Search results for: real time digital simulator

Authors: Su Yin Chiam, Zhipeng Ding, Guang Yang, Danny Jian Hang Tng, Peiyi Song, Geok Ing Ng, Ken-Tye Yong, Qing Xin Zhang

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Brain-machine interfaces (BMI) is a ground rich of exploration opportunities where manipulation of neural activity are used for interconnect with myriad form of external devices. These research and intensive development were evolved into various areas from medical field, gaming and entertainment industry till safety and security field. The technology were extended for neurological disorders therapy such as obsessive compulsive disorder and Parkinson’s disease by introducing current pulses to specific region of the brain. Nonetheless, the work to develop a real-time observing, recording and altering of neural signal brain-machine interfaces system will require a significant amount of effort to overcome the obstacles in improving this system without delay in response. To date, feature size of interface devices and the density of the electrode population remain as a limitation in achieving seamless performance on BMI. Currently, the size of the BMI devices is ranging from 10 to 100 microns in terms of electrodes’ diameters. Henceforth, to accommodate the single cell level precise monitoring, smaller and denser Nano-scaled nanowire electrode arrays are vital in fabrication. In this paper, we would like to showcase the fabrication of high aspect ratio of vertical silicon nanowire electrodes arrays using microelectromechanical system (MEMS) method. Nanofabrication of the nanowire electrodes involves in deep reactive ion etching, thermal oxide thinning, electron-beam lithography patterning, sputtering of metal targets and bottom anti-reflection coating (BARC) etch. Metallization on the nanowire electrode tip is a prominent process to optimize the nanowire electrical conductivity and this step remains a challenge during fabrication. Metal electrodes were lithographically defined and yet these metal contacts outline a size scale that is larger than nanometer-scale building blocks hence further limiting potential advantages. Therefore, we present an integrated contact solution that overcomes this size constraint through self-aligned Nickel silicidation process on the tip of vertical silicon nanowire electrodes. A 4 x 4 array of vertical silicon nanowires electrodes with the diameter of 290nm and height of 3µm has been successfully fabricated.

Keywords: brain-machine interfaces, microelectromechanical systems (MEMS), nanowire, nickel silicide

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Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence

Procedia PDF Downloads 139

Authors: Richard Patrick Kabuye

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This study focuses on the addressing the enhancement of in-service training programs as a tool of transforming the existing traditional approaches of formal lectures/contact hours. This will be supported with a more versatile, robust, and remotely accessible means of mobile based e-learning, as a support tool for the traditional means. A combination of various factors in education and incorporation of the eLearning strategy proves to be a key factor in effective in-service education. Key factor needs to be factored in so as to maintain a credible co-existence of the programs, with the prevailing social, economic and political environments. Effective in-service education focuses on having immediate transformation of knowledge into practice for a good time period, active participation of attendees, enable before training planning, in training assessment and post training feedback training analysis which will yield knowledge to the trainers of the applicability of knowledge given out. All the above require a more robust approach to attain success in implementation. Incorporating mobile technology in eLearning will enable the above to be factored together in a more coherent manner, as it is evident that participants have to take time off their duties and attend to these training programs. Making it mobile, will save a lot of time since participants would be in position to follow certain modules while away from lecture rooms, get continuous program updates after completing the program, send feedback to instructors on knowledge gaps, and a wholly conclusive evaluation of the entire program on a learn as you work platform. This study will follow both qualitative and quantitative approaches in data collection, and this will be compounded incorporating a mobile eLearning application using Android.

Keywords: in service, training, mobile, e- learning, model

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Authors: Necira Okba, Nesrine Bouzaher

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The financial aspect of the Algerian economy is part of all sectors that have undergone great changes these two last decades; the goal is to enable economic mechanisms for real growth. Insurance is an indispensable tool for stabilizing these mechanisms. Therefore, the national economy needs to develop the insurance market in order to support the investments, externally and intern ally; it turns out that reinsurance is one of the area which could prove their performance in several markets mainly emerging ones. The expansion of reinsurance in the domestic market is the preoccupation of this work, focusing on factors that could enhance the demand of reinsurance in the Algerian market. This work will be based on an analytical research of the economic contribution of the reinsurance and it’s collusion with insurance market, then it will be necessary to provide an overview of the product in the national emerging market, finally we will try to investigate on the factors that could enhance the demand in the national reinsurance market so as to determine the potential of Algeria in this area.

