Search results for: Control methods

Authors: Tadashi Watanabe

Abstract:

The two-phase flow field and the motion of the free surface in an oscillating channel are simulated numerically to assess the methodology for simulating nuclear reacotr thermal hydraulics under seismic conditions. Two numerical methods are compared: one is to model the oscillating channel directly using the moving grid of the Arbitrary Lagrangian-Eulerian method, and the other is to simulate the effect of channel motion using the oscillating acceleration acting on the fluid in the stationary channel. The two-phase flow field in the oscillating channel is simulated using the level set method in both cases. The calculated results using the oscillating acceleration are found to coinside with those using the moving grid, and the theoretical back ground and the limitation of oscillating acceleration are discussed. It is shown that the change in the interfacial area between liquid and gas phases under seismic conditions is important for nuclear reactor thermal hydraulics.

Keywords: Two-phase flow, simulation, seismic condition, moving grid, oscillating acceleration, interfacial area

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Authors: Melissa C. LaDuke

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The purpose of this targeted analysis was to identify the use of online communities of practice (CoP) within e-learning environments as a method to build social interaction and student-centered educational experiences. A literature review was conducted to survey and collect scholarly thoughts concerning CoPs from a variety of sources. Data collected included best practices, ties to educational theories, and examples of online CoPs. Social interaction has been identified as a critical piece of the learning infrastructure, specifically for adult learners. CoPs are an effective way to help students connect to each other and the material of interest. The use of CoPs falls in line with many educational theories, including situated learning theory, social constructivism, connectivism, adult learning theory, and motivation. New literacies such as social media and gamification can help increase social interaction in online environments and provide methods to host CoPs. Steps to build and sustain a CoP were discussed in addition to CoP considerations and best practices.

Keywords: Community of practice, knowledge sharing, social interaction, online course design, new literacies.

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Authors: Tor Kindsbekken Kjeldby, Ruud Henkes, Ole Jørgen Nydal

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Experimental data from an atmospheric air/water terrain slugging case has been made available by the Shell Amsterdam research center, and has been subject to numerical simulation and comparison with a one-dimensional two-phase slug tracking simulator under development at the Norwegian University of Science and Technology. The code is based on tracking of liquid slugs in pipelines by use of a Lagrangian grid formulation implemented in Cµ by use of object oriented techniques. An existing hybrid spatial discretization scheme is tested, in which the stratified regions are modelled by the two-fluid model. The slug regions are treated incompressible, thus requiring a single momentum balance over the whole slug. Upon comparison with the experimental data, the period of the simulated severe slugging cycle is observed to be sensitive to slug generation in the horizontal parts of the system. Two different slug initiation methods have been tested with the slug tracking code, and grid dependency has been investigated.

Keywords: Hydrodynamic initiation, slug tracking, terrain slugging, two-fluid model, two-phase flow.

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Authors: Nneka N. Uchegbu, Charles N. Ishiwu

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The nutritional composition and hypoglycaemic effect of crackers produced from blend of sprouted pigeon pea, unripe plantain and brewers’ spent grain and fed to Alloxan induced diabetic rat was investigated. Crackers were produced from different blends of sprouted pigeon pea, unripe plantain and brewers’ spent grain. The crackers were evaluated for proximate composition, amino acid profile and antinutritional factors. Blood glucose levels of normal and diabetic rats fed with the control sample and different formulations of cracker were measured. The protein content of the samples were significantly different (p<0.05) from each other with sample A having the lowest value and sample B with the highest value. The values obtained showed that the samples contained most of the amino acids that are found in plant proteins. The levels of antinutritional factor determined were generally low. Administration of the formulated cracker meals led to a significant reduction in the fasting blood glucose level in the diabetic rats. The present study concluded that consumption of crackers produced from this composite flour could be recommended for the diabetics and those who are sceptical about the disease.

Keywords: Crackers, diabetics rat, sprouted pigeon pea, unripe plantain and brewers’ spent grain.

