Search results for: adaptive methods

Authors: H. J. Wattimanela, U. S. Passaribu, A. N. T. Puspito, S. W. Indratno

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Molluca Collision Zone is located at the junction of the Eurasian plate, Australian, Pacific, and the Philippines. Between the Sangihe arc, west of the collision zone, and to the east of Halmahera arc is active collision and convex toward the Molluca Sea. This research will analyze the behavior of earthquake occurrence in Molluca Collision Zone related to the distributions of an earthquake in each partition regions, determining the type of distribution of a occurrence earthquake of partition regions, and the mean occurrence of earthquakes each partition regions, and the correlation between the partitions region. We calculate number of earthquakes using partition method and its behavioral using conventional statistical methods. The data used is the data type of shallow earthquakes with magnitudes ≥ 4 SR for the period 1964-2013 in the Molluca Collision Zone. From the results, we can classify partitioned regions based on the correlation into two classes: strong and very strong. This classification can be used for early warning system in disaster management.

Keywords: molluca collision zone, partition regions, conventional statistical methods, earthquakes, classifications, disaster management

Procedia PDF Downloads 486

Authors: Alireza Moghtaderi, Negin Khakpour

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Disc Herniation is a common complication in the society and it is one of the main reasons for referring to physical medicine and rehabilitation clinics. Despite of various methods proposed for treatingthis disease, still there is disagreement on success of these methods especially in non-surgical methods, and thus current study aims at determining effect of laser beam and magnet on treatment of Intervertebral Disc Herniation. During a clinical trial study, 80 patients with Intervertebral Disc Herniation underwent a combined package of treatment including magnet, laser beam, PRP and Prolotherapy during 6 months. Average age of patients was 51.25 ± 10.7 with range of 25 – 71 years. 30 men (37.5%) and 50 women (62.5%) took part in the study. average weight of patients was 64.3 ± 7.2 with range of 49 – 79 kg. highest level of Disc Herniation was L5 – S1 with frequency of 17 cases (21.3%). Disc Herniation was severe in 30 cases before treatment, but it reduced to 3 casesafter treatment. This study indicates effect of combined treatment using non-invasive laser beam and magnet therapy on disco genic diseases and mechanical pains of spine is highly effective.

Keywords: hallux, valgus, botulinum toxin a, pain

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Authors: Nguyen Tien Thanh, Günter Meon

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Precipitation plays a key role in water cycle, defining the local climatic conditions and in ecosystem. It is also an important input parameter for water resources management and hydrologic models. With spatial continuous data, a certainty of discharge predictions or other environmental factors is unquestionably better than without. This is, however, not always willingly available to acquire for a small basin, especially for coastal region in Vietnam due to a low network of meteorological stations (30 stations) on long coast of 3260 km2. Furthermore, available gridded precipitation datasets are not fine enough when applying to hydrologic models. Under conditions of global warming, an application of spatial interpolation methods is a crucial for the climate change impact studies to obtain the spatial continuous data. In recent research projects, although some methods can perform better than others do, no methods draw the best results for all cases. The objective of this paper therefore, is to investigate different spatial interpolation methods for daily precipitation over a small basin (approximately 400 km2) located in coastal region, Southern Vietnam and find out the most efficient interpolation method on this catchment. The five different interpolation methods consisting of cressman, ordinary kriging, regression kriging, dual kriging and inverse distance weighting have been applied to identify the best method for the area of study on the spatio-temporal scale (daily, 10 km x 10 km). A 30-year precipitation database was created and merged into available gridded datasets. Finally, observed changes in constructed precipitation were performed. The results demonstrate that the method of ordinary kriging interpolation is an effective approach to analyze the daily precipitation. The mixed trends of increasing and decreasing monthly, seasonal and annual precipitation have documented at significant levels.