Keywords: Algerian reinsurance data, demand trend of Algerian reinsurance, reinsurance, reinsurance market

Procedia PDF Downloads 335

Authors: Oke Oktavianty, Tadayuki Kyoutani, Shigeyuki Haruyama, Junji Kaneko, Ken Kaminishi

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Modelica has many advantages and it is very useful in modeling and simulation especially for the multi-domain with a complex technical system. However, the big obstacle for a beginner is to understand the basic concept and to build a new system model for a real system. In order to understand how to solve the simple circuit model by hand translation and to get a better understanding of how modelica works, we provide a detailed explanation about solver ordering system in horizontal and vertical sorting and make some proposals for improvement. In this study, some difficulties in using modelica software with the original concept and the comparison with Finite Element Method (FEM) approach is discussed. We also present our textual modeling approach using FEM concept for acausal and causal model construction. Furthermore, simulation results are provided that demonstrate the comparison between using textual modeling with original coding in modelica and FEM concept.

Keywords: FEM, a causal model, modelica, horizontal and vertical sorting

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Authors: Tiao Chang, Ivan Caballero, Hong Zhou

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Streams carry water and sediment naturally by maintaining channel dimensions, pattern, and profile over time. Watershed erosion as a natural process has occurred to contribute sediment to streams over time. The formation of channel dimensions is complex. This study is to relate quantifiable and consistent channel dimensions at the bankfull stage to the corresponding watershed erosion estimation by the Revised Universal Soil Loss Equation (RUSLE). Twelve sites of which drainage areas range from 7 to 100 square miles in the Hocking River Basin of Ohio were selected for the bankfull geometry determinations including width, depth, cross-section area, bed slope, and drainage area. The twelve sub-watersheds were chosen to obtain a good overall representation of the Hocking River Basin. It is of interest to determine how these bankfull channel dimensions are related to the soil erosion of corresponding sub-watersheds. Soil erosion is a natural process that has occurred in a watershed over time. The RUSLE was applied to estimate erosions of the twelve selected sub-watersheds where the bankfull geometry measurements were conducted. These quantified erosions of sub-watersheds are used to investigate correlations with bankfull channel dimensions including discharge, channel width, channel depth, cross-sectional area, and pebble distribution. It is found that drainage area, bankfull discharge and cross-sectional area correlates strongly with watershed erosion well. Furthermore, bankfull width and depth are moderately correlated with watershed erosion while the particle size, D50, of channel bed sediment is not well correlated with watershed erosion.

Keywords: watershed, stream, sediment, channel

Procedia PDF Downloads 283

Authors: Hind Alshoubaki

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The world is now confronting a widespread urban phenomenon: refugee camps, which have mostly been established in ‘rushing mode,’ pointing toward affording temporary settlements for refugees that provide them with minimum levels of safety, security and protection from harsh weather conditions within a very short time period. In fact, those emergency settlements are transforming into permanent ones since time is a decisive factor in terms of construction and camps’ age. These play an essential role in transforming their temporary character into a permanent one that generates deep modifications to the city’s territorial structure, shaping a new identity and creating a contentious change in the city’s form and history. To achieve a better understanding for the transformation of refugee camps, this study is based on a mixed-methods approach: the qualitative approach explores different refugee camps and analyzes their transformation process in terms of population density and the changes to the city’s territorial structure and urban features. The quantitative approach employs a statistical regression analysis as a reliable prediction of refugees’ satisfaction within the Zaatari camp in order to predict its future transformation. Obviously, refugees’ perceptions of their current conditions will affect their satisfaction, which plays an essential role in transforming emergency settlements into permanent cities over time. The test basically discusses five main themes: the access and readiness of schools, the dispersion of clinics and shopping centers; the camp infrastructure, the construction materials, and the street networks. The statistical analysis showed that Syrian refugees were not satisfied with their current conditions inside the Zaatari refugee camp and that they had started implementing changes according to their needs, desires, and aspirations because they are conscious about the fact of their prolonged stay in this settlement. Also, the case study analyses showed that neglecting the fact that construction takes time leads settlements being created with below-minimum standards that are deteriorating and creating ‘slums,’ which lead to increased crime rates, suicide, drug use and diseases and deeply affect cities’ urban tissues. For this reason, recognizing the ‘temporary-eternal’ character of those settlements is the fundamental concept to consider refugee camps from the beginning as definite permanent cities. This is the key factor to minimize the trauma of displacement on both refugees and the hosting countries. Since providing emergency settlements within a short time period does not mean using temporary materials, having a provisional character or creating ‘makeshift cities.’

