Search results for: active distribution network (ADN)

Authors: Naveed Ghani

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With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.

Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2

Procedia PDF Downloads 426

Authors: Ayman Othman, Tallat Ali

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A pavement maintenance management system (PMMS) was developed for the city of Aswan as a model of a small city to provide the road maintenance department in Aswan city with the capabilities for comprehensive planning of the maintenance activities needed to put the internal pavement network into desired physical condition in view of maintenance budget constraints. The developed system consists of three main stages. First is the inventory & condition survey stage where the internal pavement network of Aswan city was inventoried and its actual conditions were rated in segments of 100 meters length. Second is the analysis stage where pavement condition index (PCI) was calculated and the most appropriate maintenance actions were assigned for each segment. The total maintenance budget was also estimated and a parameter based ranking criteria were developed to prioritize maintenance activities when the available maintenance budget is not sufficient. Finally comes the packaging stage where approved maintenance budget is packed into maintenance projects for field implementation. System results indicate that, the system output maintenance budget is very reasonable and the system output maintenance programs agree to a great extent with the actual maintenance needs of the network. Condition survey of Aswan city road network showed that roughness is the most dominate distress. In general, the road network can be considered in a fairly reasonable condition, however, the developed PMMS needs to be officially adapted to maintain the road network in a desirable condition and to prevent further deterioration.

Keywords: pavement, maintenance, management, system, distresses, survey, ranking

Procedia PDF Downloads 248

Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

Procedia PDF Downloads 481

Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

Procedia PDF Downloads 382

Authors: Mounia El Hafyani, Khalid El Himdi

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Precipitation is one of the key variables in water resource planning. The importance of modeling wet and dry durations is a crucial pointer in engineering hydrology. The objective of this study is to model and analyze the distribution of wet and dry durations. For this purpose, the daily rainfall data from 1967 to 2017 of the Moroccan city of Kenitra’s station are used. Three models are implemented for the distribution of wet and dry durations, namely the first-order Markov chain, the second-order Markov chain, and the truncated negative binomial law. The adherence of the data to the proposed models is evaluated using Chi-square and Kolmogorov-Smirnov tests. The Akaike information criterion is applied to assess the most effective model distribution. We go further and study the law of the number of wet and dry days among k consecutive days. The calculation of this law is done through an algorithm that we have implemented based on conditional laws. We complete our work by comparing the observed moments of the numbers of wet/dry days among k consecutive days to the calculated moment of the three estimated models. The study shows the effectiveness of our approach in modeling wet and dry durations of daily precipitation.

Keywords: Markov chain, rainfall, truncated negative binomial law, wet and dry durations

Procedia PDF Downloads 125

Authors: Bachir Chemani, Rachid Halfaoui

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The aim of work is to define the distribution density of winding yarn on cylindrical and conical bobbins. It is known that parallel winding gives greater density and more regular distribution, but the unwinding of yarn is much more difficult for following process. The conical spool has an enormous advantage during unwinding and may contain a large amount of yarns, but the density distribution is not regular because of difference in diameters. The variation of specific density over the reel height is explained generally by the sudden change of winding speed due to direction movement variation of yarn. We determined the conditions of uniform winding and developed a calculate model to the change of the specific density of winding wire over entire spool height.

Keywords: textile, cylindrical bobbins, conical bobbins, parallel winding, cross winding

Procedia PDF Downloads 377

Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

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Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

