Search results for: work effort estimation methods

Authors: P. Martínez-Nieto, M. Vanegas-Hoyos, M. Zapata-Pineda, J. Robles-Camargo

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The aquatic plants are a promising renewable energy resource. Lake Fúquene polluting macrophytes, water hyacinth (Eichhornia crassipes C. Mart.) and Brazilian elodea (Egeria densa Planch.), were saccharifiedby different treatments and fermented to ethanol by native yeasts. Among the tested chemical and biological methods for the saccharification, Pleurotus ostreatus at 10% (m/v) was chosen as the best pre-treatment in both macrophytes (P<0.01). Subsequently 49 yeasts were isolated from Lake Fúquene and nine strains were selected, which presented the highest precipitates characteristic of ethanol in the iodoform test. The fermentations from water hyacinth and Brazilian elodea hydrolysates using these yeasts produced ethanol at a rate between 0.38 to 0.80gL-1h-1 and 0.15 to 0.27gL-1h-1 respectively. The ethanol presence was confirmed by gas chromatography–mass spectrometry. The nine yeasts chosen were preliminarily identified as belonging to the genera Candida spp., Brettanomyces sp. and Hansenula spp.

Keywords: Bio-ethanol, Chemical hydrolysis, Invasive aquatic macrophytes, Native yeasts fermenting, P. ostreatus

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: Human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, Prior distribution and approximate posterior distribution, KTH dataset.

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Authors: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

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In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: Parameterization, response surface, structure optimization, pressure hull.

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Authors: Omer F. Cansiz, Said M. Easa

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The purpose of this study is mainly to predict collision frequency on the horizontal tangents combined with vertical curves using artificial neural network methods. The proposed ANN models are compared with existing regression models. First, the variables that affect collision frequency were investigated. It was found that only the annual average daily traffic, section length, access density, the rate of vertical curvature, smaller curve radius before and after the tangent were statistically significant according to related combinations. Second, three statistical models (negative binomial, zero inflated Poisson and zero inflated negative binomial) were developed using the significant variables for three alignment combinations. Third, ANN models are developed by applying the same variables for each combination. The results clearly show that the ANN models have the lowest mean square error value than those of the statistical models. Similarly, the AIC values of the ANN models are smaller to those of the regression models for all the combinations. Consequently, the ANN models have better statistical performances than statistical models for estimating collision frequency. The ANN models presented in this paper are recommended for evaluating the safety impacts 3D alignment elements on horizontal tangents.

Keywords: Collision frequency, horizontal tangent, 3D two-lane highway, negative binomial, zero inflated Poisson, artificial neural network.

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Authors: Tatiana L. Gorbunova

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The research is dedicated to the study of the polluted river inflow impact on the Black Sea coastal marine environment within the watercourse’s plumes in the Greater Sochi area applying bioassay methods with using freshwater and marine microalgae. River waters were analyzed using microalgae Chlorella vulgaris Beijer and sea waters were tested with marine diatoms Phaeodactylum tricornutum Bohlin. Experiments included algae cells abundancy growth assessments in acute (24 hours), sub-acute (72 hours) and chronic (168 hours/7 days) tests. The increase in algal cell growth rates compared to the control in the summer period was detected as a consequence of the recreational activities intensification during the tourism seasonal peak. Most of the analyzed samples demonstrated a significant effect of algae cells growth stimulation compared to the control. It is established that under the impact of contaminants carried by river’s drain to the sea, the capacity of the coastal marine ecosystem is partially capable to compensate its effect on the coastal biocenosis, but the general trends of the impact processes remain constant.

Keywords: Algae abundance growth, bioassay, microalgae, modeling.

