse. The centre location of the ellipse can be identified using circular Hough transform (CHT). Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain a small number of nonzero elements they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of circumference pixels is identified using raster scan algorithm which uses the geometrical symmetry property. This method does not require the evaluation of tangents or curvature of edge contours, which are generally very sensitive to noise working conditions. The proposed method has the advantages of small storage, high speed and accuracy in identifying the feature. The new method has been tested on both synthetic and real images. Several experiments have been conducted on various images with considerable background noise to reveal the efficacy and robustness. Experimental results about the accuracy of the proposed method, comparisons with Hough transform and its variants and other tangential based methods are reported.

Keywords: Circular Hough transform, covariance matrix, Eigen values, ellipse detection, raster scan algorithm.

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Authors: Temidayo. O. Osunsanmi, Clinton Aigbavboa, Ayodeji Oke

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The construction industry is a renowned latecomer to the efficiency offered by the adoption of information technology. Whereas, the banking, manufacturing, retailing industries have keyed into the future by using digitization and information technology as a new approach for ensuring competitive gain and efficiency. The construction industry has yet to fully realize similar benefits because the adoption of ICT is still at the infancy stage with a major concentration on the use of software. Thus, this study evaluates the awareness and readiness of construction professionals towards embracing a full digitalization of the construction industry using construction 4.0. The term ‘construction 4.0’ was coined from the industry 4.0 concept which is regarded as the fourth industrial revolution that originated from Germany. A questionnaire was utilized for sourcing data distributed to practicing construction professionals through a convenience sampling method. Using SPSS v24, the hypotheses posed were tested with the Mann Whitney test. The result revealed that there are no differences between the consulting and contracting organizations on the readiness for adopting construction 4.0 concepts in the construction industry. Using factor analysis, the study discovers that adopting construction 4.0 will improve the performance of the construction industry regarding cost and time savings and also create sustainable buildings. In conclusion, the study determined that construction professionals have a low awareness towards construction 4.0 concepts. The study recommends an increase in awareness of construction 4.0 concepts through seminars, workshops and training, while construction professionals should take hold of the benefits of adopting construction 4.0 concepts. The study contributes to the roadmap for the implementation of construction industry 4.0 concepts in the South African construction industry.

Keywords: Building information technology, Construction 4.0, Industry 4.0, Smart Site.

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Authors: Tahsien Mohamed Okasha, Warda Youssef Mohamed Morsy, Hanan Elsayed Zaghla

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We hypothesized that post cardiac arrest patients with Glasgow Coma Scale (GCS) score of less than 8 and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. 17 subjects were enrolled in this study all over one year. The study was carried out using Quasi-experimental research design. Four tools were used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). The mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% subjects were initially arrested in form of ventricular tachycardia (VT), 23.5% initially arrested in form of ventricular fibrillation (VF), and 29.4% in form of A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also, initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. Therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than 8. Replication of the study on larger probability sample, with randomized control trial design is recommended with further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia is recommended.

Keywords: Therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest, initial arrest rhythm.

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Authors: Abdul Khaliq Amiri, Shigeyuki Date

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This study investigates the effect of using carbon-free fly ash (CfFA) and ground granulated blast-furnace slag (GGBFS) on the compressive strength of mortar. The CfFA used in this investigation is high-quality fly ash and the carbon content is 1.0% or less. In this study, three types of blends with a 30% water-binder ratio (w/b) were prepared: control, binary and ternary blends. The Control blend contained only Ordinary Portland Cement (OPC), in binary and ternary blends OPC was partially replaced with CfFA and GGBFS at different substitution rates. Mortar specimens were cured for 1 day, 7 days and 28 days under two curing conditions: steam curing and water curing. The steam cured specimens were exposed to two different pre-curing times (1.5 h and 2.5 h) and one steam curing duration (6 h) at 45 °C. The test results showed that water cured specimens revealed higher compressive strength than steam cured specimens at later ages. An increase in CfFA and GGBFS contents caused a decrease in the compressive strength of mortar. Ternary mixes exhibited better compressive strength than binary mixes containing CfFA with the same replacement ratio of mineral admixtures.

Keywords: Carbon-free fly ash, compressive strength, ground granulated blast-furnace slag, steam curing, water curing.