Procedia PDF Downloads 479

Authors: Wikanda Phaphan

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Mixture generalized gamma distribution is a combination of two distributions: generalized gamma distribution and length biased generalized gamma distribution. These two distributions were presented by Suksaengrakcharoen and Bodhisuwan in 2014. The findings showed that probability density function (pdf) had fairly complexities, so it made problems in estimating parameters. The problem occurred in parameter estimation was that we were unable to calculate estimators in the form of critical expression. Thus, we will use numerical estimation to find the estimators. In this study, we presented a new method of the parameter estimation by using the expectation – maximization algorithm (EM), the conjugate gradient method, and the quasi-Newton method. The data was generated by acceptance-rejection method which is used for estimating α, β, λ and p. λ is the scale parameter, p is the weight parameter, α and β are the shape parameters. We will use Monte Carlo technique to find the estimator's performance. Determining the size of sample equals 10, 30, 100; the simulations were repeated 20 times in each case. We evaluated the effectiveness of the estimators which was introduced by considering values of the mean squared errors and the bias. The findings revealed that the EM-algorithm had proximity to the actual values determined. Also, the maximum likelihood estimators via the conjugate gradient and the quasi-Newton method are less precision than the maximum likelihood estimators via the EM-algorithm.

Keywords: conjugate gradient method, quasi-Newton method, EM-algorithm, generalized gamma distribution, length biased generalized gamma distribution, maximum likelihood method

Procedia PDF Downloads 219

Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

Procedia PDF Downloads 75

Authors: Mahdi Kiani, Hassan Salarieh, Aria Alasty, S. Mahdi Darbandi

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The design and implementation of the hybrid control method for a three-pole active magnetic bearing (AMB) is proposed in this paper. The system is inherently nonlinear and conventional nonlinear controllers are a little complicated, while the proposed hybrid controller has a piecewise linear form, i.e. linear in each sub-region. A state-feedback hybrid controller is designed in this study, and the unmeasurable states are estimated by an observer. The gains of the hybrid controller are obtained by the Linear Quadratic Regulator (LQR) method in each sub-region. To evaluate the performance, the designed controller is implemented on an experimental setup in static mode. The experimental results show that the proposed method can efficiently stabilize the three-pole AMB system. The simplicity of design, domain of attraction, uncomplicated control law, and computational time are advantages of this method over other nonlinear control strategies in AMB systems.

Keywords: active magnetic bearing, three pole AMB, hybrid control, Lyapunov function

Procedia PDF Downloads 342

Authors: Erin Hea-Jin Kim

Abstract:

This study aims to investigate scholarly communication patterns in Korean studies, which focuses on all aspects of Korea, including history, culture, literature, politics, society, economics, religion, and so on. It is called ‘national study or home study’ as the subject of the study is itself, whereas it is called ‘area study’ as the subject of the study is others, i.e., outside of Korea. Understanding of the structure of scholarly communication in Korean studies is important since the motivations, procedures, results, or outcomes of individual studies may be affected by the cooperative relationships that appear in the communication structure. To this end, we collected 1,798 articles with the (author or index) keyword ‘Korean’ published in 2018 from the Scopus database and extracted the institution and country of the authors using a text mining technique. A total of 96 countries, including South Korea, was identified. Then we constructed a co-authorship network based on the countries identified. The indicators of social network analysis (SNA), co-occurrences, and cluster analysis were used to measure the activity and connectivity of participation in collaboration in Korean studies. As a result, the highest frequency of collaboration appears in the following order: S. Korea with the United States (603), S. Korea with Japan (146), S. Korea with China (131), S. Korea with the United Kingdom (83), and China with the United States (65). This means that the most active participants are S. Korea as well as the USA. The highest rank in the role of mediator measured by betweenness centrality appears in the following order: United States (0.165), United Kingdom (0.045), China (0.043), Japan (0.037), Australia (0.026), and South Africa (0.023). These results show that these countries contribute to connecting in Korean studies. We found two major communities among the co-authorship network. Asian countries and America belong to the same community, and the United Kingdom and European countries belong to the other community. Korean studies have a long history, and the study has emerged since Japanese colonization. However, Korean studies have never been investigated by digital content analysis. The contributions of this study are an analysis of co-authorship in Korean studies with a global perspective based on digital content, which has not attempted so far to our knowledge, and to suggest ideas on how to analyze the humanities disciplines such as history, literature, or Korean studies by text mining. The limitation of this study is that the scholarly data we collected did not cover all domestic journals because we only gathered scholarly data from Scopus. There are thousands of domestic journals not indexed in Scopus that we can consider in terms of national studies, but are not possible to collect.

