Search results for: Short Time FourierTransform

Authors: Fuad Alzahrani, Yiannis Kyratsis

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Although emergency nurses, being the frontline workers in mass-gatherings, are essential for providing an effective public health response, little is known about the skills that emergency nurses have, or require, in order to respond effectively to a disaster event. This paper is designed to address this gap in the literature by conducting an empirical study on emergency nurses’ preparedness at the mass-gathering event of Hajj in Mecca city. To achieve this aim, this study conducted a cross-sectional survey among 106 emergency department nurses in all the public hospitals in Mecca in 2014. The results revealed that although emergency nurses’ role understanding is high; they have limited knowledge and awareness of how to respond appropriately to mass-gathering disaster events. To address this knowledge gap, the top three most beneficial types of education and training courses suggested are: hospital education sessions, the Emergency Management Saudi Course and workshop; and short courses in disaster management. Finally, recommendations and constructive strategies are developed to provide the best practice in enhancing disaster preparedness. This paper adds to the body of knowledge regarding emergency nurses and mass gathering disasters. This paper measures the level of disaster knowledge, previous disaster response experience and disaster education and training amongst emergency nurses in Mecca, Saudi Arabia. It is anticipated that this study will provide a foundation for future studies aimed at better preparing emergency nurses for disaster response. This paper employs new strategies to improve the emergency nurses’ response during mass gatherings for the Hajj. Increasing the emergency nurses’ knowledge will develop their effective responses in mass-gathering disasters.

Keywords: Emergency nurses, mass-gatherings, disaster preparedness, perceived role.

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Authors: Ali Abdi Kordani, Meysam Rooyintan, Sid Mohammad Boroomandrad

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Nowadays, one the most important problems in megacities is public transportation and satisfying citizens from this system in order to decrease the traffic congestions and air pollution. Accordingly, to improve the transit passengers and increase the travel safety, new transportation systems such as Bus Rapid Transit (BRT), tram, and monorail have expanded that each one has different merits and demerits. That is why comparing different systems for a systematic selection of public transportation systems in a big city like Tehran, which has numerous problems in terms of traffic and pollution, is essential. In this paper, it is tried to investigate the advantages and feasibility of using monorail, tram and BRT systems, which are widely used in most of megacities in all over the world. In Tehran, by using SPSS statistical analysis software and TOPSIS method, these three modes are compared to each other and their results will be assessed. Experts, who are experienced in the transportation field, answer the prepared matrix questionnaire to select each public transportation mode (tram, monorail, and BRT). The results according to experts’ judgments represent that monorail has the first priority, Tram has the second one, and BRT has the third one according to the considered indices like execution costs, wasting time, depreciation, pollution, operation costs, travel time, passenger satisfaction, benefit to cost ratio and traffic congestion.

Keywords: Bus Rapid Transit, Costs, Monorail, Pollution, Tram.

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Authors: Saleem Z. Ramadan

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This paper discusses the effects of using progressive Type-I right censoring on the design of the Simple Step Accelerated Life testing using Bayesian approach for Weibull life products under the assumption of cumulative exposure model. The optimization criterion used in this paper is to minimize the expected pre-posterior variance of the P^th percentile time of failures. The model variables are the stress changing time and the stress value for the first step. A comparison between the conventional and the progressive Type-I right censoring is provided. The results have shown that the progressive Type-I right censoring reduces the cost of testing on the expense of the test precision when the sample size is small. Moreover, the results have shown that using strong priors or large sample size reduces the sensitivity of the test precision to the censoring proportion. Hence, the progressive Type-I right censoring is recommended in these cases as progressive Type-I right censoring reduces the cost of the test and doesn't affect the precision of the test a lot. Moreover, the results have shown that using direct or indirect priors affects the precision of the test.

Keywords: Reliability, Accelerated life testing, Cumulative exposure model, Bayesian estimation, Progressive Type-I censoring, Weibull distribution.