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: High voltage substations, nature-inspired algorithms, project management, meta-heuristics.

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Authors: D. Vainauska, S. Kozireva, A. Karpovs, M. Chistyakovs, M. Baryshev

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Liposomal magnetofection is a simple, highly efficient technology for cell transfection, demonstrating better outcome than a number of other common gene delivery methods. However, aggregate complexes distribution over the cell surface is non-uniform due to the gradient of the permanent magnetic field. The aim of this study was to estimate the efficiency of liposomal magnetofection for prostate carcinoma PC3 cell line using newly designed device, “DynaFECTOR", ensuring magnetofection in a dynamic gradient magnetic field. Liposomal magnetofection in a dynamic gradient magnetic field demonstrated the highest transfection efficiency for PC3 cells – it increased for 21% in comparison with liposomal magnetofection and for 42% in comparison with lipofection alone. The optimal incubation time under dynamic magnetic field for PC3 cell line was 5 minutes and the optimal rotation frequency of magnets – 5 rpm. The new approach also revealed lower cytotoxic effect to cells than liposomal magnetofection.

Keywords: Dynamic gradient magnetic field, gene delivery, liposomal magnetofection, prostate cancer cell line

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Authors: Abimbola M. Enitan, John O. Odiyo, Feroz M. Swalaha

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The study of microbial ecology and their function in anaerobic digestion processes are essential to control the biological processes. This is to know the symbiotic relationship between the microorganisms that are involved in the conversion of complex organic matter in the industrial wastewater to simple molecules. In this study, diversity and quantity of bacterial community in the granular sludge taken from the different compartments of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated using polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR). The phylogenetic analysis showed three major eubacteria phyla that belong to Proteobacteria, Firmicutes and Chloroflexi in the full-scale UASB reactor, with different groups populating different compartment. The result of qPCR assay showed high amount of eubacteria with increase in concentration along the reactor’s compartment. This study extends our understanding on the diverse, topological distribution and shifts in concentration of microbial communities in the different compartments of a full-scale UASB reactor treating brewery wastewater. The colonization and the trophic interactions among these microbial populations in reducing and transforming complex organic matter within the UASB reactors were established.

Keywords: Bacteria, brewery wastewater, real-time quantitative PCR, UASB reactor.

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Authors: Fatma N. Talkhan, H. H. Abo-Assy, K. A. Soliman, Marwa M. Azzam, A. Z. E. Abdelsalam, A. S. Abdel-Razek

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The Egyptian Bacillus thuringiensis isolate (M5) produce crystal proteins that is toxic against insects was irradiated with UV light to induce mutants. Upon testing 10 of the resulting mutants for their toxicity against cotton leafworm larvae, the three mutants 62, 64 and 85 proved to be the most toxic ones. Upon testing these mutants along with their parental isolate by SDS-PAGE analysis of spores-crystals proteins as well as vegetative cells proteins, new induced bands appeared in the three mutants by UV radiation and also they showed disappearance of some other bands as compared with the wild type isolate. Multiplex PCR technique, with five sets of specific primers, was used to detect the three types of cryI genes cryIAa, cryIAb and cryIAc. Results showed that these three genes exist, as distinctive bands, in the wild type isolate (M5) as well as in mutants 62 and 85, while the mutant 64 had two distinctive bands of cryIAb and cryIAc genes, and a faint band of cryI Aa gene. Finally, these results revealed that mutant 62 is considered as the promising mutant since it is UV resistant, highly toxic against Spodoptera littoralis and active against a wide range of Lepidopteran insects.

Keywords: Bacillus thuringiensis, biological control, cry1 genes, multiplex PC, SDS- PAGE analysis.

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Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

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New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: Information visualization, visual analytics, text mining, visual text analytics tools, big data visualization.