Keywords: co-authorship network, Korean studies, Koreanology, scholarly communication

Procedia PDF Downloads 158

Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

Procedia PDF Downloads 228

Authors: Min Ye Koo, Ji Ho Ahn, Byung Il You, Gyo Woo Lee

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Everything that is attached to the outside of the vehicle to improve the driving performance of the vehicle by changing the flow characteristics of the surrounding air or to pursue the external personality is called a tuning part. Typical tuning components include front or rear air dam, also known as spoilers, splitter, and side air dam. Particularly, the front air dam prevents the airflow flowing into the lower portion of the vehicle and increases the amount of air flow to the side and front of the vehicle body, thereby reducing lift force generation that lifts the vehicle body, and thus, improving the steering and driving performance of the vehicle. The purpose of this study was to investigate the role of anterior air dam in the flow around a sedan passenger car using computational fluid dynamics. The effects of flow velocity, trajectory of fluid particles on static pressure distribution and pressure distribution on body surface were investigated by varying flow velocity and size of air dam. As a result, it has been confirmed that the front air dam improves the flow characteristics, thereby reducing the generation of lift force of the vehicle, so it helps in steering and driving characteristics.

Keywords: numerical study, air dam, flow field, pressure distribution

Procedia PDF Downloads 207

Authors: Muhammad Qasim, Laura Minet

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Victoria (BC), Canada, is a major cruise ship destination, attracting over 600,000 tourists annually. Residents of the James Bay neighborhood, home to the Ogden Point cruise terminal, have expressed concerns about the impacts of cruise ship activity on local traffic, air pollution, and safety compliance. This study evaluates the effects of cruise ship-induced traffic in James Bay, focusing on traffic flow intensification, density surges, changes in traffic mix, and speeding violations. To achieve these objectives, traffic data was collected in James Bay during two key periods: May, before the peak cruise season, and August, during full cruise operations. Three Miovision cameras captured the vehicular traffic mix at strategic entry points, while nine traffic counters monitored traffic distribution and speeding violations across the network. Traffic data indicated an average volume of 308 vehicles per hour during peak cruise times in May, compared to 116 vehicles per hour when no ships were in port. Preliminary analyses revealed a significant intensification of traffic flow during cruise ship "hoteling hours," with a volume increase of approximately 10% per cruise ship arrival. A notable 86% surge in taxi presence was observed on days with three cruise ships in port, indicating a substantial shift in traffic composition, particularly near the cruise terminal. The number of tourist buses escalated from zero in May to 32 in August, significantly altering traffic dynamics within the neighborhood. The period between 8 pm and 11 pm saw the most significant increases in traffic volume, especially when three ships were docked. Higher vehicle volumes were associated with a rise in speed violations, although this pattern was inconsistent across all areas. Speeding violations were more frequent on roads with lower traffic density, while roads with higher traffic density experienced fewer violations, due to reduced opportunities for speeding in congested conditions. PTV VISUM software was utilized for fuzzy distribution analysis and to visualize traffic distribution across the study area, including an assessment of the Level of Service on major roads during periods before and during the cruise ship season. This analysis identified the areas most affected by cruise ship-induced traffic, providing a detailed understanding of the impact on specific parts of the transportation network. These findings underscore the significant influence of cruise ship activity on traffic dynamics in Victoria, BC, particularly during peak periods when multiple ships are in port. The study highlights the need for targeted traffic management strategies to mitigate the adverse effects of increased traffic flow, changes in traffic mix, and speed violations, thereby enhancing road safety in the James Bay neighborhood. Further research will focus on detailed emissions estimation to fully understand the environmental impacts of cruise ship activity in Victoria.