Keywords: interpolation, precipitation, trend, vietnam

Procedia PDF Downloads 271

Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

Procedia PDF Downloads 262

Authors: Hamad Alhamad, Catriona Khamisha, Emma Green, Yvonne Robb

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Introduction: Practice education is a key component of occupational therapy education. This critical review aimed to explore students’ and clinical supervisors’ experiences of practice education, and to make recommendations for research. Method: The literature was systematically searched using five databases. Qualitative, quantitative and mixed methods studies were included. Critical Appraisal Skills Programme checklist for qualitative studies and Mixed Methods Assessment Tool for quantitative and mixed methods studies were used to assess study quality. Findings: Twenty-two studies with high quality scores were included: 16 qualitative, 3 quantitative and 3 mixed methods. Studies were conducted in Australia, Canada, USA and UK. During practice education, students learned professional skills, practical skills, clinical skills and problem-solving skills, and improved confidence and creativity. Supervisors had an opportunity to reflect on their practice and get experience of supervising students. However, clear objectives and expectations for students, and sufficient theoretical knowledge, preparation and resources for supervisors were required. Conclusion: Practice education provides different skills and experiences, necessary to become competent professionals; but some areas of practice education need to improve. Studies in non-western countries are needed to explore the perspectives of students and clinical supervisors in different cultures, to ensure the practice education models adopted are relevant.

Keywords: occupational therapy, practice education, fieldwork, students, clinical supervisors

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Authors: Dimitra Alexiou

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During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: tourism, statistical methods, exponential smoothing, land spatial planning, economy

Procedia PDF Downloads 250

Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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Authors: Prachi Choudhary, Jai Gopal Sharma

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Microbial cultures determine the type of organism, its abundance in the tested sample, or both. It is one of the primary diagnostic methods of microbiology. It is used to determine the cause of infectious disease by letting the agent multiply in a predetermined medium. Different bacteria produce colonies that may be very distinct from the bacterial species that produced them. To culture any pathogen or microorganism, we should first know about the types of media used in microbiology for culturing. Sometimes sub culturing is also done in various microorganisms if some mixed growth is seen in culture. Nearly 3 types of culture media based on consistency – solid, semi-solid, and liquid (broth) media; are further explained in the report. Then, The Five I's approach is a method for locating, growing, observing, and characterizing microorganisms, including inoculation and incubation. Isolation, inspection, and identification. For identification of bacteria, we have to culture the sample like urine, sputum, blood, etc., on suitable media; there are different methods of culturing the bacteria or microbe like pour plate method, streak plate method, swabbing by needle, pipetting, inoculation by loop, spreading by spreader, etc. After this, we see the bacterial growth after incubation of 24 hours, then according to the growth of bacteria antibiotics susceptibility test is conducted; this is done for sensitive antibiotics or resistance to that bacteria, and also for knowing the name of bacteria. Various methods like the dilution method, disk diffusion method, E test, etc., do antibiotics susceptibility tests. After that, various medicines are provided to the patients according to antibiotic sensitivity and resistance.

Keywords: inoculation, incubation, isolation, antibiotics suspectibility test, characterizing

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Authors: Martynova Alina, Lyubov Buzoleva

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Streptococcus pneumoniae is the causative agent of pneumonias and meningitids throught all the world. Having high genetic diversity, this microorganism can cause different clinical forms of pneumococcal infections and microbiologically it is really difficult diagnosed by routine methods. Also, epidemiological surveillance requires more developed methods of molecular typing because the recent method of serotyping doesn't allow to distinguish invasive and non-invasive isolates properly. Non-coding genome of bacteria seems to be the interesting source for seeking of highly distinguishable markers to discriminate the subspecies of such a variable bacteria as Streptococcus pneumoniae. Technically, we proposed scheme of discrimination of S.pneumoniae strains with amplification of non-coding region (SP_1932) with the following restriction with 2 types of enzymes of Alu1 and Mn1. Aim: This research aimed to compare different methods of typing and their application for molecular epidemiology purposes. Methods: we analyzed population of 100 strains of S.pneumoniae isolated from different patients by different molecular epidemiology methods such as pulse-field gel electophoresis (PFGE), restriction polymorphism analysis (RFLP) and multilolocus sequence typing (MLST), and all of them were compared with classic typing method as serotyping. The discriminative power was estimated with Simpson Index (SI). Results: We revealed that the most discriminative typing method is RFLP (SI=0,97, there were distinguished 42 genotypes).PFGE was slightly less discriminative (SI=0,95, we identified 35 genotypes). MLST is still the best reference method (SI=1.0). Classic method of serotyping showed quite weak discriminative power (SI=0,93, 24 genotypes). In addition, sensivity of RFLP was 100%, specificity was 97,09%. Conclusion: the most appropriate method for routine epidemiology surveillance is RFLP with non-coding region of Streptococcsu pneumoniae, then PFGE, though in some cases these results should be obligatory confirmed by MLST.