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Authors: Phool Singh, Ashok Jangid, N. S. Tomer, Deepa Sinha

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The aim of this paper is to investigate twodimensional unsteady flow of a viscous incompressible fluid about stagnation point on permeable stretching sheet in presence of time dependent free stream velocity. Fluid is considered in the influence of transverse magnetic field in the presence of radiation effect. Rosseland approximation is use to model the radiative heat transfer. Using time-dependent stream function, partial differential equations corresponding to the momentum and energy equations are converted into non-linear ordinary differential equations. Numerical solutions of these equations are obtained by using Runge-Kutta Fehlberg method with the help of Newton-Raphson shooting technique. In the present work the effect of unsteadiness parameter, magnetic field parameter, radiation parameter, stretching parameter and the Prandtl number on flow and heat transfer characteristics have been discussed. Skin-friction coefficient and Nusselt number at the sheet are computed and discussed. The results reported in the paper are in good agreement with published work in literature by other researchers.

Keywords: Magneto hydrodynamics, stretching sheet, thermal radiation, unsteady flow.

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled direct normal irradiance field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: Artificial Neural Networks, Resilient Propagation, Solar Radiation, Time Series Forecasting.

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Authors: Nadya Hajar, Zainal, S., Atikah, O., Tengku Elida, T. Z. M.

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Ethanol has been known for a long time, being perhaps the oldest product obtained through traditional biotechnology fermentation. Agriculture waste as substrate in fermentation is vastly discussed as alternative to replace edible food and utilization of organic material. Pineapple peel, highly potential source as substrate is a by-product of the pineapple processing industry. Bio-ethanol from pineapple (Ananas comosus) peel extract was carried out by controlling fermentation without any treatment. Saccharomyces ellipsoides was used as inoculum in this fermentation process as it is naturally found at the pineapple skin. In this study, the capability of Response Surface Methodology (RSM) for optimization of ethanol production from pineapple peel extract using Saccharomyces ellipsoideus in batch fermentation process was investigated. Effect of five test variables in a defined range of inoculum concentration 6- 14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix), temperature (24-32°C) and time of incubation (30-54 hrs) on the ethanol production were evaluated. Data obtained from experiment were analyzed with RSM of MINITAB Software (Version 15) whereby optimum ethanol concentration of 8.637% (v/v) was determined. The optimum condition of 14% (v/v) inoculum concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The significant regression equation or model at the 5% level with correlation value of 99.96% was also obtained.

Keywords: Bio-ethanol, pineapple peel extract, Response Surface Methodology (RSM), Saccharomyces ellipsoideus.

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Authors: Petr Cernohorsky, Jan Voracek

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Well-developed strategic marketing planning is the essential prerequisite for establishment of the right and unique competitive advantage. Typical market, however, is a heterogeneous and decentralized structure with natural involvement of individual or group subjectivity and irrationality. These features cannot be fully expressed with one-shot rigorous formal models based on, e.g. mathematics, statistics or empirical formulas. We present an innovative solution, extending the domain of agent based computational economics towards the concept of hybrid modeling in service provider and consumer market such as telecommunications. The behavior of the market is described by two classes of agents - consumer and service provider agents - whose internal dynamics are fundamentally different. Customers are rather free multi-state structures, adjusting behavior and preferences quickly in accordance with time and changing environment. Producers, on the contrary, are traditionally structured companies with comparable internal processes and specific managerial policies. Their business momentum is higher and immediate reaction possibilities limited. This limitation underlines importance of proper strategic planning as the main process advising managers in time whether to continue with more or less the same business or whether to consider the need for future structural changes that would ensure retention of existing customers or acquisition of new ones.

Keywords: Agent-based computational economics, hybrid modeling, strategic marketing, system dynamics.