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Authors: Khairul Jauhari, Achmad Widodo, Ismoyo Haryanto

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In this article, the radial displacement error correction capability of a high precision spindle grinding caused by unbalance force was investigated. The spindle shaft is considered as a flexible rotor mounted on two sets of angular contact ball bearing. Finite element methods (FEM) have been adopted for obtaining the equation of motion of the spindle. In this paper, firstly, natural frequencies, critical frequencies, and amplitude of the unbalance response caused by residual unbalance are determined in order to investigate the spindle behaviors. Furthermore, an optimization design algorithm is employed to minimize radial displacement of the spindle which considers dimension of the spindle shaft, the dynamic characteristics of the bearings, critical frequencies and amplitude of the unbalance response, and computes optimum spindle diameters and stiffness and damping of the bearings. Numerical simulation results show that by optimizing the spindle diameters, and stiffness and damping in the bearings, radial displacement of the spindle can be reduced. A spindle about 4 μm radial displacement error can be compensated with 2 μm accuracy. This certainly can improve the accuracy of the product of machining.

Keywords: Error correction, High precision grinding, Optimization, Radial displacement, Spindle.

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Authors: Muammer Kaya

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The main purpose of this article is to provide a comprehensive review of various physical and chemical processes for electronic waste (e-waste) recycling, their advantages and shortfalls towards achieving a cleaner process of waste utilization, with especial attention towards extraction of metallic values. Current status and future perspectives of waste printed circuit boards (PCBs) recycling are described. E-waste characterization, dismantling/ disassembly methods, liberation and classification processes, composition determination techniques are covered. Manual selective dismantling and metal-nonmetal liberation at – 150 µm at two step crushing are found to be the best. After size reduction, mainly physical separation/concentration processes employing gravity, electrostatic, magnetic separators, froth floatation etc., which are commonly used in mineral processing, have been critically reviewed here for separation of metals and non-metals, along with useful utilizations of the non-metallic materials. The recovery of metals from e-waste material after physical separation through pyrometallurgical, hydrometallurgical or biohydrometallurgical routes is also discussed along with purification and refining and some suitable flowsheets are also given. It seems that hydrometallurgical route will be a key player in the base and precious metals recoveries from e-waste. E-waste recycling will be a very important sector in the near future from economic and environmental perspectives.

Keywords: E-waste, WEEE, PCB, recycling, metal recovery, hydrometallurgy, pyrometallurgy, biohydrometallurgy.

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Authors: Nhon Do, Thuong Huynh, An Pham

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Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.

Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.

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Authors: Laura Zizka, Gaby Probst

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The COVID-19 pandemic has affected the way Higher Education Institutions (HEIs) have given their courses. From emergency remote where all students and faculty were immediately confined to home teaching and learning, the continuing evolving sanitary situation obliged HEIs to adopt other methods of teaching and learning from blended courses that included both synchronous and asynchronous courses and activities to HyFlex models where some students were on campus while others followed the course simultaneously online. Each semester brought new challenges for HEIs and, subsequently, additional emotional reactions. This paper investigates the affective side of teaching and learning in various online modalities and its toll on students and faculty members over the past three semesters. The findings confirm that students and faculty who have more self-efficacy, flexibility, and resilience reported positive emotions and embraced the opportunities that these past semesters have offered. While HEIs have begun a new semester in an attempt to return to ‘normal’ face-to-face courses, this paper posits that there are lessons to be learned from these past three semesters. The opportunities that arose from the challenge of the pandemic should be considered when moving forward by focusing on a greater emphasis on the affective aspect of teaching and learning in HEIs worldwide. 

Keywords: affective teaching and learning, engagement, interaction, motivation, social presence

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Authors: Cristiano R. Cervi, Renata Galante, José Palazzo M. de Oliveira

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In this paper, we address the problem of identifying academic reputation of researchers using scientific metrics in different research areas. Due to the characteristics of each area, researchers can present different behaviors. In previous work, we define Rep-Index that makes use of a profile template to individually identify the reputation of researchers. The Rep-Index is comprehensive and adaptive because involves hole trajectory of the researcher built throughout his career and can be used in different areas and in different contexts. Now, we compare our metric (Rep-Index) with the h-index and the g-index through experiments with researchers in the fields of Economics, Dentistry and Computer Science. We analyze the trajectory of 830 Brazilian researchers from the National Council of Technological and Scientific Development (CNPq), which receive grants research productivity. The grants are aimed at productivity researchers that stand out among their peers, enhancing their scientific normative criteria established by CNPq. Of the 830 researchers, 210 are in the area of Economics, 216 of Dentistry e 404 of Computer Science. The experiments show that our metric is strongly correlated with h-index, g-index and CNPq ranking. We also show good results for our hypothesis that our metric can be used to evaluate research in several areas. We apply our metric (Rep-Index) to compare the behavior of researchers in relation to their h-index and g-index through extensive experiments. The experiments showed that our metric is strongly correlated with h-index, g-index and CNPq ranking.