Keywords: cruise ship tourism, air quality, traffic violations, transport dynamics, pollution

Procedia PDF Downloads 22

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

Procedia PDF Downloads 317

Authors: Jie Su, Zhenghua Zhou, Yushi Wang, Yongyi Li

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The ground motion characteristics, which are given by the analysis of acceleration records, underlie the formulation and revision of the seismic design code of structural engineering. China Digital Strong Motion Network had recorded a lot of accelerograms of main shock from 478 permanent seismic stations, during the Ms8.0 Wenchuan earthquake on 12th May, 2008. These accelerograms provided a large number of essential data for the analysis of ground motion characteristics of the event. The spatial distribution characteristics, rupture directivity effect, hanging-wall and footwall effect had been studied based on these acceleration records. The results showed that the contours of horizontal peak ground acceleration and peak velocity were approximately parallel to the seismogenic fault which demonstrated that the distribution of the ground motion intensity was obviously controlled by the spatial extension direction of the seismogenic fault. Compared with the peak ground acceleration (PGA) recorded on the sites away from which the front of the fault rupture propagates, the PGA recorded on the sites toward which the front of the fault rupture propagates had larger amplitude and shorter duration, which indicated a significant rupture directivity effect. With the similar fault distance, the PGA of the hanging-wall is apparently greater than that of the foot-wall, while the peak velocity fails to observe this rule. Taking account of the seismic intensity distribution of Wenchuan Ms8.0 earthquake, the shape of strong ground motion contours was significantly affected by the directional effect in the regions with Chinese seismic intensity level VI ~ VIII. However, in the regions whose Chinese seismic intensity level are equal or greater than VIII, the mutual positional relationship between the strong ground motion contours and the surface outcrop trace of the fault was evidently influenced by the hanging-wall and foot-wall effect.

Keywords: hanging-wall and foot-wall effect, peak ground acceleration, rupture directivity effect, strong ground motion

Procedia PDF Downloads 350

Authors: K. Eshwara Prasad, R. Raman Goud, Swadesh Kumar Singh, N. Sateesh

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In the present work forming limit diagrams and strain distribution profile diagrams for extra deep drawing steel at room and elevated temperatures have been determined experimentally by conducting stretch forming experiments by using designed and fabricated warm stretchforming tooling setup. With the help of forming Limit Diagrams (FLDs) and strain distribution profile diagrams the formability of Extra Deep Drawing steel has been analyzed and co-related with mechanical properties like strain hardening COEFFICIENT (n) and normal anisotropy (r−).Mechanical properties of EDD steel from room temperature to 4500C were determined and discussed the impact of temperature on the properties like work hardening exponent (n) anisotropy(r-) and strength coefficient of the material. Also the fractured surfaces after stretching have undergone the some metallurgical investigations and attempt has been made to co-relate with the formability of EDD steel sheets. They are co-related and good agreement with FLDs at various temperatures.

Keywords: FLD, microhardness, strain distribution profile, stretch forming

Procedia PDF Downloads 325

Authors: Kateřina Jurdová

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Hanging to the trapezoidal sheet by decking hanger is a very widespread solution used in civil engineering to lead the distribution of energy, sanitary, air distribution system etc. under the roof or floor structure. The trapezoidal decking hanger is usually a part of the whole installation system for specific distribution medium. The leading companies offer installation systems for each specific distribution e.g. pipe rings, sprinkler systems, installation channels etc. Every specific part is connected to the base connector which is decking hanger. The own connection has three main components: decking hanger, threaded bar with nuts and web of trapezoidal sheet. The aim of this contribution is determinate the failure mechanism of each component in connection. Load bearing capacity of most components in connection could be calculated by formulas in European codes. This contribution is focused on problematic of bearing resistance of threaded bar in web of trapezoidal sheet. This issue is studied by experimental research and numerical modelling. This contribution presented the initial results of experiment which is compared with numerical model of specimen.