Keywords: molecular epidemiology typing, non-coding genome, Streptococcus pneumoniae, MLST

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Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

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Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

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Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

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Authors: Jianrong Wu, Xuan Fu, Akihiro Higashi, Zhiming Tan

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CMOS image sensors with a rolling shutter are used broadly in the digital cameras embedded in mobile devices. The rolling shutter suffers the flicker artifacts from the fluorescent lamp, and it could be observed easily. In this paper, the characteristics of illumination flicker in motion case were analyzed, and two efficient detection methods based on matching fragment selection were proposed. According to the experimental results, our methods could achieve as high as 100% accuracy in static scene, and at least 97% in motion scene.

Keywords: illumination flicker, embedded camera, rolling shutter, detection

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Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

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To address the problem that the FM continuous-wave radar (FMCW) extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a new detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a BP neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise and accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal-to-noise ratio of the sign signals.

Keywords: frequency modulated continuous wave radar, ICEEMDAN, BP neural network, vital signs signal

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Authors: Qiyao Han, Xianhai Meng

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Urban infrastructures refer to the fundamental facilities and systems that serve cities. Due to the global climate change and human activities in recent years, many urban areas around the world are facing enormous challenges from natural and man-made disasters, like flood, earthquake and terrorist attack. For this reason, urban resilience to disasters has attracted increasing attention from researchers and practitioners. Given the complexity of infrastructure systems and the uncertainty of disasters, this paper suggests that studies of resilience could focus on urban functional sustainability (in social, economic and environmental dimensions) supported by infrastructure systems under disturbance. It is supposed that urban infrastructure systems with high resilience should be able to reconfigure themselves without significant declines in critical functions (services), such as primary productivity, hydrological cycles, social relations and economic prosperity. Despite that some methods have been developed to integrate the resilience and sustainability of individual infrastructure components, more work is needed to enable system-level integration. This research presents a conceptual analysis framework for integrating resilience and sustainability based on fractal theory. It is believed that the ability of an ecological system to maintain structure and function in face of disturbance and to reorganize following disturbance-driven change is largely dependent on its self-similar and hierarchical fractal structure, in which cross-scale resilience is produced by the replication of ecosystem processes dominating at different levels. Urban infrastructure systems are analogous to ecological systems because they are interconnected, complex and adaptive, are comprised of interconnected components, and exhibit characteristic scaling properties. Therefore, analyzing resilience of ecological system provides a better understanding about the dynamics and interactions of infrastructure systems. This paper discusses fractal characteristics of ecosystem resilience, reviews literature related to system-level infrastructure resilience, identifies resilience criteria associated with sustainability dimensions, and develops a conceptual analysis framework. Exploration of the relevance of identified criteria to fractal characteristics reveals that there is a great potential to analyze infrastructure systems based on fractal. In the conceptual analysis framework, it is proposed that in order to be resilient, urban infrastructure system needs to be capable of “maintaining” and “reorganizing” multi-scale critical functions under disasters. Finally, the paper identifies areas where further research efforts are needed.

Keywords: fractal, urban infrastructure, sustainability, system-level resilience

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: YU Kaijun, Liang Dong, Zhang Yarong, Jin Zhenzhou, Yang Zhaobao

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For the impact monitoring of distributed structures, the traditional positioning methods are based on the time difference, which includes the four-point arc positioning method and the triangulation positioning method. But in the actual operation, these two methods have errors. In this paper, the Multi-Agent Blackboard Coordination Principle is used to combine the two methods. Fusion steps: (1) The four-point arc locating agent calculates the initial point and records it to the Blackboard Module.(2) The triangulation agent gets its initial parameters by accessing the initial point.(3) The triangulation agent constantly accesses the blackboard module to update its initial parameters, and it also logs its calculated point into the blackboard.(4) When the subsequent calculation point and the initial calculation point are within the allowable error, the whole coordination fusion process is finished. This paper presents a Multi-Agent collaboration method whose agent framework is JADE. The JADE platform consists of several agent containers, with the agent running in each container. Because of the perfect management and debugging tools of the JADE, it is very convenient to deal with complex data in a large structure. Finally, based on the data in Jade, the results show that the impact location method based on Multi-Agent coordination fusion can reduce the error of the two methods.