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Authors: Ali Pour Yazdanpanah, Farideh Foroozandeh Shahraki, Emma Regentova

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The reconstruction from sparse-view projections is one of important problems in computed tomography (CT) limited by the availability or feasibility of obtaining of a large number of projections. Traditionally, convex regularizers have been exploited to improve the reconstruction quality in sparse-view CT, and the convex constraint in those problems leads to an easy optimization process. However, convex regularizers often result in a biased approximation and inaccurate reconstruction in CT problems. Here, we present a nonconvex, Lipschitz continuous and non-smooth regularization model. The CT reconstruction is formulated as a nonconvex constrained L1 − L2 minimization problem and solved through a difference of convex algorithm and alternating direction of multiplier method which generates a better result than L0 or L1 regularizers in the CT reconstruction. We compare our method with previously reported high performance methods which use convex regularizers such as TV, wavelet, curvelet, and curvelet+TV (CTV) on the test phantom images. The results show that there are benefits in using the nonconvex regularizer in the sparse-view CT reconstruction.

Keywords: Computed tomography, sparse-view reconstruction, L1 −L2 minimization, non-convex, difference of convex functions.

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Authors: T. Valdbjørn Rasmussen

Abstract:

Design criteria for achieving an acceptable indoor radon concentration are presented in this paper. The paper suggests three design criteria. These criteria have to be considered at the early stage of the building design phase to meet the latest recommendations from the World Health Organization in most countries. The three design criteria are; first, establishing a radon barrier facing the ground; second, lowering the air pressure in the lower zone of the slab on ground facing downwards; third, diluting the indoor air with outdoor air. The first two criteria can prevent radon from infiltrating from the ground, and the third criteria can dilute the indoor air. By combining these three criteria, the indoor radon concentration can be lowered achieving an acceptable level. In addition, a cheap and reliable method for measuring the radon concentration in the indoor air is described. The provision on radon in the Danish Building Regulations complies with the latest recommendations from the World Health Organization. Radon can cause lung cancer and it is not known whether there is a lower limit for when it is not harmful to human beings. Therefore, it is important to reduce the radon concentration as much as possible in buildings. Airtightness is an important factor when dealing with buildings. It is important to avoid air leakages in the building envelope both facing the atmosphere, e.g. in compliance with energy requirements, but also facing the ground, to meet the requirements to ensure and control the indoor environment. Infiltration of air from the ground underneath a building is the main providing source of radon to the indoor air.

Keywords: Radon, natural radiation, barrier, pressure lowering, ventilation.

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Authors: Chien-Min Chu, Bor-Wen Tsai, Kang-Tsung Chang

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Landslide susceptibility map delineates the potential zones for landslide occurrence. Previous works have applied multivariate methods and neural networks for mapping landslide susceptibility. This study proposed a new approach to integrate decision tree model and spatial cluster statistic for assessing landslide susceptibility spatially. A total of 2057 landslide cells were digitized for developing the landslide decision tree model. The relationships of landslides and instability factors were explicitly represented by using tree graphs in the model. The local Getis-Ord statistics were used to cluster cells with high landslide probability. The analytic result from the local Getis-Ord statistics was classed to create a map of landslide susceptibility zones. The map was validated using new landslide data with 482 cells. Results of validation show an accuracy rate of 86.1% in predicting new landslide occurrence. This indicates that the proposed approach is useful for improving landslide susceptibility mapping.

Keywords: Landslide susceptibility Zonation, Decision treemodel, Spatial cluster, Local Getis-Ord statistics.

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Authors: S. Zappacosta, C. Bove, M. Carmela Marinelli, P. di Lauro, K. Spasenovic, L. Ostano, G. Aiello, M. Pietrosanto

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This paper proposes a neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The classification capability was compared with the flood hazard mapping River Basin Plans (Piani Assetto Idrogeologico, acronimed as PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), encoding four different increasing flood hazard levels. The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka

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This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.

Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: Social Media, text mining, knowledge discovery, predictive analysis, machine learning.