Keywords: decking hanger, concentrated load, connection, load bearing capacity, trapezoidal metal sheet

Procedia PDF Downloads 392

Authors: Natcha Wattanaprapa, Alongkorn Taengtong, Phachaya Chaiwchan

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This study investigates and promotes the distribution of community enterprise products of Samut Songkhram province by using e-commerce web technology to help distribute the products. This study also aims to develop the information system to be able to operate on multiple platforms and promote the easy usability on smartphones to increase the efficiency and promote the distribution of community enterprise products of Samut Songkhram province in three areas including Baan Saraphi learning center, the learning center of Bang Noi Floating market as well as Bang Nang Li learning center. The main structure consists of spreading the knowledge regarding the tourist attraction in the area of community enterprise, e-commerce system of community enterprise products, and Chatbot. The researcher developed the system into an application form using the software package to create and manage the content on the internet. Connect management system (CMS) word press was used for managing web pages. Add-on CMS word press was used for creating the system of Chatbot, and the database of PHP My Admin was used as the database management system. The evaluation by the experts and users in 5 aspects, including the system efficiency, the accuracy in the operation of the system, the convenience and ease of use of the system, the design, and the promotion of product distribution in Samut Songkhram province by using questionnaires revealed that the result of evaluation in the promotion of product distribution in Samut Songkhram province was the highest with the mean of 4.20. When evaluating the efficiency of the developed system, it was found that the result of system efficiency was the highest level with a mean of 4.10.

Keywords: community enterprise, digital commerce, promotion of product distribution, Samut Songkhram province

Procedia PDF Downloads 148

Authors: Niall J. English

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Under- and post-graduate training can benefit from a more active learning style, and most particularly so in engineering. Despite this, outreach to young children in primary and secondary schools is less-developed in terms of its documented effectiveness, especially given new emphasis placed within the third level and advanced research program’s on Education and Public Engagement (EPE). Bearing this in mind, outreach and school visits form the basis to ascertain how active learning, careers stimulus and EPE initiatives for young children can inform the university sector, helping to improve future engineering-teaching standards, and enhancing both quality and practicalities of the teaching-and-learning experience. Indeed, engineering-education EPE/outreach work has been demonstrated to lead to several tangible benefits and improved outcomes, such as greater engagement and interest with science/engineering for school-children, careers awareness, enabling teachers with strong contributions to technical knowledge of engineering subjects, and providing development of general professional skills for engineering, e.g., communication and teamwork. This intervention involved active learning in ‘buzz’ groups for young children of concepts in gas engineering, observing their peer interactions to develop university-level lessons on activity learning. In addition, at the secondary level, careers-outreach efforts have led to statistical determinations of motivations towards engineering education and training, which aids in the redesign of engineering curricula for more active learning.

Keywords: outreach, education and public engagement, careers, peer interactions

Procedia PDF Downloads 120

Authors: Azam Najafkouchak, David Todem, Dorothy Pathak, Pramod Pathak, Joseph Gardiner

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Propensity score (PS) methods have recently become the standard analysis tool for causal inference in observational studies where exposure is not randomly assigned. Thus, confounding can impact the estimation of treatment effect on the outcome. Due to the dangers of discretizing continuous variables, the focus of this paper will be on how the variation in cut-points or boundaries will affect the average treatment effect utilizing the stratification of the PS method. In this study, we will develop a new methodology to improve the efficiency of the PS analysis through stratification and simulation study. We will also explore the property of empirical distribution of average treatment effect theoretically, including asymptotic distribution, variance estimation and 95% confident Intervals.

Keywords: propensity score, stratification, emprical distribution, average treatment effect

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Authors: Pirom Thangchitpianpol, Suttipong Jumroonrut

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This research investigates the distribution of food demand for animal food and the optimum amount of that food production at minimum cost. The data consist of customer purchase orders for the food of laying hens, price of food for laying hens, cost per unit for the food inventory, cost related to food of laying hens in which the food is out of stock, such as fine, overtime, urgent purchase for material. They were collected from January, 1990 to December, 2013 from a factory in Nakhonratchasima province. The collected data are analyzed in order to explore the distribution of the monthly food demand for the laying hens and to see the rate of inventory per unit. The results are used in a stochastic linear programming model for aggregate planning in which the optimum production or minimum cost could be obtained. Programming algorithms in MATLAB and tools in Linprog software are used to get the solution. The distribution of the food demand for laying hens and the random numbers are used in the model. The study shows that the distribution of monthly food demand for laying has a normal distribution, the monthly average amount (unit: 30 kg) of production from January to December. The minimum total cost average for 12 months is Baht 62,329,181.77. Therefore, the production planning can reduce the cost by 14.64% from real cost.