Keywords: refugee, refugee camp, temporary, Zaatari

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Authors: Hamouda M. Mousa, M. Obaid, Chan Hee Park, Cheol Sang Kim

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The rate of copper cementation on iron rod was investigated. The study was mainly dedicated to illustrate the effect of application of electromagnetic field (EMF) on the rate of cementation. The magnetic flux was placed parallel to the iron rod and different magnetic field strength was studied. The results showed that without EMF, the rate of mass transfer was correlated by the equation: Sh= 1.36 Re0. 098 Sc0.33. The application of EMF enhanced the time required to reach high percentage copper cementation by 50%. The rate of mass transfer was correlated by the equation: Sh= 2.29 Re0. 95 Sc0.33, with applying EMF. This work illustrates that the enhancement of copper recovery in presence of EMF is due to the induced motion of Fe+n in the solution which is limited in the range of rod rotation speed of 300~900 rpm. The calculation of power consumption of EMF showed that although the application of EMF partially reduced the cementation time, the reduction of power consumption due to utilization of magnetic field is comparable to the increase in power consumed by introducing magnetic field of 2462 A T/m.

Keywords: copper cementation, electromagnetic field, copper ions, iron cylinder

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: M. R. Aher, R. B. Laware, G. S. Asane, B. S. Kuchekar

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Objective: Studies have shown that a new combination therapy with Artemisinin derivatives and curcumin is unique, with potential advantages over known ACTs. In present study an attempt was made to prepare microparticulate drug delivery system of Curcumin-Zn complex and evaluate it in combination with artemether for antimalarial activity. Material and method: Curcumin Zn complex was prepared and encapsulated using sodium alginate. Microparticles thus obtained are further coated with various enteric polymers at different coating thickness to control the release. Microparticles are evaluated for encapsulation efficiency, drug loading and in vitro drug release. Roentgenographic Studies was conducted in rabbits with BaSO 4 tagged formulation. Optimized formulation was screened for antimalarial activity using P. berghei-infected mice survival test and % paracetemia inhibition, alone (three oral dose of 5mg/day) and in combination with arthemether (i.p. 500, 1000 and 1500µg). Curcumin-Zn(II) was estimated in serum after oral administration to rats by using spectroflurometry. Result: Microparticles coated with Cellulose acetate phthalate showed most satisfactory and controlled release with 479 min time for 60% drug release. X-ray images taken at different time intervals confirmed the retention of formulation in GI tract. Estimation of curcumin in serum by spectroflurometry showed that drug concentration is maintained in the blood for longer time with tmax of 6 hours. The survival time (40 days post treatment) of mice infected with P. berghei was compared to survival after treatment with either Curcumin-Zn(II) microparticles artemether combination, curcumin-Zn complex and artemether. Oral administration of Curcumin-Zn(II)-artemether prolonged the survival of P.berghei-infected mice. All the mice treated with Curcumin-Zn(II) microparticles (5mg/day) artemether (1000µg) survived for more than 40 days and recovered with no detectable parasitemia. Administration of Curcumin-Zn(II) artemether combination reduced the parasitemia in mice by more than 90% compared to that in control mice for the first 3 days after treatment. Conclusion: Antimalarial activity of the curcumin Zn-artemether combination was more pronounced than mono therapy. A single dose of 1000µg of artemether in curcumin-Zn combination gives complete protection in P. berghei-infected mice. This may reduce the chances of drug resistance in malaria management.