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Authors: Jung Ah Park, Zhijie Zhao, Doug Young Suh, Joern Ostermann

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In this paper, we propose an effective relay communication for layered video transmission as an alternative to make the most of limited resources in a wireless communication network where loss often occurs. Relaying brings stable multimedia services to end clients, compared to multiple description coding (MDC). Also, retransmission of only parity data about one or more video layer using channel coder to the end client of the relay device is paramount to the robustness of the loss situation. Using these methods in resource-constrained environments, such as real-time user created content (UCC) with layered video transmission, can provide high-quality services even in a poor communication environment. Minimal services are also possible. The mathematical analysis shows that the proposed method reduced the probability of GOP loss rate compared to MDC and raptor code without relay. The GOP loss rate is about zero, while MDC and raptor code without relay have a GOP loss rate of 36% and 70% in case of 10% frame loss rate.

Keywords: Relay communication, Multiple Description Coding, Scalable Video Coding

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Authors: Parham Azimi, Hamid Reza Charmchi

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In this research, we have developed a new efficient heuristic algorithm for the dynamic facility layout problem with budget constraint (DFLPB). This heuristic algorithm combines two mathematical programming methods such as discrete event simulation and linear integer programming (IP) to obtain a near optimum solution. In the proposed algorithm, the non-linear model of the DFLP has been changed to a pure integer programming (PIP) model. Then, the optimal solution of the PIP model has been used in a simulation model that has been designed in a similar manner as the DFLP for determining the probability of assigning a facility to a location. After a sufficient number of runs, the simulation model obtains near optimum solutions. Finally, to verify the performance of the algorithm, several test problems have been solved. The results show that the proposed algorithm is more efficient in terms of speed and accuracy than other heuristic algorithms presented in previous works found in the literature.

Keywords: Budget constraint, Dynamic facility layout problem, Integer programming, Simulation

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Authors: Mária Hudáková, Mária Lusková

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This report is focused on widening the theoretical knowledge as well as controlling practical application from the risk management point of view, regarding to dynamic business changes that have occurred in Slovakia which recently has been considered to be an environment full of risk and uncertainty. The idea of the report is the proposal of the controlling operation model in the course of risk management process in an enterprise operating in Slovakia, by which the controller is able to identify early risk factors in suggested major areas of the business management upon appropriate business information integration, consecutive control and prognoses and to prepare in time full-value documents in order to suggest measures for reduction thereof. Dealing with risk factors, that can quickly limit the growth potential of the enterprise, is an essential part of managerial activities on each level. This is the reason why mutual unofficial, ergo collegial cooperation of individual departments is necessary for controlling application from the business risk management point of view. An important part of the report is elaborated survey of the most important risk factors existing in major management areas of enterprises operating in Slovakia. The outcome of the performed survey is a catalogue of the most important enterprise risk factors. The catalogue serves for better understanding risk factors affecting the Slovak enterprises, their importance and evaluation.

Keywords: Controlling, information system, risks management, risk factor, crisis of enterprise.

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Authors: S. Oujdi, H. Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 Algorithm, Decision trees, S-CART, Spatial data mining.

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Authors: M. Shirinbayan, J. Fitoussi, N. Abbasnezhad, A. Lucas, A. Tcharkhtchi

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Sheet Molding Compounds (SMCs) with special microstructures are very attractive to use in automobile structures especially when they are accidentally subjected to collision type accidents because of their high energy absorption capacity. These are materials designated as standard SMC, Advanced Sheet Molding Compounds (A-SMC), Low-Density SMC (LD-SMC) and etc. In this study, testing methods have been performed to compare the mechanical responses and damage phenomena of SMC, LD-SMC, and A-SMC under quasi-static and high strain rate tensile tests. The paper also aims at investigating the effect of an initial pre-damage induced by fatigue on the tensile dynamic behavior of A-SMC. In the case of SMCs and A-SMCs, whatever the fibers orientation and applied strain rate are, the first observed phenomenon of damage corresponds to decohesion of the fiber-matrix interface which is followed by coalescence and multiplication of these micro-cracks and their propagations. For LD-SMCs, damage mechanisms depend on the presence of Hollow Glass Microspheres (HGM) and fibers orientation.