Keywords: animal food, stochastic linear programming, aggregate planning, production planning, demand uncertainty

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Authors: Akim Borbuev, Francisco de León

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Economic and population growth in densely-populated urban areas introduce major challenges to distribution system operators, planers, and designers. To supply added loads, utilities are frequently forced to invest in new distribution feeders. However, this is becoming increasingly more challenging due to space limitations and rising installation costs in urban settings. This paper proposes the conversion of critical alternating current (ac) distribution feeders into direct current (dc) feeders to increase the power transfer capacity by a factor as high as four. Current trends suggest that the return of dc transmission, distribution, and utilization are inevitable. Since a total system-level transformation to dc operation is not possible in a short period of time due to the needed huge investments and utility unreadiness, this paper recommends that feeders that are expected to exceed their limits in near future are converted to dc. The increase in power transfer capacity is achieved through several key differences between ac and dc power transmission systems. First, it is shown that underground cables can be operated at higher dc voltage than the ac voltage for the same dielectric stress in the insulation. Second, cable sheath losses, due to induced voltages yielding circulation currents, that can be as high as phase conductor losses under ac operation, are not present under dc. Finally, skin and proximity effects in conductors and sheaths do not exist in dc cables. The paper demonstrates that in addition to the increased power transfer capacity utilities substituting ac feeders by dc feeders could benefit from significant lower costs and reduced losses. Installing dc feeders is less expensive than installing new ac feeders even when new trenches are not needed. Case studies using the IEEE 342-Node Low Voltage Networked Test System quantify the technical and economic benefits of dc feeders.

Keywords: DC power systems, distribution feeders, distribution networks, power transfer capacity

Procedia PDF Downloads 128

Authors: Salma Mirza, Syeda Asma Naqvi, Khalid Mohammed Khan, M. Iqbal Choudhary

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In this study twenty-five (25) newly synthesized compounds substituted aryl thiazoles (SAT) 1-25 were synthesized, and in vitro cytotoxicity of these compounds was evaluated against four cancer cell lines namely, MCF-7 (ER+ve breast), MDA-MB-231 (ER-ve breast), HCT116 (colorectal), and, HeLa (cervical) and compared with the standard anticancer drug doxorubicin with IC50 value of 1.56 ± 0.05 μM. Among them, compounds 1, 4-8 and 19 were found to be active against all four cell lines. Compound 20 was found to be selectively active against MCF7 cells with IC50 value of 40.21 ± 4.15 µM, whereas compound 19 was active against only MCF7 and HeLa cells with IC50 values of 46.72 ± 1.8 and 19.86 ± 0.11 μM, respectively. These results suggest that aryl thiazoles 1 and 4 deserve to be investigated further in vivo as anti-cancer agents.

Keywords: anticancer agents, breast cancer cell lines (MCF7, MDA-MB-231), colorectal cancer cell line (HCT-116), cervical cancer cell line (HeLa), Thiazole derivatives

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: R. Marandi, H. Shahrir, T. Nejad Ghaffar Borhani, M. Kamaruddin

Abstract:

In the present study, a steady state population balance model was developed to predict the polymer particle size distribution (PSD) in ethylene gas phase fluidized bed olefin polymerization reactors. The multilayer polymeric flow model (MPFM) was used to calculate the growth rate of a single polymer particle under intra-heat and mass transfer resistance. The industrial plant data were used to calculate the growth rate of polymer particle and the polymer PSD. Numerical simulations carried out to describe the influence of effective monomer diffusion coefficient, polymerization rate and initial catalyst size on the catalyst particle growth and final polymer PSD. The results present that the intra-heat and mass limitation is important for the ethylene polymerization, the growth rate of particle and the polymer PSD in the fluidized bed reactor. The effect of the agglomeration on the PSD is also considered. The result presents that the polymer particle size distribution becomes broader as the agglomeration exits.