Keywords: formulation, microparticulate drug delivery, antimalarial, pharmaceutics

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Authors: Devendra Gupta, Vikash Arya, Prabhat K. Singh

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Background: Ultrasound guidance could be beneficial in placing central venous catheters by improving the success rate, reducing the number of needle passes, and decreasing complications. Central venous cannulation set has a single puncture needle of a fixed length of 6.4 cm. However, the average distance of midpoint of IJV to the skin is around 1 cm to 2 cm. The long length needle has tendency to go in depth more than required and this is very common during learning period of any individual. Therefore, we devised a long needle with a guard which can be adjusted according to the required length. Methods: After approval from the institute ethics committee and patient’s written informed consent, a prospective, randomized, single-blinded controlled study was conducted. Adult patient aged of both sexes with ASA grade 1-2 undergoing surgery requiring internal jugular venous (IJV) access was included. After intubation, the head was rotated to the contralateral side at 30 degree head rotation on the position of the right IJV. The transducer probe a 6.5 to 13-MHz linear transducer (Sonosite, USA) had been placed at the apex of triangle with minimal pressure to avoid IJV compression. The distance from skin to midpoint of the right IJV and skin to anterior wall of Common Carotid Artery (CCA) had been done using B-mode duplex sonography with a 6.5 to 13-MHz linear transducer. Depending upon the results of randomization 420 patients had been divided into two groups of equal numbers (n=210). Group 1. USG guided right sided IJV cannulation was done with conventional (6.4 cm) needle; and Group 2. USG guided right sided IJV cannulation was done with conventional (6.4 cm) needle with guard fixed to a required length (length between skin and midpoint of IJV) by an experienced anesthesiologist. Independent observer has noted the number of attempts and occurrence of complications (CCA puncture, pneumothorax or adjacent tissue damage). Results: Demographic data were similar in both the group. The groups were comparable when considered for relationship of IJV to CCA. There was no significant difference between groups as regard to distance of midpoint of IJV to the skin (p<0.05). IJV cannulation was successfully done in single attempts in 180 (85.7%), in two attempts in 27 (12.9%) and three attempts in 3 (1.4%) in group I, whereas in single attempt in 207 (98.6%) and second attempts in 3 (1.4%) in group II (p <0.000). Incidence of carotid artery puncture was significantly more in group I (7.1%) compared to group II (0%) (p<0.000). Incidence of adjacent tissue puncture was significantly more in group I (8.6%) compared to group II (0%) (p<0.000). Conclusion: Therefore IJV catheterization using guard over the needle at predefined length with the help of real-time ultrasound results in better success rates and lower immediate complications.

Keywords: ultrasound guided, internal jugular vein cannulation, measured guided needle, common carotid artery puncture

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Authors: Aydan Atalar, Nurcan Cetinkaya

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Corn stover is leftover of the leaves, stalk, husks and tassels in the field after harvesting the grain combined. Corn stover is a low-quality roughage but has mostly been used as roughage source for feeding ruminant animals in developing countries including Turkey; however, it can also be used to make biofuels as in developed countries. The objectives of the present study were to improve the digestibility of corn stover by the treatment of white rod fungus mainly Pleurotus osteritus (PO), Pleurotus eryingii (PE) and Lantinula edudes (LE) at different incubation times and also to determine the most effective fungus and incubation time to prepare fermeted corn stover for ruminant nutrition. The choped corn stover was treated with PO, PE and LE and incubated for 10, 20, 30 and 40 days in incubator at 26 0C. After each incubation time dry matter(DM), organic matter(OM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), neutral detergent lignin (ADL), in-vitro true dry matter digestibility (IVTDMD) and organic matter digestibility (IVTOMD) were determined. The mean IVTDMD and IVTOMD levels were increased by PO, PE and LE treatments in increasing order of incubation times. The obtained IVTDM values were 59.45, 60.51, 60.82 and 60.18 %; 59.45, 70.55, 67.18 and 66.96 %; 59.45, 70.55, 67.18 and 66,96 %; 59.45, 74.90, 69.18 % ; 59.45, 76.50, 71.24 and 73.04 for control, PO, PE and LE treatments at 0, 10, 20, 30 and 40 days incubation times respectively. The obtained IVTOMD values were 56.45,60.26,60.82and 60.18 %; 56.45, 68.70, 67.18 and 66.96 %; 56.45, 71.26, 69.18 and 69.28 %; 56.45, 73.23, 71.24 and 73.04 % for control, PO, PE and LE treatments at 0, 10, 20, 30 and 40 days incubation times respectively. The most effective fungus was PO and the incubation time was 30 days. In conclusion, PO treatment of corn stover with 30 days incubation may be used to prepare fermented corn stover for ruminant nutrition.