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Authors: G.–A. Constantin, G. Voicu, E.–M. Stefan, P. Tudor, G. Paraschiv, M.–G. Munteanu

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In the activity of handling and transport of food products, the products may be subjected to mechanical stresses that may lead to their deterioration by deformation, breaking, or crushing. This is the case for biscuits, regardless of their type (gluten-free or sugary), the addition of ingredients or flour from which they are made. However, gluten-free biscuits have a higher mechanical resistance to breakage or crushing compared to easily shattered sugar biscuits (especially those for children). The paper presents the results of the experimental evaluation of the texture for four varieties of commercial biscuits, using the penetrometer equipped with needle cone at five different additional weights on the cone-rod. The assortments of biscuits tested in the laboratory were Petit Beurre, Picnic, and Maia (all three manufactured by RoStar, Romania) and Sultani diet biscuits, manufactured by Eti Burcak Sultani (Turkey, in packs of 138 g). For the four varieties of biscuits and the five additional weights (50, 77, 100, 150 and 177 g), the experimental data obtained were subjected to regression analysis in the MS Office Excel program, using Velon's relationship (h = a∙ln(t) + b). The regression curves were analysed comparatively in order to identify possible differences and to highlight the variation of the penetration depth h, in relation to the time t. Based on the penetration depth between two-time intervals (every 5 seconds), the curves of variation of the penetration speed in relation to time were then drawn. It was found that Velon's law verifies the experimental data for all assortments of biscuits and for all five additional weights. The correlation coefficient R2 had in most of the analysed cases values over 0.850. The values recorded for the penetration depth were framed, in general, within 45-55 p.u. (penetrometric units) at an additional mass of 50 g, respectively between 155-168 p.u., at an additional mass of 177 g, at Petit Beurre biscuits. For Sultani diet biscuits, the values of the penetration depth were within the limits of 32-35 p.u., at an additional weight of 50 g and between 80-114 p.u., at an additional weight of 177g. The data presented in the paper can be used by both operators on the manufacturing technology flow, as well as by the traders of these food products, in order to establish the most efficient parametric of the working regimes (when packaging and handling).

Keywords: Biscuits resistance/texture, penetration depth, penetration velocity, sharp pin penetrometer.

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Authors: A. Rezazadeh, N. Omidvar, H. Eini-Zinab

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Food insecurity (FI) influences may result in poor physical and mental health outcomes. Minor ethnic group may experience higher level of FI, and this situation may be related with higher depression prevalence. The aim of this study was to determine the association of depression with food security status in major (Azeri) and minor (Kurdish) ethnicity living in Urmia, West Azerbaijan, north of Iran. In this cross-sectional study, 723 participants (427 women and 296 men) aged 20–64 years old, from two ethnic groups (445 Azeri and 278 Kurdish), were selected through a multi stage cluster systematic sampling. Depression rate was assessed by “Beck” short form questionnaire (validated in Iranians) through interviews. Household FI status (HFIS) was measured using adapted HFI access scale through face-to-face interviews at homes. Multinomial logistic regression was used to estimate odds ratios (OR) of depression across HFIS. Higher percent of Kurds had moderate and severe depression in comparison with Azeri group (73 [17.3%] vs. 86 [27.9%]). There were not any significant differences between the two ethnicities in mild depression. Also, of all the subjects, moderate-to-sever FI was more prevalent in Kurds (28.5%), compared to Azeri group (17.3%) [P < 0.01]. Kurdish ethnic group living in food security or mild FI households had lower chance to have symptom of severe depression in comparison to those with sever FI (OR=0.097; 95% CI: 0.02-0.47). However, there was no significant association between depression and HFI in Azeri group. Findings revealed that the severity of HFI was related with severity depression in minor studied ethnic groups. However, in Azeri ethnicity as a major group, other confounders may have influence on the relation with depression and FI, that were not studied in the present study.

Keywords: Depression, ethnicity, food security status, Iran.

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Authors: Mona Soliman Habib

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This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: I. Badhrees

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This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of Laser in the Liquid Argon Time Projection Chamber.

The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT_(e) > 20GeV, and η_(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432pb.

The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σ_e = 1.24±0.10stat±0.30sys.10 -56cm⁴.

Keywords: ATLAS, CERN, KACST, LArTPC, Particle Physics.