Keywords: SMC, LD-SMC, A-SMC, HGM, damage.

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Authors: Ijeoma Chinyere Ukonu

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This research seeks to investigate how the globalisation of fast food has affected students’ food choice. A mixed method approach was used in this research; basically involving quantitative and qualitative methods. The quantitative method uses a self-completion questionnaire to randomly sample one hundred and four students; while the qualitative method uses a semi structured interview technique to survey four students on their knowledge and choice to consume fast food. A cross tabulation of variables and the Kruskal Wallis nonparametric test were used to analyse the quantitative data; while the qualitative data was analysed through deduction of themes, and trends from the interview transcribe. The findings revealed that globalisation has amplified the evolution of fast food, popularising it among students. Its global presence has affected students’ food choice and preference. Price, convenience, taste, and peer influence are some of the major factors affecting students’ choice of fast food. Though, students are familiar with the health effect of fast food and the significance of using food information labels for healthy choice making, their preference of fast food is more than homemade food.

Keywords: Fast food, food choice, globalisation, students.

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Authors: Shiau-Feng Lin, Chiuhsiang Joe Lin, Rou-Wen Wang, Wei-Jung Shiang

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The Virtual Reality (VR) is becoming increasingly important for business, education, and entertainment, therefore VR technology have been applied for training purposes in the areas of military, safety training and flying simulators. In particular, the superior and high reliability VR training system is very important in immersion. Manipulation training in immersive virtual environments is difficult partly because users must do without the hap contact with real objects they rely on in the real world to orient themselves and their manipulated. In this paper, we create a convincing questionnaire of immersion and an experiment to assess the influence of immersion on performance in VR training system. The Immersion Questionnaire (IQ) included spatial immersion, Psychological immersion, and Sensory immersion. We show that users with a training system complete visual attention and detection of signals. Twenty subjects were allocated to a factorial design consisting of two different VR systems (Desktop VR and Projector VR). The results indicated that different VR representation methods significantly affected the participants- Immersion dimensions.

Keywords: Virtual Reality, Training, Immersion, Visual Attention, Visual Detection

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Authors: Ashanie Guanathillake, Kithsiri Samarasinghe

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Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering  algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.

Keywords: Energy efficient, Global re-clustering, Local re-clustering, Wireless sensor networks.

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Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

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In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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Authors: Saeedeh Bakhtiari, Johannes Depessemier, Stijn Hertelé, Wim De Waele

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High cycle fatigue comprising up to 10⁷ load cycles has been the subject of many studies, and the behavior of many materials was recorded adequately in this regime. However, many applications involve larger numbers of load cycles during the lifetime of machine components. In this ultra-high cycle regime, other failure mechanisms play, and the concept of a fatigue endurance limit (assumed for materials such as steel) is often an oversimplification of reality. When machine component design demands a high geometrical complexity, cast iron grades become interesting candidate materials. Grey cast iron is known for its low cost, high compressive strength, and good damping properties. However, the ultra-high cycle fatigue behavior of cast iron is poorly documented. The current work focuses on the ultra-high cycle fatigue behavior of EN-GJL-250 (GG25) grey cast iron by developing an ultrasonic (20 kHz) fatigue testing system. Moreover, the testing machine is instrumented to measure the temperature and the displacement of  the specimen, and to control the temperature. The high resonance frequency allowed to assess the  behavior of the cast iron of interest within a matter of days for ultra-high numbers of cycles, and repeat the tests to quantify the natural scatter in fatigue resistance.

Keywords: GG25, cast iron, ultra-high cycle fatigue, ultrasonic test.

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Authors: Seyed Hossein Iranmanesh, Mansoureh Zarezadeh

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This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.