Keywords: Researcher reputation, profile model, scientific metrics.

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Authors: M. Cynthya, V. Prabhawathi, D. Mukesh

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Food contamination occurs during post process handling. This leads to spoilage and growth of pathogenic microorganisms in the food, thereby reducing its shelf life or spreading of food borne diseases. Several methods are tried and one of which is use of antimicrobial packaging. Here, papain, a protease enzyme, is covalently immobilized with the help of glutarldehyde on polyurethane and used as a food wrap to protect food from microbial contamination. Covalent immobilization of papain was achieved at a pH of 7.4; temperature of 4°C; glutaraldehyde concentration of 0.5%; incubation time of 24h; and 50mg of papain. The formation of -C=Nobserved in the Fourier transform infrared spectrum confirmed the immobilization of the enzyme on the polymer. Immobilized enzyme retained higher activity than the native free enzyme. The modified polyurethane showed better reduction of Staphylococcus aureus biofilm than bare polymer film (eight folds reduction in live colonies, two times reduction in protein and 6 times reduction in carbohydrates). The efficacy of this was studied by wrapping it over S. aureus contaminated cottage cheese (paneer) and cheese and stored at a temperature of 4°C for 7days. The modified film reduced the bacterial contamination by eight folds when compared to the bare film. FTIR also indicated reduction in lipids, sugars and proteins in the biofilm.

Keywords: Cheese, Papain, polyurethane, Staphylococcus aureus.

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Authors: Shaila Ahmed, Raghu Prasad Rao Metpally, Sreedhara Sangadala, Boojala Vijay B Reddy

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Bone growth factors, such as Bone Morphogenic Protein-2 (BMP-2) have been approved by the FDA to replace grafting for some surgical interventions, but the high dose requirement limits its use in patients. Noggin, an extracellular protein, blocks the effect of BMP-2 by binding to BMP. Preventing the BMP-2/noggin interaction will help increase the free concentration of BMP-2 and therefore should enhance its efficacy to induce bone formation. The work presented here involves computational design of novel small molecule inhibitory agents of BMP-2/noggin interaction, based on our current understanding of BMP-2, and its known putative ligands (receptors and antagonists). A successful acquisition of such an inhibitory agent of BMP-2/noggin interaction would allow clinicians to reduce the dose required of BMP-2 protein in clinical applications to promote osteogenesis. The available crystal structures of the BMPs, its receptors, and the binding partner noggin were analyzed to identify the critical residues involved in their interaction. In presenting this study, LUDI de novo design method was utilized to perform virtual screening of a large number of compounds from a commercially available library against the binding sites of noggin to identify the lead chemical compounds that could potentially block BMP-noggin interaction with a high specificity.

Keywords: Transforming growth factor-beta, Bone morphogenic proteins, Noggin, LUDI de novo design method, CAP small molecules.

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Authors: S. Alfalah, J. Falah, T. Alfalah, M. Elfalah, O. Falah

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The field of education is an ever-evolving area constantly enriched by newly discovered techniques provided by active research in all areas of technologies. The recent years have witnessed the introduction of a number of promising technologies and applications to enhance the teaching and learning experience. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing education in many fields. VR creates an artificial environment, using computer hardware and software, which is similar to the real world. This simulation provides a solution to improve the delivery of materials, which facilitates the teaching process by providing a useful aid to instructors, and enhances the learning experience by providing a beneficial learning aid. In order to assure future utilization of such systems, students’ perceptions were examined toward utilizing VR as an educational tool in the Faculty of Information Technology (IT) in The University of Jordan. A questionnaire was administered to IT undergraduates investigating students’ opinions about the potential opportunities that VR technology could offer and its implications as learning and teaching aid. The results confirmed the end users’ willingness to adopt VR systems as a learning aid. The result of this research forms a solid base for investing in a VR system for IT education.