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Authors: Chan Eang Teng, Tang Mui Joo

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With the viral factor on social media, the sense of persuasion is generated by repetition and popularity. When users’ interest is captured, political awareness increases to spark political enthusiasm, but, the level of user’s political participation and political attitude of those active users is still questionable. An online survey on 250 youth and in-depth interview on two politicians are conducted to answer the main question in this paper. The result shows that Facebook significantly increases political awareness among youths. Social media may not be the major trigger to political activism among youths as most respondents opined that they would still vote without Facebook. Other factors could be political campaigning, political climate, age, peer pressure or others. Finding also shows that majority of respondents did not participate in online political debates or political groups. Many also wondered if the social media was the main power switch that triggers the political influx among young voters. The research finding is significant to understand how the new media, Facebook, has reshaped the political landscape in Malaysia, creating the Social Media Election that changed the rules of the political game. However, research finding does not support the ideal notion that the social media is the major trigger to youth’s political activism. This research outcome has exposed the flaws of the Social Media Election. It has revealed the less optimistic side of youth political activism. Unfortunately, results fall short of the idealistic belief that the social media have given rise to political activism among youths in the 13^th General Election in Malaysia. The research outcome also highlights an important lesson for the democratic discourse of Malaysia which is making informed and educated decisions takes more commitment, proactive and objective attitude.

Keywords: Social media, political participation, political activism, democracy, political communication.

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Authors: Jehad Al Dallal

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Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. In this paper, algorithms are introduced to compute all backward and forward static slices of a computer program by traversing the program representation graph once. The program representation graph used in this paper is called Program Dependence Graph (PDG). We have conducted an experimental comparison study using 25 software modules to show the effectiveness of the introduced algorithm for computing all backward static slices over single-point slicing approaches in computing the parallelism and functional cohesion of program modules. The effectiveness of the algorithm is measured in terms of time execution and number of traversed PDG edges. The comparison study results indicate that using the introduced algorithm considerably saves the slicing time and effort required to measure module parallelism and functional cohesion.

Keywords: Backward slicing, cohesion measure, forward slicing, parallelism measure, program dependence graph, program slicing, static slicing.

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Authors: Peng Shen Ong, Yoong Choon Chang, Chee Pun Ooi, Ettikan K. Karuppiah, Shahirina Mohd Tahir

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Falling has been one of the major concerns and threats to the independence of the elderly in their daily lives. With the worldwide significant growth of the aging population, it is essential to have a promising solution of fall detection which is able to operate at high accuracy in real-time and supports large scale implementation using multiple cameras. Field Programmable Gate Array (FPGA) is a highly promising tool to be used as a hardware accelerator in many emerging embedded vision based system. Thus, it is the main objective of this paper to present an FPGA-based solution of visual based fall detection to meet stringent real-time requirements with high accuracy. The hardware architecture of visual based fall detection which utilizes the pixel locality to reduce memory accesses is proposed. By exploiting the parallel and pipeline architecture of FPGA, our hardware implementation of visual based fall detection using FGPA is able to achieve a performance of 60fps for a series of video analytical functions at VGA resolutions (640x480). The results of this work show that FPGA has great potentials and impacts in enabling large scale vision system in the future healthcare industry due to its flexibility and scalability.

Keywords: Fall detection, FPGA, hardware implementation.

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Authors: Elena B. Cherepetskaya, Alexander A. Karabutov, Natalia B. Podymova, Ivan Sas