Keywords: biological treatment, corn stover, digestibility, Lantinula edudes, Pleurotus eryingii, Pleurotus osteritus

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Authors: Andreas Savvides, Chloe Kadi

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The objective of this study is to investigate how the planning and design of open parks within neighborhoods and communities can promote physical activity in order to enhance the health of the local population. An extensive literature review was conducted for studies regarding the relationship between health and physical activity and the park characteristics that can promote physical activity among people. The findings of the literature review were then compared and analysed, in order to identify the main characteristics of urban parks that can promote physical activity and enhance public health. In order to find out how the characteristics identified in the literature were applied in real life, an analysis of three existing parks in three different countries was conducted. The parks, apart from their geographical location, also vary in size and layout. The parks were chosen because they are urban open parks and they include facilities for physical activity.

Keywords: urban planning, active living behaviour, open parks, sustainable mobility

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Authors: Endalew Fufa Kufi

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Every married person aspires to be a parent regardless of the situation in which s/he lives. Such aspiration meets with reality when the destined parent is able to give adequate supports and services to his/her children, whether the latter are got by birth or through adoption. The adequacy of services parents provide their children is both enriched and tempted by the work on which they involve. On the one hand, parents need to work and earn a living in order to support their family. On the other hand, they must spend most of their time outside home to do the work, which shortens the time and might they spare to care for their children. Where the sufficiency of services parents owe their children could be ascertained by in terms of life skills, physical care and related provisions, the role of working fathers and mothers in providing such supports could be diverse across cultures and work traditions. Hence, this research deals with the investigation of working mothers’ parental practices, challenges they face in providing parental services and the implication for the future progress of the parents and their children. Target of the study will be Arsi University in Oromia Regional State of Ethiopia. Descriptive survey design in holding the research, and data for the research will be collected in the form of experiential self-report from 150 working mothers selected from the entire working women population of Colleges of Agriculture and Environmental Studies and College of Health Sciences through stratified random-sampling. Instruments of data collection will be closed and open-ended questionnaire. Complementary data will also be collected from purposively selected samples through semi-structured interview. Data for the research will be collected through questionnaire first and then through interview. Data analysis will also follow the same procedure. The collected data will systematically be organized and statistically and thematically analyzed in order to come up with indicative findings. The overarching thesis is that, working mothers in the study area bear a lot of responsibilities both at home and at work place which leave them very little time for parenting services. Unless due attention is given to the way they can spare time for their children, they are more likely to be tense between work-life and family care services, which tempt them in different directions.

Keywords: challenges, mothers, practices, university, working

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Authors: S. Pullteap, M. Pathomsuriyaporn

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In this article, a study of employee’s opinion to the factors that affect to the flood preventive and the corrective action plan in an electronic industry at the Sharp Manufacturing (Thailand) Co., Ltd. has been investigated. The surveys data of 175 workers and supervisors have, however, been selected for data analysis. The results is shown that the employees emphasize about the needs in a subsidy at the time of disaster at high levels of 77.8%, as the plan focusing on flood prevention of the rehabilitation equipment is valued at the intermediate level, which is 79.8%. Demonstration of the hypothesis has found that the different education levels has thus been affected to the needs factor at the flood disaster time. Moreover, most respondents give priority to flood disaster risk management factor. Consequently, we found that the flood prevention plan is valued at high level, especially on information monitoring, which is 93.4% for the supervisor item. The respondents largely assume that the flood will have impacts on the industry, up to 80%, thus to focus on flood management plans is enormous.