Keywords: Education, information, technology, virtual reality.

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Authors: Kiurski S. Jelena, Aksentijević M. Snežana, Kecić S. Vesna, Oros B. Ivana

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Prosperity of electronic equipment in photocopying environment not only has improved work efficiency, but also has changed indoor air quality. Considering the number of photocopying employed, indoor air quality might be worse than in general office environments. Determining the contribution from any type of equipment to indoor air pollution is a complex matter. Non-methane hydrocarbons are known to have an important role on air quality due to their high reactivity. The presence of hazardous pollutants in indoor air has been detected in one photocopying shop in Novi Sad, Serbia. Air samples were collected and analyzed for five days, during 8-hr working time in three time intervals, whereas three different sampling points were determined. Using multiple linear regression model and software package STATISTICA 10 the concentrations of occupational hazards and microclimates parameters were mutually correlated. Based on the obtained multiple coefficients of determination (0.3751, 0.2389 and 0.1975), a weak positive correlation between the observed variables was determined. Small values of parameter F indicated that there was no statistically significant difference between the concentration levels of nonmethane hydrocarbons and microclimates parameters. The results showed that variable could be presented by the general regression model: y = b0 + b1xi1+ b2xi2. Obtained regression equations allow to measure the quantitative agreement between the variables and thus obtain more accurate knowledge of their mutual relations.

Keywords: Indoor air quality, multiple regression analysis, nonmethane hydrocarbons, photocopying process.

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Authors: Ilias A. Makris

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In this work, we attempt to associate firm characteristics with innovative activity. We collect microdata from listed firms of selected Eurozone Country-members, after the beginning of 2007 financial crisis. The following literature, several indicators of growth and performance were selected and tested for their ability to interpret innovative activity. The main scope is to examine the possible differences in performance and growth between innovative and non-innovative firms, during a severe recession. Additionally to that, a special focus will be held on whether macroeconomic performance and national innovation system, determines the extent of innovators' performance. Preliminary findings, through correlation matrices and non-parametric tests, strongly indicate the positive relation between innovative activity and most of the measures used (profitability, size, employment), confirming that even during a recessionary period, innovative firms not only survive but also seem to succeed better economic results in almost all indexes relative to non-innovative. However, even though innovators seem to perform better in all economies examined, the extent of that performance seems to be strongly affected by the supportive mechanisms (financial and structural) that their country provides. Thus, it is clear, that the technologically intensive 'gap' between European South and North, during the economic crisis, became chaotic, due to the harsh austerity measures and reduced budgets in those countries, even in sectors with high potentials in economic activity and employment, impairing the effects of crisis and enhancing the vicious circle of recession.

Keywords: Eurozone, innovative activity, development, firm performance, non-parametric tests.

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Authors: Hany Mahgoub, Dietmar Rösner, Nabil Ismail, Fawzy Torkey

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This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TFIDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.

Keywords: Text mining, data mining, association rule mining

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Authors: Chang-Lin Hu, Yao-You Cheng, Meng-Lin Li

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The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.

Keywords: retrospective synthetic focusing, high frame rate, correlation weighting.

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Authors: Gbenga F. Akomolafe, Joseph Omojola, Ezekiel S. Joshua, Seyi C. Adediwura, Elijah T. Adesuji, Michael O. Odey, Oyinade A. Dedeke, Ayo H. Labulo

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Microgravity is known to be a major abiotic stress in space which affects plants depending on the duration of exposure. In this work, tomatoes seeds were exposed to long hours of simulated microgravity condition using a one-axis clinostat. The seeds were sown on a 1.5% combination of plant nutrient and agar-agar solidified medium in three Petri dishes. One of the Petri dishes was mounted on the clinostat and allowed to rotate at the speed of 20 rpm for 72 hours, while the others were subjected to the normal gravity vector. The anatomical sections of both clinorotated and normal gravity plants were made after 72 hours and observed using a Phase-contrast digital microscope. The percentage germination, as well as the growth rate of the normal gravity seeds, was higher than the clinorotated ones. The germinated clinorotated roots followed different directions unlike the normal gravity ones which grew towards the direction of gravity vector. The clinostat was able to switch off gravistimulation. Distinct cellular arrangement was observed for tomatoes under normal gravity condition, unlike those of clinorotated ones. The root epidermis and cortex of normal gravity are thicker than the clinorotated ones. This implied that under long-term microgravity influence, plants do alter their anatomical features as a way of adapting to the stress condition.