Keywords: impact monitoring, structural health monitoring(SHM), multi-agent system(MAS), black-board coordination, JADE

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Distillation is one of the most important and utilized separation methods in the industrial practice. There are different ways to design of distillation column. One of these ways is short cut method. In short cut method, material balance and equilibrium are employed to calculate number of tray in distillation column. There are different methods that are classified in short cut method. One of these methods is Fenske-Underwood-Gilliland method. In this method, minimum reflux ratio should be calculated by underwood equation. Underwood proposed an equation that is useful for simple distillation column with one feed and one top and bottom product. In this study, underwood method is developed to predict minimum reflux ratio for column with one side stream upper than feed. The result of this model compared with McCabe-Thiele method. The result shows that proposed method able to calculate minimum reflux ratio with very small error.

Keywords: minimum reflux ratio, side stream, distillation, Underwood’s method

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: adaptive filtering, sparse system identification, TD-LMS algorithm, VSSLMS algorithm

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Authors: Ali Bolat, Ali Bayat, Mustafa Gullu

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Maize can be cultivated both under main and second crop conditions in Turkey. Main pests of maize under second crop conditions are Sesamia nonagrioides Lefebvre (Lepidoptera: Noctuidae) and Ostrinia nubilalis Hübner (Lepidoptera: Crambidae). Aerial spraying applications to control these two main maize pests can be carried out until 2006 in Turkey before it was banned due to environmental concerns like drifting of sprayed pestisides and low biological efficiency. In this context, pulverizers which can spray tall maize plants ( > 175 cm) from the ground have begun to be used. However, the biological efficiency of these sprayers is unknown. Some methods have been tested to increase the success of ground spraying in field experiments conducted in second crop maize in 2008 and 2009. For this aim, 6 spraying methods (air assisted spraying with TX cone jet, domestic cone nozzles, twinjet nozzles, air induction nozzles, standard domestic cone nozzles and tail booms) were used at two application rates (150 and 300 l.ha-1) by a sprayer. In the study, biological efficacy evaluations of each methods were measured in each parcel. Biological efficacy evaluations included counts of number of insect damaged plants, number of holes in stems and live larvae and pupa in stems of selected plants. As a result, the highest biological efficacy value (close to 70%) was obtained from Air Assisted Spraying method at 300 l / ha application volume.

Keywords: air assisted sprayer, drift nozzles, biological efficiency, maize plant

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Authors: Eduardo F. Mello, Peter H. Bauer

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The primary focus of this paper is the generation of energy-optimal speed trajectories for heterogeneous electric vehicle platoons in urban driving conditions. Optimal speed trajectories are generated for individual vehicles and for an entire platoon under the assumption that they can be executed without errors, as would be the case for self-driving vehicles. It is then shown that the optimization for the “average vehicle in the platoon” generates similar transportation energy savings to optimizing speed trajectories for each vehicle individually. The introduced approach only requires the lead vehicle to run the optimization software while the remaining vehicles are only required to have adaptive cruise control capability. The achieved energy savings are typically between 30% and 50% for stop-to-stop segments in cities. The prime motivation of urban platooning comes from the fact that urban platoons efficiently utilize the available space and the minimization of transportation energy in cities is important for many reasons, i.e., for environmental, power, and range considerations.

Keywords: electric vehicles, energy efficiency, optimization, platooning, self-driving vehicles, urban traffic

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Authors: Essam Al Daoud

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Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

Procedia PDF Downloads 159

Authors: Amare Setegn Enyew, Bikila Teklu Wodajo

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The primary aim of flexible pavement design is to ensure the development of economical and safe road infrastructure. However, failures can still occur due to improper or erroneous structural design. In Ethiopia, the design of flexible pavements relies on doing calculations manually and selecting pavement structure from catalogue. The catalogue offers, in eight different charts, alternative structures for combinations of traffic and subgrade classes, as outlined in the Ethiopian Roads Authority (ERA) Pavement Design Manual 2001. Furthermore, design modification is allowed in accordance with the structural number principles outlined in the AASHTO 1993 Guide for Design of Pavement Structures. Nevertheless, the manual calculation and design process involves the use of nomographs, charts, tables, and formulas, which increases the likelihood of human errors and inaccuracies, and this may lead to unsafe or uneconomical road construction. To address the challenge, a software called AASHERA has been developed for AASHTO 1993 and ERA design methods, using MATLAB language. The software accurately determines the required thicknesses of flexible pavement surface, base, and subbase layers for the two methods. It also digitizes design inputs and references like nomographs, charts, default values, and tables. Moreover, the software allows easier comparison of the two design methods in terms of results and cost of construction. AASHERA's accuracy has been confirmed through comparisons with designs from handbooks and manuals. The software can aid in reducing human errors, inaccuracies, and time consumption as compared to the conventional manual design methods employed in Ethiopia. AASHERA, with its validated accuracy, proves to be an indispensable tool for flexible pavement structure designers.