Keywords: flood prevention plan, flood event, electronic industrial plant, disaster, risk management

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Authors: H. Mahdjoub, B. Hamaidi, B. Zerouali, S. Rouabhia

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The issue of fault detection and diagnosis (FDD) has gained widespread industrial interest in process condition monitoring applications. Accordingly, the use of neuro-fuzzy technic seems very promising. This paper treats a diagnosis modeling a strategic equipment of an industrial installation. We propose a diagnostic tool based on adaptive neuro-fuzzy inference system (ANFIS). The neuro-fuzzy network provides an abductive diagnosis. Moreover, it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. This work was carried out with real data of a lubrication circuit from the gas turbine. The machine of interest is a gas turbine placed in a gas compressor station at South Industrial Centre (SIC Hassi Messaoud Ouargla, Algeria). We have defined the zones of good and bad functioning, and the results are presented to demonstrate the advantages of the proposed method.

Keywords: fault detection and diagnosis, lubrication system, turbine, ANFIS, training, pattern recognition

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Authors: Stuart Bradley, Mathew Legg, Lilyan Panton

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Ultrasonic remote sensing is a useful tool for assessing the interior structure of complex targets. For these methods, significantly enhanced spatial resolution is obtained if the pulse is coded, for example using a linearly changing frequency during the pulse duration. Such pulses have a time-dependent spectral structure. Interpretation of the backscatter from targets is, therefore, complicated if the scattering is frequency-dependent. While analytic models are well established for steady sinusoidal excitations applied to simple shapes such as spheres, such models do not generally exist for temporally evolving excitations. Therefore, models are developed in the current paper for handling such signals so that the properties of the targets can be quantitatively evaluated while maintaining very high spatial resolution. Laboratory measurements on simple shapes are used to confirm the validity of the models.

Keywords: linear FM chirp, time-dependent acoustic scattering, ultrasonic remote sensing, ultrasonic scattering

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Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization

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Authors: V. Kuzhandai Velu, R. Ramesh

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Background and objectives: Acute myocardial infarction (AMI) is the most common cause of mortality and morbidity. Over the last decade, microRNAs (miRs) have emerged as a potential marker for detecting AMI. The current study evaluates the kinetics and importance of miRs in the differential diagnosis of ST-segment elevated MI (STEMI) and non-STEMI (NSTEMI) and its correlation to conventional biomarkers and to predict the immediate outcome of AMI for arrhythmias and left ventricular (LV) dysfunction. Materials and Method: A total of 100 AMI patients were recruited for the study. Routine cardiac biomarker and miRNA levels were measured during diagnosis and serially at admission, 6, 12, 24, and 72hrs. The baseline biochemical parameters were analyzed. The expression of miRs was compared between STEMI and NSTEMI at different time intervals. Diagnostic utility of miR-1, miR-133, miR-208, and miR-499 levels were analyzed by using RT-PCR and with various diagnostics statistical tools like ROC, odds ratio, and likelihood ratio. Results: The miR-1, miR-133, and miR-499 showed peak concentration at 6 hours, whereas miR-208 showed high significant differences at all time intervals. miR-133 demonstrated the maximum area under the curve at different time intervals in the differential diagnosis of STEMI and NSTEMI which was followed by miR-499 and miR-208. Evaluation of miRs for predicting arrhythmia and LV dysfunction using admission sample demonstrated that miR-1 (OR = 8.64; LR = 1.76) and miR-208 (OR = 26.25; LR = 5.96) showed maximum odds ratio and likelihood respectively. Conclusion: Circulating miRNA showed a highly significant difference between STEMI and NSTEMI in AMI patients. The peak was much earlier than the conventional biomarkers. miR-133, miR-208, and miR-499 can be used in the differential diagnosis of STEMI and NSTEMI, whereas miR-1 and miR-208 could be used in the prediction of arrhythmia and LV dysfunction, respectively.

Keywords: myocardial infarction, cardiac biomarkers, microRNA, arrhythmia, left ventricular dysfunction

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Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