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Nonlinear evolution of broadband ultrasonic pulses passed through the rock specimens is studied using the apparatus “GEOSCAN-02M”. Ultrasonic pulses are excited by the pulses of Qswitched Nd:YAG laser with the time duration of 10 ns and with the energy of 260 mJ. This energy can be reduced to 20 mJ by some light filters. The laser beam radius did not exceed 5 mm. As a result of the absorption of the laser pulse in the special material – the optoacoustic generator–the pulses of longitudinal ultrasonic waves are excited with the time duration of 100 ns and with the maximum pressure amplitude of 10 MPa. The immersion technique is used to measure the parameters of these ultrasonic pulses passed through a specimen, the immersion liquid is distilled water. The reference pulse passed through the cell with water has the compression and the rarefaction phases. The amplitude of the rarefaction phase is five times lower than that of the compression phase. The spectral range of the reference pulse reaches 10 MHz. The cubic-shaped specimens of the Karelian gabbro are studied with the rib length 3 cm. The ultimate strength of the specimens by the uniaxial compression is (300±10) MPa. As the reference pulse passes through the area of the specimen without cracks the compression phase decreases and the rarefaction one increases due to diffraction and scattering of ultrasound, so the ratio of these phases becomes 2.3:1. After preloading some horizontal cracks appear in the specimens. Their location is found by one-sided scanning of the specimen using the backward mode detection of the ultrasonic pulses reflected from the structure defects. Using the computer processing of these signals the images are obtained of the cross-sections of the specimens with cracks. By the increase of the reference pulse amplitude from 0.1 MPa to 5 MPa the nonlinear transformation of the ultrasonic pulse passed through the specimen with horizontal cracks results in the decrease by 2.5 times of the amplitude of the rarefaction phase and in the increase of its duration by 2.1 times. By the increase of the reference pulse amplitude from 5 MPa to 10 MPa the time splitting of the phases is observed for the bipolar pulse passed through the specimen. The compression and rarefaction phases propagate with different velocities. These features of the powerful broadband ultrasonic pulses passed through the rock specimens can be described by the hysteresis model of Preisach- Mayergoyz and can be used for the location of cracks in the optically opaque materials.

Keywords: Cracks, geological materials, nonlinear evolution of ultrasonic pulses, rock.

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Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

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Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: Fire detector, rack, response characteristic, warehouse.

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Authors: Dana M. Ragab, Jasim A. Ghaeb

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The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: Three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality.

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: Autonomous vehicle, data recording, remote monitoring, controller area network.

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: Wavelet transform, computational error, computational duration, strong ground motion data.

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: Direct search, DFIG, equivalent circuit parameters, optimization.

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Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: Building envelope, machine learning, perforated metal, multi-factor optimization, façade.

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Authors: Bikramaditya Das, Susmita Das

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Study on suppression of interference in time domain equalizers is attempted for high data rate impulse radio (IR) ultra wideband communication system. The narrow band systems may cause interference with UWB devices as it is having very low transmission power and the large bandwidth. SRAKE receiver improves system performance by equalizing signals from different paths. This enables the use of SRAKE receiver techniques in IRUWB systems. But Rake receiver alone fails to suppress narrowband interference (NBI). A hybrid SRake-MMSE time domain equalizer is proposed to overcome this by taking into account both the effect of the number of rake fingers and equalizer taps. It also combats intersymbol interference. A semi analytical approach and Monte-Carlo simulation are used to investigate the BER performance of SRAKEMMSE receiver on IEEE 802.15.3a UWB channel models. Study on non-line of sight indoor channel models (both CM3 and CM4) illustrates that bit error rate performance of SRake-MMSE receiver with NBI performs better than that of Rake receiver without NBI. We show that for a MMSE equalizer operating at high SNR-s the number of equalizer taps plays a more significant role in suppressing interference.

Keywords: IR-UWB, UWB, IEEE 802.15.3a, NBI, data rate, bit error rate.

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Authors: Kiomars Sefidi

Abstract:

Dead wood and habitat tree such as fallen logs, snags, stumps and cracks and loos bark etc. are regarded as an important ecological component of forests on which many forest dwelling species depend on presence of them within forest ecosystems. Meanwhile its relation to management history in Caspian forest has gone unreported. The aim of research was to compare the amounts of dead wood and habitat trees in the forests with historically different intensities of management, including: forests with the long term implication of management (PS), the short term implication of management (NS) which were compared with semi virgin forest (GS). The number of 405 individual dead and habitat trees were recorded and measured at 109 sampling locations. ANOVA revealed volume of dead tree in the form and decay classes significantly differ within sites and dead volume in the semi virgin forest significantly higher than managed sites. Comparing the amount of dead and habitat tree in three sites showed that, dead tree volume related with management history and significantly differ in three study sites. Meanwhile, frequency of habitat trees was significantly different within sites. The highest amount of habitat trees including cavities, cracks and loose bark and fork split trees was recorded in virgin site and lowest recorded in the sites with the long term implication of management. It can be concluded that forest management cause reduction of the amount of dead and habitat tree specially in a large size, thus managing this forest according to ecological sustainable principles require a commitment to maintaining stand structure that allow, continued generation of dead trees in a full range of size.