Keywords: Anatomy, Clinostat, Germination, Microgravity, Lycopersicon esculentum.

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Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: Air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF.

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Authors: Mohammad Reza Kangavari, Samira Ghandchi, Manak Golpour

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Most of the Question Answering systems composed of three main modules: question processing, document processing and answer processing. Question processing module plays an important role in QA systems. If this module doesn't work properly, it will make problems for other sections. Moreover answer processing module is an emerging topic in Question Answering, where these systems are often required to rank and validate candidate answers. These techniques aiming at finding short and precise answers are often based on the semantic classification. This paper discussed about a new model for question answering which improved two main modules, question processing and answer processing. There are two important components which are the bases of the question processing. First component is question classification that specifies types of question and answer. Second one is reformulation which converts the user's question into an understandable question by QA system in a specific domain. Answer processing module, consists of candidate answer filtering, candidate answer ordering components and also it has a validation section for interacting with user. This module makes it more suitable to find exact answer. In this paper we have described question and answer processing modules with modeling, implementing and evaluating the system. System implemented in two versions. Results show that 'Version No.1' gave correct answer to 70% of questions (30 correct answers to 50 asked questions) and 'version No.2' gave correct answers to 94% of questions (47 correct answers to 50 asked questions).

Keywords: Answer Processing, Classification, QuestionAnswering and Query Reformulation.

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Authors: R. Reka, R. S. D. Wahidabanu

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The conventional routing protocol designed for MANET fail to handle dynamic movement and self-starting behavior of the node effectively. Every node in MANET is considered as forward as well receiver node and all of them participate in routing the packet from source to the destination. While the interconnection topology is highly dynamic, the performance of the most of the routing protocol is not encouraging. In this paper, a reliable broadcast approach for MANET is proposed for improving the transmission rate. The MANET is considered with asymmetric characteristics and the properties of the source and destination nodes are different. The non-forwarding node list is generated with a downstream node and they do not participate in the routing. While the forwarding and non-forwarding node is constructed in a conventional way, the number of nodes in non-forwarding list is more and increases the load. In this work, we construct the forwarding and non-forwarding node optimally so that the flooding and broadcasting is reduced to certain extent. The forwarded packet is considered as acknowledgements and the non-forwarding nodes explicitly send the acknowledgements to the source. The performance of the proposed approach is evaluated in NS2 environment. Since the proposed approach reduces the flooding, we have considered functionality of the proposed approach with AODV variants. The effect of network density on the overhead and collision rate is considered for performance evaluation. The performance is compared with the AODV variants found that the proposed approach outperforms all the variants.

Keywords: Flooding, Forwarded Nodes, MANET, Non-forwarding nodes, Routing protocols.

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Authors: Ahmed Mansouri, Naoji Matsumoto

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This research is a comparative study of complexity, as a multidimensional concept, in the context of streetscape composition in Algeria and Japan. 80 streetscapes visual arrays have been collected and then presented to 20 participants, with different cultural backgrounds, in order to be categorized and classified according to their degrees of complexity. Three analysis methods have been used in this research: cluster analysis, ranking method and Hayashi Quantification method (Method III). The results showed that complexity, disorder, irregularity and disorganization are often conflicting concepts in the urban context. Algerian daytime streetscapes seem to be balanced, ordered and regular, and Japanese daytime streetscapes seem to be unbalanced, regular and vivid. Variety, richness and irregularity with some aspects of order and organization seem to characterize Algerian night streetscapes. Japanese night streetscapes seem to be more related to balance, regularity, order and organization with some aspects of confusion and ambiguity. Complexity characterized mainly Algerian avenues with green infrastructure. Therefore, for Japanese participants, Japanese traditional night streetscapes were complex. And for foreigners, Algerian and Japanese avenues nightscapes were the most complex visual arrays.