Procedia PDF Downloads 143

Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

Procedia PDF Downloads 65

Authors: Y. Venturini, C. Tintori

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Given the continuous demand for improved readout performances in particle and dark matter physics, CAEN SpA is pushing on the development of advanced technologies for detector readout. We present the Digitizers 2.0, the result of the success of the previous Digitizers generation, combined with expanded capabilities and a renovation of the user experience introducing the open FPGA. The first product of the family is the VX2740 (64 ch, 125 MS/s, 16 bit) for advanced waveform recording and Digital Pulse Processing, fitting with the special requirements of Dark Matter and Neutrino experiments. In parallel, CAEN is developing the FERS-5200 platform, a Front-End Readout System designed to read out large multi-detector arrays, such as SiPMs, multi-anode PMTs, silicon strip detectors, wire chambers, GEM, gas tubes, and others. This is a highly-scalable distributed platform, based on small Front-End cards synchronized and read out by a concentrator board, allowing to build extremely large experimental setup. We plan to develop a complete family of cost-effective Front-End cards tailored to specific detectors and applications. The first one available is the A5202, a 64-channel unit for SiPM readout based on CITIROC ASIC by Weeroc.

Keywords: dark matter, digitizers, front-end electronics, open FPGA, SiPM

Procedia PDF Downloads 120

Authors: Regita P. Permata, Ulfa S. Nuraini

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Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

Procedia PDF Downloads 122

Authors: Shukran M. Dadayev

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To author's best knowledge, in this paper, the Basic Properties and Research methods of a Fundamental Particle is studied for the first time. That's to say, Fundamental Particle has not been discovered in the Nature yet. Because Fundamental Particle consists of specific Physical, Geometrical and Internal bases. Geometrical and Internal characteristics that are considered significant for the elementary and fundamental particles aren’t basic properties, characteristics or criteria of a Fundamental Particle. Of course, completely new Physical and Visual experimental methods of Quantum mechanics and Behavioral-Physical investigations of Particles are needed to study and discover the Fundamental Particle. These are new Physical, Visual and Behavioral-Physical experimental methods for describing and discovering the Fundamental Particle in the Nature and Microworld. Fundamental Particle consists of the same Energy-Mass-Motion system and a symmetry of Energy-Mass-Motion. Fundamental Particle supplies each of the elementary particles with the same Energy-Mass-Motion system at the same time and regulates each of the particles. Fundamental Particle gives Energy, Mass and Motion to each particles at the same time, each of the Particles consists of acquired Energy-Mass-Motion system and symmetry. Energy, Mass, Motion given by the Fundamental Particle to the particles are Symmetrical Equivalent and they remain in their primary shapes in all cases. Fundamental Particle gives Energy-Mass-Motion system and symmetry consisting of different measures and functions to each of the particles. The Motion given by the Fundamental Particle to the particles is Gravitation, Gravitational Interaction not only gives Motion, but also cause Motion by attracting. All Substances, Fields and Cosmic objects consist of Energy-Mass-Motion. The Field also includes specific Mass. They are always Energetic, Massive and Active. Fundamental Particle establishes the bases of the Nature. Supplement and Regulating of all the particles existing in the Nature belongs to Fundamental Particle.

Keywords: basic properties of a fundamental particle, behavioral-physical and visual methods, energy-mass-motion system and symmetrical equivalence, fundamental particle

Procedia PDF Downloads 3649

Authors: Mahmoud Lot

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In this article, we will discuss the solution of elliptic optimal control problem. First, by using the nite element method, we obtain the discrete form of the problem. The obtained discrete problem is actually a large scale constrained optimization problem. Solving this optimization problem with traditional methods is difficult and requires a lot of CPU time and memory. But split Bergman method converts the constrained problem to an unconstrained, and hence it saves time and memory requirement. Then we use the split Bregman method for solving this problem, and examples show the speed and accuracy of split Bregman methods for solving these types of problems. We also use the SQP method for solving the examples and compare with the split Bregman method.

Keywords: Split Bregman Method, optimal control with elliptic partial differential equation constraint, finite element method

Procedia PDF Downloads 149

Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

Procedia PDF Downloads 143

Authors: Manoel Pereira, Alvaro Veiga, Camila Epprecht, Renato Costa

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This paper introduces an empirical version of the Esscher transform for risk-neutral option pricing. Traditional parametric methods require the formulation of an explicit risk-neutral model and are operational only for a few probability distributions for the returns of the underlying. In our proposal, we make only mild assumptions on the pricing kernel and there is no need for the formulation of the risk-neutral model for the returns. First, we simulate sample paths for the returns under the physical distribution. Then, based on the empirical Esscher transform, the sample is reweighted, giving rise to a risk-neutralized sample from which derivative prices can be obtained by a weighted sum of the options pay-offs in each path. We compare our proposal with some traditional parametric pricing methods in four experiments with artificial and real data.