Keywords: Cracks trees, forest biodiversity, fork split trees, nature conservation, sustainable management.

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Authors: Batin Latif Aylak, Bernd Noche

Abstract:

Overhead conveyor systems are in use in many installations around the world, meeting the widest range of applications possible. Overhead conveyor systems are particularly preferred in automotive industry but also at post offices. Overhead conveyor systems must always be integrated with a logistical process by finding the best way for a cheaper material flow in order to guarantee precise and fast workflows. With their help, any transport can take place without wasting ground and space, without excessive company capacity, lost or damaged products, erroneous delivery, endless travels and without wasting time. Ultra-light overhead conveyor systems are rope-based conveying systems with individually driven vehicles. The vehicles can move automatically on the rope and this can be realized by energy and signals. Crossings are realized by switches. Ultra-light overhead conveyor systems provide optimal material flow, which produces profit and saves time. This article introduces two new ultra-light overhead conveyor designs in logistics and explains their components. According to the explanation of the components, scenarios are created by means of their technical characteristics. The scenarios are visualized with the help of CAD software. After that, assumptions are made for application area. According to these assumptions scenarios are visualized. These scenarios help logistics companies achieve lower development costs as well as quicker market maturity.

Keywords: Logistics, material flow, overhead conveyor.

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Authors: Samuel A. Phillips, Emmanuel A. Ayanlowo, Rasaki O. Olanrewaju, Olayode Fatoki

Abstract:

This paper employs the Jeffrey's prior technique in the process of estimating the periodograms and frequency of sinusoidal model for unknown noisy time variants or oscillating events (data) in a Bayesian setting. The non-informative Jeffrey's prior was adopted for the posterior trigonometric function of the sinusoidal model such that Cramer-Rao Lower Bound (CRLB) inference was used in carving-out the minimum variance needed to curb the invariance structure effect for unknown noisy time observational and repeated circular patterns. An average monthly oscillating temperature series measured in degree Celsius (0C) from 1901 to 2014 was subjected to the posterior solution of the unknown noisy events of the sinusoidal model via Markov Chain Monte Carlo (MCMC). It was not only deduced that two minutes period is required before completing a cycle of changing temperature from one particular degree Celsius to another but also that the sinusoidal model via the CRLB-Jeffrey's prior for unknown noisy events produced a miniature posterior Maximum A Posteriori (MAP) compare to a known noisy events.

Keywords: Cramer-Rao Lower Bound (CRLB), Jeffrey's prior, Sinusoidal, Maximum A Posteriori (MAP), Markov Chain Monte Carlo (MCMC), Periodograms.

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Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

Abstract:

One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: Malware detection, network security, targeted attack.

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Authors: Regius Asiimwe, Amir Anvar

Abstract:

This paper describes the process used in the automation of the Maritime UAV commands using the Kinect sensor. The AR Drone is a Quadrocopter manufactured by Parrot [1] to be controlled using the Apple operating systems such as iPhones and Ipads. However, this project uses the Microsoft Kinect SDK and Microsoft Visual Studio C# (C sharp) software, which are compatible with Windows Operating System for the automation of the navigation and control of the AR drone. The navigation and control software for the Quadrocopter runs on a windows 7 computer. The project is divided into two sections; the Quadrocopter control system and the Kinect sensor control system. The Kinect sensor is connected to the computer using a USB cable from which commands can be sent to and from the Kinect sensors. The AR drone has Wi-Fi capabilities from which it can be connected to the computer to enable transfer of commands to and from the Quadrocopter. The project was implemented in C#, a programming language that is commonly used in the automation systems. The language was chosen because there are more libraries already established in C# for both the AR drone and the Kinect sensor. The study will contribute toward research in automation of systems using the Quadrocopter and the Kinect sensor for navigation involving a human operator in the loop. The prototype created has numerous applications among which include the inspection of vessels such as ship, airplanes and areas that are not accessible by human operators.