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Authors: Arun Kumar Datta, M. A. Ansari, N. R. Mondal, B. V. Raghavaiah, Manisha Dubey, Shailendra Jain

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This study is carried out to understand the effects of Static frequency converter (SFC) on large machine. SFC has a feature of four quadrant operations. By virtue of this it can be implemented to run a synchronous machine either as a motor or alternator. This dual mode operation helps a single machine to start & run as a motor and then it can be converted as an alternator whenever required. One such dual purpose machine is taken here for study. This machine is installed at a laboratory carrying out short circuit test on high power electrical equipment. SFC connected with this machine is broadly described in this paper. The same SFC has been modeled with the MATLAB/Simulink software. The data applied on this virtual model are the actual parameters from SFC and synchronous machine. After running the model, simulated machine voltage and current waveforms are validated with the real measurements. Processing of these waveforms is done through Fast Fourier Transformation (FFT) which reveals that the waveforms are not sinusoidal rather they contain number of harmonics. These harmonics are the major cause of generating shaft voltage. It is known that bearings of electrical machine are vulnerable to current flow through it due to shaft voltage. A general discussion on causes of shaft voltage in perspective with this machine is presented in this paper.

Keywords: Alternators, AC-DC power conversion, capacitive coupling, electric discharge machining, frequency converter, Fourier transforms, inductive coupling, simulation, Shaft voltage, synchronous machines, static excitation, thyristor.

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Authors: Vitomir Struc, Nikola Pavesic

Abstract:

Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.

Keywords: Biometrics, face recognition, appearance based methods, image degradations, the XM2VTS database.

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Authors: M. Vogiatzis, K. Perakis

Abstract:

Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: land use/land cover, random forest, Landsat-8 OLI, Sentinel-2A MSI, Corine land cover

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Authors: Esam I. Jassim, Mohamed M. Awad

Abstract:

Natural gas flow contains undesirable solid particles, liquid condensation, and/or oil droplets and requires reliable removing equipment to perform filtration. Recent natural gas processing applications are demanded compactness and reliability of process equipment. Since conventional means are sophisticated in design, poor in efficiency, and continue lacking robust, a supersonic nozzle has been introduced as an alternative means to meet such demands. A 3-D Convergent-Divergent Nozzle is simulated using commercial Code for pressure ratio (NPR) varies from 1.2 to 2. Six different shapes of nozzle are numerically examined to illustrate the position of shock-wave as such spot could be considered as a benchmark of particle separation. Rectangle, triangle, circular, elliptical, pentagon, and hexagon nozzles are simulated using Fluent Code with all have same cross-sectional area. The simple one-dimensional inviscid theory does not describe the actual features of fluid flow precisely as it ignores the impact of nozzle configuration on the flow properties. CFD Simulation results, however, show that nozzle geometry influences the flow structures including location of shock wave. The CFD analysis predicts shock appearance when p01/pa>1.2 for almost all geometry and locates at the lower area ratio (Ae/At). Simulation results showed that shock wave in Elliptical nozzle has the farthest distance from the throat among the others at relatively small NPR. As NPR increases, hexagon would be the farthest. The numerical result is compared with available experimental data and has shown good agreement in terms of shock location and flow structure.

Keywords: CFD, Particle Separation, Shock wave, Supersonic Nozzle.

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Authors: Haleem K. Hussain, Liu Gui Wei, Zhang Lian Zhen, Yongxue Li

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It is necessary to evaluate the bridges conditions and strengthen bridges or parts of them. The reinforcement necessary due to some reasons can be summarized as: First, a changing in use of bridge could produce internal forces in a part of structural which exceed the existing cross-sectional capacity. Second, bridges may also need reinforcement because damage due to external factors which reduced the cross-sectional resistance to external loads. One of other factors could listed here its misdesign in some details, like safety of bridge or part of its.This article identify the design demands of Qing Shan bridge located in is in Heilongjiang Province He gang - Nen Jiang Road 303 provincial highway, Wudalianchi area, China, is an important bridge in the urban areas. The investigation program was include the observation and evaluate the damage in T- section concrete beams , prestressed concrete box girder bridges section in additional evaluate the whole state of bridge includes the pier , abutments , bridge decks, wings , bearing and capping beam, joints, ........etc. The test results show that the bridges in general structural condition are good. T beam span No 10 were observed, crack extended upward along the ribbed T beam, and continue to the T beam flange. Crack width varying between 0.1mm to 0.4mm, the maximum about 0.4mm. The bridge needs to be improved flexural bending strength especially at for T beam section.