Keywords: Earned Value Management System (EVMS), Artificial Neural Network (ANN), Estimate At Completion, Forecasting Methods, Project Performance Measurement.

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Authors: Amjad Al Shammari, Ashraf Ibrahim, Laila Seada

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Background and Objectives: Incidence of thyroid carcinoma has been increasing world-wide. In the present study, we evaluated diagnostic accuracy of Fine needle aspiration (FNA) and its efficiency in early detecting neoplastic lesions of thyroid gland over a 3-year period. Methods: Data have been retrieved from pathology files in King Khalid Hospital. For each patient, age, gender, FNA, site & size of nodule and final histopathologic diagnosis were recorded. Results: Study included 490 cases where 419 of them were female and 71 male. Male to female ratio was 1:6. Mean age was 43 years for males and 38 for females. Cases with confirmed histopathology were 131. In 101/131 (77.1%), concordance was found between FNA and histology. In 30/131 (22.9%), there was discrepancy in diagnosis. Total malignant cases were 43, out of which 14 (32.5%) were true positive and 29 (67.44%) were false negative. No false positive cases could be found in our series. Conclusion: FNA could diagnose benign nodules in all cases, however, in malignant cases, ultrasound findings have to be taken into consideration to avoid missing of a microcarcinoma in the contralateral lobe.

Keywords: FNA, hail, histopathology, thyroid.

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Authors: Wittaya Deein, Chockpisit Thepsithar, Aree Thongpukdee

Abstract:

Plant tissue culture is an important in vitro technology applied for agricultural and industrial production. A sterile condition of culture medium is one of the main aspects. The alternative technique for medium sterilization to replace autoclaving was carried out. For sterilization of plant tissue culture medium without autoclaving, ten commercial pure essential oils and 5 disinfectants were tested. Each essential oil or disinfectant was added to a 20-mL Murashige and Skoog (MS) medium before medium was solidified in a 120-mL container, kept for 2 weeks before evaluating sterile conditions. Treated media, supplemented with essential oils or disinfectants, were compared to control medium, autoclaved at 121 degree Celsius for 15 min. Sterile conditions of MS medium were found 100% from betel oil or clove oil (18 mL/20 mL medium), cinnamon oil (36 mL/20 mL medium), lavender oil or holy basil oil (108 mL/20 mL medium), and lemon oil or tea tree oil or turmeric oil (252 mL/20 mL medium), compared to 100% sterile condition from autoclaved medium. For disinfectants, 2% iodine + 2.4% potassium iodide, 2% merbromine solution, 10% povidone-iodine, 6% sodium hypochlorite or 0.1% thimerosal at 36 mL/20 mL medium provided 100% sterile conditions. Furthermore, growth of new shoots from chrysanthemum node explants on treated media (fresh weight, shoot length, root length and number of node) were also reported and discussed in the comparison of those on autoclaved medium.

Keywords: Chrysanthemum, disinfectants, essential oils, MS medium, sterilizing agents, sterilization of medium without autoclaving.

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Authors: C. Ardil

Abstract:

This paper investigates the application of the determinate fuzzy preference programming method for a more nuanced and comprehensive evaluation of stealth aircraft. Traditional methods often struggle to incorporate subjective factors and uncertainties inherent in complex systems like stealth aircraft. Determinate fuzzy preference programming addresses this limitation by leveraging the strengths of determinate fuzzy sets. The proposed novel multiple criteria decision-making algorithm integrates these concepts to consider aspects and criteria influencing aircraft performance. This approach aims to provide a more holistic assessment by enabling decision-makers to observe positive and negative outranking flows simultaneously. By demonstrating the validity and effectiveness of this approach through a practical example of selecting a stealth aircraft, this paper aims to establish the determinate fuzzy preference programming method as a valuable tool for informed decision-making in this critical domain.

Keywords: Determinate fuzzy set, stealth aircraft selection, distance function, decision making, uncertainty, preference programming. MCDM

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