Keywords: Streetscape, Nightscape, Complexity, Visual Array, Affordance, Cluster Analysis, Hayashi Quantification Method.

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Authors: Sara Ramezanzadeh, Nashid Nabian

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Historically, pandemics in different periods have caused compulsory changes in human life. In the case of COVID-19, according to the limitations and established care instructions, spatial alignment with the conditions is important. Following the outbreak of COVID-19, the question raised in this study is how to do spatial design in five scales, namely object, space, architecture, city, and infrastructure, in response to the consequences created in the realms under study. From the beginning of the pandemic until now, some changes in the spatial realm have been created spontaneously or by space users. These transformations have been mostly applied in modifiable parts such as furniture arrangement, especially in work-related spaces. To implement other comprehensive requirements, flexibility and adaptation of space design to the conditions resulting from the pandemics are needed during and after the outbreak. Studying the effects of pandemics from the past to the present, this research covers eight major realms, including three categories of ramifications, solutions, and paradigm shifts, and analytical conclusions about the solutions that have been created in response to them. Finally, by the consideration of epidemiology as a modern discipline influencing the design, spatial solutions in the five scales mentioned (in response to the effects of the eight realms for spatial adaptation in the face of pandemics and their following conditions) are presented as a series of guidelines. Due to the unpredictability of possible pandemics in the future, the possibility of changing and updating the provided guidelines is considered.

Keywords: Pandemics, COVID-19, spatial design, ramifications, paradigm shifts, guidelines.

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Authors: L. Khalfa, M. Bagane, M. L. Cervera, S. Najjar

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The aim of this work is to present a low cost adsorbent for removing toxic heavy metals from aqueous solutions. Therefore, we are interested to investigate the efficiency of natural clay minerals collected from south Tunisia and their modified form using sulfuric acid in the removal of toxic metal ions: Zn(II) and Pb(II) from synthetic waste water solutions. The obtained results indicate that metal uptake is pH-dependent and maximum removal was detected to occur at pH 6. Adsorption equilibrium is very rapid and it was achieved after 90 min for both metal ions studied. The kinetics results show that the pseudo-second-order model describes the adsorption and the intraparticle diffusion models are the limiting step. The treatment of natural clay with sulfuric acid creates more active sites and increases the surface area, so it showed an increase of the adsorbed quantities of lead and zinc in single and binary systems. The competitive adsorption study showed that the uptake of lead was inhibited in the presence of 10 mg/L of zinc. An antagonistic binary adsorption mechanism was observed. These results revealed that clay is an effective natural material for removing lead and zinc in single and binary systems from aqueous solution.

Keywords: Lead, zinc heavy metal, activated clay, kinetic study, competitive adsorption, modeling.

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Authors: Elham S. Hasham, Anthony S. Hasham

Abstract:

The construction industry is one of Australia’s fastest growing industries and its success is a result of a firm’s client satisfaction with focus on product determinants such as price and quality. Ensuring quality at every phase is a must and building rapport with the client will go a long way. To capitalize on the growing demand for Engineering Consulting Firms (ECFs), it is imperative to stress the implication of customer satisfaction and excellence in standards and performance. Consequently, the emphasis should be on improving employee skills through various training provisions. Clients seek consistency and thus expect that all services should be similar in respect to quality and the ability of the service to meet their needs. This calls for empowerment and comfortable work conditions to motivate employees and give them incentive to deliver quality and excellent output. The methodology utilized is triangulation - a combination of both quantitative and qualitative research. The case study - Australian Consulting Engineers (ACE) - was established in Australia in 1995 and has operations throughout Australia, the Philippines, Europe, UAE, KSA, and with a branch in Lebanon. ACE is affiliated with key agencies and support organizations in the engineering industry with International Organization for Standardization (ISO) certifications in Safety and Quality Management. The objective of this study, conducted in Australia, is significant as it sheds light on employee motivation and client satisfaction as imperative determinants of the success of an organization.