Keywords: esscher transform, generalized autoregressive Conditional Heteroscedastic (GARCH), nonparametric option pricing

Procedia PDF Downloads 484

Authors: Gui Yang Wu, Bo Wang, Xin Wang

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Nowadays, 5G service-based interface architecture uses text-based payload like JSON to transfer business data between network functions, which has obvious advantages as internet services but causes unnecessarily larger traffic. In this paper, a new 5G application payload size reduction method is presented to provides the mechanism to negotiate about new capability between network functions when network communication starts up and how 5G application data are reduced according to negotiated information with peer network function. Without losing the advantages of 5G text-based payload, this method demonstrates an excellent result on application payload size reduction and does not increase the usage quota of computing resource. Implementation of this method does not impact any standards or specifications and not change any encoding or decoding functionality too. In a real 5G network, this method will contribute to network efficiency and eventually save considerable computing resources.

Keywords: 5G, JSON, payload size, service-based interface

Procedia PDF Downloads 175

Authors: Aya Tanaka, Mariko Era, Manami Masuda, Yui Okuno, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

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Objectives— Fungi and bacteria are present in a wide range of natural environments. They are breed in the foods such as vegetables and fruit, causing corruption and deterioration of these foods in some cases. Furthermore, some species of fungi and bacteria are known to cause food intoxication or allergic reactions in some individuals. To prevent fungal and bacterial contamination, various fungicides and bactericidal have been developed that inhibit fungal and bacterial growth. Fungicides and bactericides must show high antifungal and antibacterial activity, sustainable activity, and a high degree of safety. Therefore, we focused on the fatty acid salt which is the main component of soap. We focused on especially C10K and C12K. This study aimed to find the effectiveness of the fatty acid salt as antimicrobial agents for food safety. Materials and Methods— Cladosporium cladosporioides NBRC 30314, Penicillium pinophilum NBRC 6345, Aspergillus oryzae (Akita Konno store), Rhizopus oryzae NBRC 4716, Fusarium oxysporum NBRC 31631, Escherichia coli NBRC 3972, Bacillus subtilis NBRC 3335, Staphylococcus aureus NBRC 12732, Pseudomonas aenuginosa NBRC 13275 and Serratia marcescens NBRC 102204 were chosen as tested fungi and bacteria. Hartmannella vermiformis NBRC 50599 and Acanthamoeba castellanii NBRC 30010 were chosen as tested amoeba. Nine fatty acid salts including potassium caprate (C10K) and laurate (C12K) at 350 mM and pH 10.5 were used as antifungal activity. The spore suspension of each fungus (3.0×10⁴ spores/mL) or the bacterial suspension (3.0×10⁵ or 3.0×10⁶ or 3.0×10⁷ CFU/mL) was mixed with each of the fatty acid salts (final concentration of 175 mM). Samples were counted at 0, 10, 60, and 180 min by plating (100 µL) on potato dextrose agar or nutrient agar. Fungal and bacterial colonies were counted after incubation for 1 or 2 days at 30 °C. Results— C10K was antifungal activity of 4 log-unit incubated time for 10 min against fungi other than A. oryzae. C12K was antifungal activity of 4 log-unit incubated time for 10 min against fungi other than P. pinophilum and A. oryzae. C10K and C12K did not show high anti-yeast activity. C10K was antibacterial activity of 6 or 7 log-unit incubated time for 10 min against bacteria other than B. subtilis. C12K was antibacterial activity of 5 to 7 log-unit incubated time for 10 min against bacteria other than S. marcescens. C12K was anti-amoeba activity of 4 log-unit incubated time for 10 min against H. vermiformis. These results suggest C10K and C12K have potential in the field of food safety.

Keywords: food safety, microbes, antimicrobial, fatty acid salts

Procedia PDF Downloads 483

Authors: Tim Nedyalkov

Abstract:

A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. They are collecting, managing, and retaining large amounts of data in cloud environments makes information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Keywords: cloud compliance, cloud security, data governance, privacy protection

Procedia PDF Downloads 109