Keywords: Field investigation, prestressed concrete box girder, maintenance, Qing Shan Bridge

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Authors: Meseret Teshome

Abstract:

This study has the objective of assessing the effect of kaizen (5S, Muda elimination and Quality Control Circle (QCC) on employees’ affective attitude (job satisfaction, commitment and job stress) in Kombolcha Textile Share Company. A conceptual model was developed to describe the relationship between Kaizen and Employees’ Affective Attitude (EAA) factors. The three factors of Employee Affective Attitude were measured using questionnaire derived from other validated questionnaire. In the data collection to conduct this study; questionnaire, unstructured interview, written documents and direct observations are used. To analyze the data, SPSS and Microsoft Excel were used. In addition, the internal consistency of similar items in the questionnaire instrument was measured for their equivalence by using the cronbach’s alpha test. In this study, the effect of 5S, Muda elimination and QCC on job satisfaction, commitment and job stress in Kombolcha Textile Share Company is assessed and factors that reduce employees’ job satisfaction with respect to kaizen implementation are identified. The total averages of means from the questionnaire are 3.1 for job satisfaction, 4.31 for job commitment and 4.2 for job stress. And results from interview and secondary data show that kaizen implementation have effect on EAA. In general, based on the thesis results it was concluded that kaizen (5S, muda elimination and QCC) have positive effect for improving EAA factors at KTSC. Finally, recommendations for improvement are given based on the results.

Keywords: Kaizen, job satisfaction, job commitment, job stress.

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Authors: Fereydoon Sarmadian, Ali Keshavarzi

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Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.

Keywords: Artificial neural network, Field capacity, Permanentwilting point, Pedotransfer functions.

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Authors: A. S. Abdel-Razek, M. M. M. Abd-Elgawad

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The potential of entomopathogenic nematodes in suppressing T. squalida population on cauliflower from transplanting to harvest was evaluated. Significant reductions in plant infestation percentage and population density (/m2) were recorded throughout the plantation seasons, 2011 and 2012 before and after spraying the plants. The percent reduction in numbers/m2 was the highest in March for the treatments with Heterorhabditis indica Behera and Heterorhabditis bacteriophora Giza during the plantation season 2011, while at the plantation season 2012, the reduction in population density was the highest in January for Heterorhabditis Indica Behera and in February for H . bacteriophora Giza treatments. In a comparison test with conventional insecticides Hostathion and Lannate, there were no significant differences in control measures resulting from treatments with H. indica Behera, H. bacteriophora Giza and Lannate. At the plantation season is 2012. Also, the treatments reduced the economic threshold of T. squalida on cauliflower in this experiment as compared with before and after spraying with both the two entomopathogenic nematodes at both seasons 2011 and 2012. This means an increase in the marketability of heads harvested as a consequence of monthly treatments. 

Keywords: Cruciferous plants, chemical insecticides, microbial control, Scarabiead beetles, seasonal monitoring.

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Authors: Jiqing Han, Rongchun Gao

Abstract:

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel compensation technique, this paper applies MAP (Maximum A Posterior Probability) channel compensation technique, which was used in speech recognition, to speaker recognition system. In the aspect of channel robust features, this paper introduces pitch-dependent features and pitch-dependent speaker model for the second stage recognition. Based on the first stage recognition to testing speech using GMM (Gaussian Mixture Model), the system uses GMM scores to decide if it needs to be recognized again. If it needs to, the system selects a few speakers from all of the speakers who participate in the first stage recognition for the second stage recognition. For each selected speaker, the system obtains 3 pitch-dependent results from his pitch-dependent speaker model, and then uses ANN (Artificial Neural Network) to unite the 3 pitch-dependent results and 1 GMM score for getting a fused result. The system makes the second stage recognition based on these fused results. The experiments show that the correct rate of two-stage recognition system based on MAP channel compensation technique and pitch-dependent features is 41.7% better than the baseline system for closed-set test.

Keywords: Channel Compensation, Channel Robustness, MAP, Speaker Identification

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