Keywords: UAV, AR drone, Kinect Sensors, Automation, Real time, C sharp, Microsoft Kinect SDK.

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Authors: Md. Royhanur Islam, Thomas Cansse, Md. Sahidul Islam, Atiqur Rahman Sunny

Abstract:

The geographical location of Bangladesh makes it one of the most vulnerable countries to climate change. Climate-induced phenomena mainly affect the south-central region of Bangladesh (Laxmipur district) where they have begun to occur more frequently. The aim of the study was to identify the hydro-climatic factors that lead to weather-related disasters in the coastal areas and analyse the consequences of these factors on coastal livelihoods, with possible adaptation options using participatory rural appraisal (PRA) tools. The present study showed several disasters such as land erosion, depressions and cyclones, coastal flooding, storm surge, and precipitation. The frequency of these disasters is of a noticeable rate. Surveys have also discovered that land erosion is ongoing. Tidal water is being introduced directly into the mainland, and as a result of the salt intrusion, production capacity is declining. The coastal belt is an important area for fishing activities, but due to changed fishing times and a lack of Alternative Income Generating Activities (AIGAs), people have been forced to search for alternative livelihood options by taking both short-term and long-term adaptation options. Therefore, in order to increase awareness and minimize the losses, vulnerable communities must be fully incorporated into disaster response strategies. The government as well as national and international donor organizations should come forward and resolve the present situation of these vulnerable groups since otherwise, they will have to endure endless and miserable suffering due to the effects of climate change ahead in their lives.

Keywords: Adaptation, community, fishery development, livelihood.

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Authors: H. Taheri Shahraiyni, B. Ataie Ashtiani

Abstract:

Flow movement in unsaturated soil can be expressed by a partial differential equation, named Richards equation. The objective of this study is the finding of an appropriate implicit numerical solution for head based Richards equation. Some of the well known finite difference schemes (fully implicit, Crank Nicolson and Runge-Kutta) have been utilized in this study. In addition, the effects of different approximations of moisture capacity function, convergence criteria and time stepping methods were evaluated. Two different infiltration problems were solved to investigate the performance of different schemes. These problems include of vertical water flow in a wet and very dry soils. The numerical solutions of two problems were compared using four evaluation criteria and the results of comparisons showed that fully implicit scheme is better than the other schemes. In addition, utilizing of standard chord slope method for approximation of moisture capacity function, automatic time stepping method and difference between two successive iterations as convergence criterion in the fully implicit scheme can lead to better and more reliable results for simulation of fluid movement in different unsaturated soils.

Keywords: Finite Difference methods, Richards equation, fullyimplicit, Crank-Nicolson, Runge-Kutta.

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Authors: Kai Qian, Ming Yang, Minzhe Guo, Prabir Bhattacharya, Lixin Tao

Abstract:

Computer network courses are essential parts of college computer science curriculum and hands-on networking experience is well recognized as an effective approach to help students understand better about the network concepts, the layered architecture of network protocols, and the dynamics of the networks. However, existing networking labs are usually server-based and relatively cumbersome, which require a certain level of specialty and resource to set up and maintain the lab environment. Many universities/colleges lack the resources and build-ups in this field and have difficulty to provide students with hands-on practice labs. A new affordable and easily-adoptable approach to networking labs is desirable to enhance network teaching and learning. In addition, current network labs are short on providing hands-on practice for modern wireless and mobile network learning. With the prevalence of smart mobile devices, wireless and mobile network are permeating into various aspects of our information society. The emerging and modern mobile technology provides computer science students with more authentic learning experience opportunities especially in network learning. A mobile device based hands-on labware can provide an excellent ‘real world’ authentic learning environment for computer network especially for wireless network study. In this paper, we present our mobile device-based hands-on labware (series of lab module) for computer network learning which is guided by authentic learning principles to immerse students in a real world relevant learning environment. We have been using this labware in teaching computer network, mobile security, and wireless network classes. The student feedback shows that students can learn more when they have hands-on authentic learning experience. 

Keywords: Mobile computing, android, network, labware.

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