Keywords: Organizational behaviour, leadership, satisfaction, motivation, quality service.

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Authors: F. Al-Mufadi, F. Djavanroodi

Abstract:

During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of Standard deviation (S. D.) and inhomogeneity index (C_i) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90^°, 20^° and 20mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route B_C at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67HV from 21HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.

Keywords: SPD, ECAP, FEM, Pure Al, Mechanical properties.

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Authors: SeHun Lim, Sanghoon Kim, Sun-Tae Chung, Seongwon Cho

Abstract:

Face authentication for access control is a face membership authentication which passes the person of the incoming face if he turns out to be one of an enrolled person based on face recognition or rejects if not. Face membership authentication belongs to the two class classification problem where SVM(Support Vector Machine) has been successfully applied and shows better performance compared to the conventional threshold-based classification. However, most of previous SVMs have been trained using image feature vectors extracted from face images of each class member(enrolled class/unenrolled class) so that they are not robust to variations in illuminations, poses, and facial expressions and much affected by changes in member configuration of the enrolled class In this paper, we propose an effective face membership authentication method based on SVM using class discriminating features which represent an incoming face image-s associability with each class distinctively. These class discriminating features are weakly related with image features so that they are less affected by variations in illuminations, poses and facial expression. Through experiments, it is shown that the proposed face membership authentication method performs better than the threshold rule-based or the conventional SVM-based authentication methods and is relatively less affected by changes in member size and membership.

Keywords: Face Authentication, Access control, member ship authentication, SVM.

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Authors: Mohd F. Taha, Chong F. Kiat, Maizatul S. Shaharun, Anita Ramli

Abstract:

The abundance and availability of rice husk, an agricultural waste, make them as a good source for precursor of activated carbon. In this work, rice husk-based activated carbons were prepared via base treated chemical activation process prior the carbonization process. The effect of carbonization temperatures (400, 600 and 800oC) on their pore structure was evaluated through morphology analysis using scanning electron microscope (SEM). Sample carbonized at 800oC showed better evolution and development of pores as compared to those carbonized at 400 and 600oC. The potential of rice husk-based activated carbon as an alternative adsorbent was investigated for the removal of Ni(II), Zn(II) and Pb(II) from single metal aqueous solution. The adsorption studies using rice husk-based activated carbon as an adsorbent were carried out as a function of contact time at room temperature and the metal ions were analyzed using atomic absorption spectrophotometer (AAS). The ability to remove metal ion from single metal aqueous solution was found to be improved with the increasing of carbonization temperature. Among the three metal ions tested, Pb(II) ion gave the highest adsorption on rice husk-based activated carbon. The results obtained indicate the potential to utilize rice husk as a promising precursor for the preparation of activated carbon for removal of heavy metals.

Keywords: Activated carbon, metal ion adsorption, rice husk, wastewater treatment.

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Authors: B. Suárez, G. Forman

Abstract:

Kombucha (a symbiotic culture of bacteria and yeast) produces material capable of acquiring multiple shapes and textures that change significantly under different environment or temperature variations (e.g., when it is exposed to wet conditions), properties that may be explored in the scenic industry. This paper presents an analysis of its specific characteristics, exploring them as a non-conventional material for arts and performance. Costume Design uses surfaces as a powerful way of expression to represent concepts and stories; it may apply the unique features of nano bacterial cellulose (NBC) as assets in this artistic context. A mix of qualitative and quantitative (interventionist) methodology approaches were used such as review of relevant literature to deepen knowledge on the research topic (crossing bibliography from different fields of studies: biology, art, costume design, etc.); as well as descriptive methods: laboratorial experiments, document quantities, observation to identify material properties and possibilities used to express a multiple narrative ideas, concepts and feelings. The results confirmed that NBC is an interactive and versatile material viable to be used in an alternative scenic context; its unique aesthetic and performative qualities, which change in contact to moisture, are resources that can be used to show a visual and poetic impact on stage.

Keywords: Biotechnological materials, contemporary dance, costume design, nano bacterial cellulose, performing arts.

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Authors: Walid MOUDANI

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.

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