Keywords: flexible pavement design, AASHTO 1993, ERA, MATLAB, AASHERA

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Authors: Chau Nguyen Pham Minh

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The aim of this study is to answer the following research question: What do we know about virtual customer integration in innovation development based on existing empirical research? The paper is based on a systematic review of 136 articles which were published in the past 16 years. The analysis focuses on three areas: what forms of virtual customer integration (e.g. netnography, online co-creation, virtual experience) have been applied in innovation development; how have virtual customer integration methods effectively been utilized by firms; and what are the influences of virtual customer integration on innovation development activities? Through the detailed analysis, the study provides researchers with broad understanding about virtual customer integration in innovation development. The study shows that practitioners and researchers increasingly pay attention on using virtual customer integration methods in developing innovation since those methods have dominant advantages in interact with customers in order to generate the best ideas for innovation development. Additionally, the findings indicate that netnography has been the most common method in integrating with customers for idea generation; while virtual product experience has been mainly used in product testing. Moreover, the analysis also reveals the positive and negative influences of virtual customer integration in innovation development from both process and strategic perspectives. Most of the review studies examined the phenomenon from company’s perspectives to understand the process of applying virtual customer integration methods and their impacts; however, the customers’ perspective on participating in the virtual interaction has been inadequately studied; therefore, it creates many potential interesting research paths for future studies.

Keywords: innovation, virtual customer integration, co-creation, netnography, new product development

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Authors: Mohamed A. Moustafa Hassan, Omnia S .S. Hussian, Hany M. Elsaved

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This paper introduces the application of Fuzzy Logic Controller (FLC) to extract the Maximum Power Point Tracking (MPPT) from the PV panel. In addition, the proportional integral (PI) controller is used to be the strategy for battery charge control according to acceptable performance criteria. The parameters of the PI controller have been tuned via Modified Adaptive Accelerated Coefficient Particle Swarm Optimization (MAACPSO) technique. The simulation results, using MATLAB/Simulink tools, show that the FLC technique has advantages for use in the MPPT problem, as it provides a fast response under changes in environmental conditions such as radiation and temperature. In addition, the use of PI controller based on MAACPSO results in a good performance in terms of controlling battery charging with constant voltage and current to execute rapid charging.

Keywords: battery charging, fuzzy logic control, maximum power point tracking, PV system, PI controller, evolutionary technique

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Authors: Kika Ioannou Kazamia

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This paper examines the action research cycle of the second phase of longitudinal research on sustainable interior design practices, between two groups of stakeholders, designers and clients. During this phase of the action research, the second step - the change stage - of Lewin’s change management model has been utilized to change values, approaches, and attitudes toward sustainable design practices among the participants. Affective domain learning theory is utilized to attach new values. Learning with the use of information technology, collaborative learning, and problem-based learning are the learning methods implemented toward the acquisition of the objectives. Learning methods, and aims, require the design of interventions with participants' involvement in activities that would lead to the acknowledgment of the benefits of sustainable practices. Interventions are steered to measure participants’ decisions for the worth and relevance of ideas, and experiences; accept or commit to a particular stance or action. The data collection methods used in this action research are observers’ reports, participants' questionnaires, and interviews. The data analyses use both quantitative and qualitative methods. The main beneficial aspect of the quantitative method was to provide the means to separate many factors that obscured the main qualitative findings. The qualitative method allowed data to be categorized, to adapt the deductive approach, and then examine for commonalities that could reflect relevant categories or themes. The results from the data indicate that during the second phase, designers and clients' participants altered their behaviours.