Keywords: population balance, olefin polymerization, fluidized bed reactor, particle size distribution, agglomeration

Procedia PDF Downloads 333

Authors: Marwa Sahnoun, Chokri Abdennadher

Abstract:

This article comes, very timely, to look at the effectiveness of active labor market policies (ALMP) in improving labor market outcomes. Using panel data estimates for 19 European countries during the period 2000-2012, this article showed the role of institutional factors, especially the role of employment policies implementation based on three variables: the allocation of resources for the implementation of policies, continuity and timing in the implementation of policies to capture their effectiveness on the labor market. Empirical results shows favor effect of training, employment incentives, sheltered employment and rehabilitation and direct job creation on the entire population employment growth. Results shows also that start-up incentives seems to be more effective in increasing employment than other types of policies. Importantly, two aspects are important in terms of implementation: public expenditure on program administration, e.g. (PES) watches the most favorable aspect and the continuity of policies implemented.

Keywords: active labor market policies, implementation, public expenditure on program administration, start-up incentives, training

Procedia PDF Downloads 399

Authors: Fangwei Zhu, Wei Tian, Linzhuo Wang, Miao Yu

Abstract:

Megaproject has long been a critical issue in project governance, for its low success rate and large impact on society. Although the extant literature on megaproject governance is vast, to our best knowledge, the lacking of a thorough literature review makes it hard for us to gain a holistic view on current scenario of megaproject governance. The study conducts a systematic literature review process to analyze the existing literatures on megaproject governance. The finding indicates that mega project governance needs to be handled at network level and forming a network level governance provides a holistic framework for governing megaproject towards sustainable development of the projects. Theoretical and practical implications, as well as future studies and limitations, were discussed.

Keywords: megaproject, governance, literature review, network

Procedia PDF Downloads 200

Authors: Geminne Manzano, Clairecynth Yu, Lilibeth Salvador-Reyes, Viviene Santiago, Porfirio AliñO

Abstract:

The distribution and abundance patterns of many marine sessile organisms such as sponges vary among and within reefs. Determining the factors affecting its distribution is essential especially for organisms that produce secondary metabolites with pharmaceutical importance. In this study, the small-scale distribution patterns of the Philippine blue sponge, Xestospongia sp. in relation to some ecological factors were examined. The relationship between the renieramycin-M production and their benthic attributes were also determined. Ecological surveys were conducted on two stations with varying depth and exposure located in Oriental Mindoro, Philippines. Three 30 by 6m belt transect were used to assess the sponge abundance at each station. The substratum of the sponges was also characterized. Fish visual census observations were also taken together with the photo transect methods benthic surveys. Sponge samples were also collected for the extraction of Renieramycin-M and for further chemical analysis. Varying distribution patterns were observed to be attributed to the combination of different ecological and environmental factors. The amount of Renieramycin-production also varied in each station. The common substratum for blue sponges includes hard and soft corals, as well as, dead coral with algal patches. Blue sponges from exposed habitat frequently grow associated with massive and branching corals, Porites sp., while the most frequent substrate found on sheltered habitats is the coral Pavona sp. Exploring the influence of ecological and environmental parameters on the abundance and distribution of sponge assemblages provide ecological insights and their potential applications to pharmaceutical studies. The results of this study provide further impetus in pursuing studies into patterns and processes of the Philippine blue sponge, Xestospongia sp. distribution in relation to the chemical ecology of its secondary metabolites.

Keywords: distribution patterns, Porifera, Renieramycin-M, sponge assemblages, Xestospongia sp.

Procedia PDF Downloads 266

Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani Alghamdi

Abstract:

Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: binary segmentation, change point, exponentialLomax distribution, information criterion

Procedia PDF Downloads 175