Keywords: design, change, sustainability, learning, practices

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Authors: Irene T. Ho

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Students with Autism Spectrum Disorder (ASD) studying in mainstream schools often face difficulties adjusting to school life and teachers often find it challenging to meet the needs of these students. The Hong Kong Jockey Club Autism Support Network (JC A-Connect) is an initiative launched in 2015 to enhance support for students with ASD as well as their families and schools. The School Support Programme of the Project aims at building the capacity of schools to provide quality education for these students. The present report provides a summary of the main features of the support model and the related evaluation results. The school support model was conceptualized in response to four observed needs: (1) inadequate teacher expertise in dealing with the related challenges, (2) the need to promote evidence-based practices in schools, (3) less than satisfactory home-school collaboration and whole-school participation, and (4) lack of concerted effort by different parties involved in providing support to schools. The resulting model had partnership and capacity building as two guiding tenets for the School Support Programme. There were two levels of partnership promoted in the project. At the programme support level, a platform that enables effective collaboration among major stakeholders was established, including the funding body that provides the necessary resources, the Education Bureau that helps to engage schools, university experts who provide professional leadership and research support, as well as non-governmental organization (NGO) professionals who provide services to the schools. At the programme implementation level, tripartite collaboration among teachers, parents and professionals was emphasized. This notion of partnership permeated efforts at capacity building targeting students with ASD, school personnel, parents and peers. During 2015 to 2018, school-based programmes were implemented in over 400 primary and secondary schools with the following features: (1) spiral Tier 2 (group) training for students with ASD to enhance their adaptive skills, led by professionals but with strong teacher involvement to promote transfer of knowledge and skills; (2) supplementary programmes for teachers, parents and peers to enhance their capability to support students with ASD; and (3) efforts at promoting continuing or transfer of learning, on the part of both students and teachers, to Tier 1 (classroom practice) and Tier 3 (individual training) contexts. Over 5,000 students participated in the Programme, representing about 50% of students diagnosed with ASD in mainstream public sector schools in Hong Kong. Results showed that the Programme was effective in helping students improve to various extents at three levels: achievement of specific training goals, improvement in adaptive skills in school, and change in ASD symptoms. The sense of competence of teachers and parents in dealing with ASD-related issues, measured by self-report rating scales, was also significantly enhanced. Moreover, effects on enhancing the school system to provide support for students with ASD, assessed according to indicators of inclusive education, were seen. The process and results of this Programme illustrate how obstacles to inclusive education for students with ASD could be overcome by strengthening the necessary partnerships and building the required capabilities of all parties concerned.

Keywords: autism, school support, skills training, teacher development, three-tier model

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Authors: Akiyoshi Wakatani

Abstract:

This paper describes the Message Passing Interface (MPI) implementation of ADETRAN language, and its evaluation on SX-ACE supercomputers. ADETRAN language includes pdo statement that specifies the data distribution and parallel computations and pass statement that specifies the redistribution of arrays. Two methods for implementation of pass statement are discussed and the performance evaluation using Splitting-Up CG method is presented. The effectiveness of the parallelization is evaluated and the advantage of one dimensional distribution is empirically confirmed by using the results of experiments.

Keywords: iterative methods, array redistribution, translator, distributed memory

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Authors: Hajnalka Szarvas

Abstract:

The research examines the effectiveness of e-participation tools and methods from a point of view of cultural fitting to the Hungarian community traditions. Participation can have very different meanings depending on the local cultural and historical traditions, experiences of the certain societies. Generally when it is about e-democracy or e-participation tools most of the researches are dealing with its technological sides and novelties, but there is not much said about the cultural and social context of the different platforms. However from the perspective of their success it would be essential to look at the human factor too, the actual users, how the certain DMS or any online platform is fitting to the way of thought, the way of functioning of the certain society. Therefore the paper will explore that to what extent the different online platforms like Loomio, Democracy OS, Your Priorities EVoks, Populus, miutcank.hu, Liquid Democracy, Brain Bar Budapest Lab are compatible with the Hungarian mental structures and community traditions, the contents of collective mind about community functioning. As a result the influence of cultural embeddedness of the logic of e-participation development tools on success of these methods will be clearly seen. Furthermore the most crucial factors in general which determine the efficiency of e-participation development tools in Hungary will be demonstrated.

Keywords: cultural embeddedness, e-participation, local community traditions, mental structures

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Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

Abstract:

Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Keywords: adaptive complex systems, X-Events, risk management, antifragility, banking antifragility index, triangular fuzzy number

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Authors: Mohsen Maadani, Seyed Ahmad Motamedi

Abstract:

The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. An adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.

Keywords: average delay, contention window, distributed coordination function (DCF), jitter, industrial wireless network (IWN), maximum delay, reliability, retry limit

Procedia PDF Downloads 410