Search results for: optimal functioning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3771

Search results for: optimal functioning

2631 Powerful Laser Diode Matrixes for Active Vision Systems

Authors: Dzmitry M. Kabanau, Vladimir V. Kabanov, Yahor V. Lebiadok, Denis V. Shabrov, Pavel V. Shpak, Gevork T. Mikaelyan, Alexandr P. Bunichev

Abstract:

This article is deal with the experimental investigations of the laser diode matrixes (LDM) based on the AlGaAs/GaAs heterostructures (lasing wavelength 790-880 nm) to find optimal LDM parameters for active vision systems. In particular, the dependence of LDM radiation pulse power on the pulse duration and LDA active layer heating as well as the LDM radiation divergence are discussed.

Keywords: active vision systems, laser diode matrixes, thermal properties, radiation divergence

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2630 Assessing the Channel Design of the Eco-Friendly ‘Falaj’ Water System in Meeting the Optimal Water Demand: A Case Study of Falaj Al-Khatmain, Sultanate of Oman

Authors: Omer Al-Kaabi, Ahmed Nasr, Abdullah Al-Ghafri, Mohammed Abdelfattah

Abstract:

The Falaj system, derived from natural water sources, is a man-made canal system designed to supply communities of farmers with water for domestic and agricultural purposes. For thousands of years, Falaj has served communities by harnessing the force of gravity; it persists as a vital water management system in numerous regions across the Sultanate of Oman. Remarkably, predates the establishment of many fundamental hydraulic principles used today. Al-Khatmain Falaj, with its accessibility and historical significance spanning over 2000 years, was chosen as the focal point of this study. The research aimed to investigate the efficiency of Al-Khatmain Falaj in meeting specific water demands. The HEC-RAS model was utilized to visualize water flow dynamics within the Falaj channels, accompanied by graphical representations of pertinent variables. The application of HEC-RAS helped to measure different water flow scenarios within the channel, enabling a clear comparison with the demand area catchment. The cultivated land of Al-Khatmain is 723,124 m² and consists of 16,873 palm trees representing 91% of the total area and the remaining 9% is mixed types of trees counted 3,920 trees. The study revealed a total demand of 8,244 m³ is required to irrigate the cultivated land. Through rigorous analysis, the study has proven that the Falaj system in Al-Khatmain operates with high efficiency, as the average annual water supply is 9676.8 m3/day. Additionally, the channel designed at 0.6m width x 0.3m height efficiently holds the optimal water supply, with an average flow depth of 0.21m. Also, the system includes an overflow drainage channel to mitigate floods and prevent crop damage based on seasonal requirements. This research holds promise for examining diverse hydrological conditions and devising effective strategies to manage scenarios of both high and low flow rates.

Keywords: Al-Khatmain, sustainability, Falaj, HEC-RAS, water management system

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2629 Exercise Training for Management Hypertensive Patients: A Systematic Review and Meta-Analysis

Authors: Noor F. Ilias, Mazlifah Omar, Hashbullah Ismail

Abstract:

Exercise training has been shown to improve functional capacity and is recommended as a therapy for management of blood pressure. Our purpose was to establish whether different exercise capacity produces different effect size for Cardiorespiratory Fitness (CRF), systolic (SBP) and diastolic (DBP) blood pressure in patients with hypertension. Exercise characteristic is required in order to have optimal benefit from the training, but optimal exercise capacity is still unwarranted. A MEDLINE search (1985 to 2015) was conducted for exercise based rehabilitation trials in hypertensive patients. Thirty-seven studies met the selection criteria. Of these, 31 (83.7%) were aerobic exercise and 6 (16.3%) aerobic with additional resistance exercise, providing a total of 1318 exercise subjects and 819 control, the total of subjects was 2137. We calculated exercise volume and energy expenditure through the description of exercise characteristics. 4 studies (18.2%) were 451kcal - 900 kcal, 12 (54.5%) were 900 kcal – 1350 kcal and 6 (27.3%) >1351kcal per week. Peak oxygen consumption (peak VO2) increased by mean difference of 1.44 ml/kg/min (95% confidence interval [CI]: 1.08 to 1.79 ml/kg/min; p = 0.00001) with weighted mean 21.2% for aerobic exercise compare to aerobic with additional resistance exercise 4.50 ml/kg/min (95% confidence interval [CI]: 3.57 to 5.42 ml/kg/min; p = 0.00001) with weighted mean 14.5%. SBP was clinically reduce for both aerobic and aerobic with resistance training by mean difference of -4.66 mmHg (95% confidence interval [CI]: -5.68 to -3.63 mmHg; p = 0.00001) weighted mean 6% reduction and -5.06 mmHg (95% confidence interval [CI]: -7.32 to -2.8 mmHg; p = 0.0001) weighted mean 5% reduction respectively. Result for DBP was clinically reduce for aerobic by mean difference of -1.62 mmHg (95% confidence interval [CI]: -2.09 to -1.15 mmHg; p = 0.00001) weighted mean 4% reduction and aerobic with resistance training reduce by mean difference of -3.26 mmHg (95% confidence interval [CI]: -4.87 to -1.65 mmHg; p = 0.0001) weighted mean 6% reduction. Optimum exercise capacity for 451 kcal – 900 kcal showed greater improvement in peak VO2 and SBP by 2.76 ml/kg/min (95% confidence interval [CI]: 1.47 to 4.05 ml/kg/min; p = 0.0001) with weighted mean 40.6% and -16.66 mmHg (95% confidence interval [CI]: -21.72 to -11.60 mmHg; p = 0.00001) weighted mean 9.8% respectively. Our data demonstrated that aerobic exercise with total volume of 451 kcal – 900 kcal/ week energy expenditure may elicit greater changes in cardiorespiratory fitness and blood pressure in hypertensive patients. Higher exercise capacity weekly does not seem better result in management hypertensive patients.

Keywords: blood Pressure, exercise, hypertension, peak VO2

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2628 Sectoral Linkages and Key Sectors of the Georgian Economy

Authors: Vano Benidze, Ioseb Berikashvili

Abstract:

Since 2003, Georgia has implemented many successful reforms, however, economic growth, poverty alleviation and unemployment reduction are still major challenges facing country’s economy. This is due to the fact that most reforms during the past 2 decades were mainly geared toward improving the institutional environment, while economy’s sectoral composition and industrial policy were largely ignored. Each individual sector plays its own specific role in the functioning of the whole economy that cannot be accomplished by any other sector. However, given the unavoidable reality that one sector uses intermediate inputs from other industries to produce its output and sells part of its output to other sectors, the importance of sectors should consider these sectoral interdependencies as well. Simply put, not all industries are equally useful for economic growth and development. In this context, the aim of this paper is to identify the key economic sectors of the Georgian economy. Leontief input-output analysis has been used in deriving backward and forwards linkages for all sectors in the Georgian economy for 2020 and 2021. Sectors with both high backward and forward linkages have been identified as key sectors of the economy. The results obtained are beneficial for the success of the economic and industrial policy of Georgia. If targeted properly by thoughtful policy intervention, key sectors identified in this paper will have a high potential of spreading growth impulses throughout the economy and will possibly generate higher economic growth.

Keywords: structural change, key sectors, development strategies, input-output analysis

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2627 Peat Soil Stabilization by Using Sugarcane Bagasse Ash (SCBA)

Authors: Mohd. Khaidir Abu Talib, Noriyuki Yasufuku, Ryohei Ishikura

Abstract:

It is well recognized that peat can impede the proper hydration of cement because of high organic content, presence of humic acid and less solid particles. That means the large amount of cement is required in order to neutralize the acids or otherwise the process of the peat stabilization remains retarded. Nevertheless, adding a great quantity of cement into the peat is absolutely an unfriendly and uneconomical solution. Sugarcane production is world number one commodities and produced a lot of bagasse. Bagasse is burnt to generate power required for diverse activities in the factory and leave bagasse ash as a waste. Increasing concern of disposal of bagasse residual creates interest to explore the potential application of this material. The objective of this study is to develop alternative binders that are environment friendly and contribute towards sustainable management by utilizing sugarcane bagasse ash (SCBA) in the stabilization of peat soil. Alongside SCBA, Ordinary Portland Cement (OPC), calcium chloride (CaCl2) and silica sand (K7) were used as additives to stabilize the peat that sampled from Hokkaido, Japan. In obtaining the optimal mix design, specimens of stabilized peat were tested in unconfined compression. It was found that stabilized peat comprising 20% and 5% (PCB1-20 and PCB2-5) partial replacement of OPC with SCBA 1 and SCBA 2 attain the maximum unconfined compressive strength (UCS) and discovered greater than untreated soil (P) and UCS of peat-cement (PC) specimen. At the optimal mix design, the UCS of the stabilized peat specimens increased with increasing of curing time, preloading during curing, OPC dosage and K7 dosage. For PCB1-20 mixture, inclusion of a minimum OPC dosage of 300 kg/m3 and K7 dosage of 500 kg/m3 along with curing under 20kPa pressure is recommendable for the peat stabilization to be effective. However for PCB2-5 mixture, it suggested to use more OPC and K7 dosage or alternatively increase the preloading during curing to 40kPa in order to achieve minimum strength target. It can be concluded that SCBA 1 has better quality than SCBA 2 in peat stabilization especially the contribution made by its fine particle size.

Keywords: peat stabilization, sugarcane bagasse ash utilization, partial cement replacement, unconfined strength

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2626 Increasing Business Competitiveness in Georgia in Terms of Globalization

Authors: Badri Gechbaia, Levan Gvarishvili

Abstract:

Despite the fact that a lot of Georgian scientists have worked on the issue of the business competitiveness, it think that it is necessary to deepen the works in this sphere, it is necessary also to perfect the methodology in the estimation of the business competitiveness, we have to display the main factors which define the competitive advantages in the business sphere, we have also to establish the interconnections between the business competitiveness level and the quality of states economical involvement in the international economic processes, we have to define the ways to rise the business competitiveness and its role in the upgrading of countries economic development. The introduction part justifies the actuality of the studied topic and the thesis; It defines the survey subject, the object, and the goals with relevant objectives; theoretical-methodological and informational-statistical base for the survey; what is new in the survey and what the value for its theoretical and practical application is. The aforementioned study is an effort to raise public awareness on this issue. Analysis of the fundamental conditions for the efficient functioning of business in Georgia, identification of reserves for increasing its efficiency based on the assessment of the strengths and weaknesses of the business sector. Methods of system analysis, abstract-logic, induction and deduction, synthesis and generalization, and positive, normative, and comparative analysis are used in the research process. Specific regularities of the impact of the globalization process on the determinants of business competitiveness are established. The reasons for business competitiveness in Georgia have been identified

Keywords: competitiveness, methodology, georgian, economic

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2625 Resilience-Based Emergency Bridge Inspection Routing and Repair Scheduling under Uncertainty

Authors: Zhenyu Zhang, Hsi-Hsien Wei

Abstract:

Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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2624 Characteristics of Photoluminescence in Resonant Quasiperiodic Double-period Quantum Wells

Authors: C. H. Chang, R. Z. Qiu, C. W. Tsao, Y. H. Cheng, C. H. Chen, W. J. Hsueh

Abstract:

Characteristics of photoluminescence (PL) in a resonant quasi-periodic double-period quantum wells (DPQW) are demonstrated. The maximum PL intensity in the DPQW is remarkably greater than that in a traditional periodic QW (PQW) under the Bragg or anti-Bragg conditions. The optimal PL spectrum in the DPQW has an asymmetrical form instead of the symmetrical form in the PQW. Moreover, there are two large values of PL intensity in the DPQW, which also differs from the PQW.

Keywords: Photoluminescence, quantum wells, quasiperiodic structure

Procedia PDF Downloads 709
2623 Application of Harris Hawks Optimization Metaheuristic Algorithm and Random Forest Machine Learning Method for Long-Term Production Scheduling Problem under Uncertainty in Open-Pit Mines

Authors: Kamyar Tolouei, Ehsan Moosavi

Abstract:

In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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2622 A Dual-Mode Infinite Horizon Predictive Control Algorithm for Load Tracking in PUSPATI TRIGA Reactor

Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

Abstract:

The PUSPATI TRIGA Reactor (RTP), Malaysia reached its first criticality on June 28, 1982, with power capacity 1MW thermal. The Feedback Control Algorithm (FCA) which is conventional Proportional-Integral (PI) controller, was used for present power control method to control fission process in RTP. It is important to ensure the core power always stable and follows load tracking within acceptable steady-state error and minimum settling time to reach steady-state power. At this time, the system could be considered not well-posed with power tracking performance. However, there is still potential to improve current performance by developing next generation of a novel design nuclear core power control. In this paper, the dual-mode predictions which are proposed in modelling Optimal Model Predictive Control (OMPC), is presented in a state-space model to control the core power. The model for core power control was based on mathematical models of the reactor core, OMPC, and control rods selection algorithm. The mathematical models of the reactor core were based on neutronic models, thermal hydraulic models, and reactivity models. The dual-mode prediction in OMPC for transient and terminal modes was based on the implementation of a Linear Quadratic Regulator (LQR) in designing the core power control. The combination of dual-mode prediction and Lyapunov which deal with summations in cost function over an infinite horizon is intended to eliminate some of the fundamental weaknesses related to MPC. This paper shows the behaviour of OMPC to deal with tracking, regulation problem, disturbance rejection and caters for parameter uncertainty. The comparison of both tracking and regulating performance is analysed between the conventional controller and OMPC by numerical simulations. In conclusion, the proposed OMPC has shown significant performance in load tracking and regulating core power for nuclear reactor with guarantee stabilising in the closed-loop.

Keywords: core power control, dual-mode prediction, load tracking, optimal model predictive control

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2621 The Impact of Childhood Cancer on the Quality of Life of Survivor: A Qualitative Analysis of Functionality and Participation

Authors: Catarina Grande, Barbara Mota

Abstract:

The main goal of the present study was to understand the impact of childhood cancer on the quality of life of survivors and the extent to which oncologic disease affects the functionality and participation of survivors at the present time, compared to the time of diagnosis. Six survivors of pediatric cancer participated in the study. Participants were interviewed using a semi-structured interview, adapted from two instruments present in the literature - QALY and QLACS - and piloted through a previous study. This study is based on a qualitative approach using content analysis, allowing the identification of categories and subcategories. Subsequently, the correspondence between the units of meaning and the codes in the International Classification of Functioning, Disability, and Health for Children and Young, which contributed to a more detailed analysis of the impact on the quality of life of survivors in relation to the domains under study. The results showed significant changes between the moment of diagnosis and the present moment, concretely at the microsystem of the survivor. Regarding functionality and participation, the results show that the functions of the body are the most affected domain, emphasizing the emotional component that currently has a greater impact on the quality of life of survivors. The present study allowed identifying a set of codes for the development of a CIF-CJ core set for pediatric cancer survivors. He also indicated the need for future studies to validate and deepen these issues.

Keywords: cancer, participation, quality of life, survivor

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2620 Real-Time Radiological Monitoring of the Atmosphere Using an Autonomous Aerosol Sampler

Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

Abstract:

An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

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2619 Identification of Tissue-Specific Transcription Factors in C. roseus with Emphasis to the TIA Biosynthetic Pathway

Authors: F. M. El-Domyati, A. Atef, S. Edris, N. O. Gadalla, M. A. Al-Kordy, A. M. Ramadan, Y. M. Saad, H. S. Al-Zahrani, A. Bahieldin

Abstract:

Transcriptome retrieved from SRA database of different tissues and treatments of C. roseus was assembled in order to detect tissue-specific transcription factors (TFs) and TFs possibly related to terpenoid indole alkaloids (TIA) pathway. A number of 290 TF-like transcripts along with 12 transcripts related to TIA biosynthetic pathway were divided in terms of co-expression in the different tissues, treatments and genotypes. Three transcripts encoding peroxidases 1 and 12 were downregulated in hairy root, while upregulated in mature leaf. Eight different transcripts of the TIA pathway co-expressed with TFs either functioning downstream tryptophan biosynthesis, e.g., tdc, str1 and sgd, or upstream vindoline biosynthesis, e.g., t16h, omt, nmt, d4h and dat. The results showed no differential expression of TF transcripts in hairy roots knocked down for tdc gene (TDCi) as compared to their wild type controls. There were several evidences of tissue-specific expression of TF transcripts in flower, mature leaf, root/hairy root, stem, seedling, hairy root and immature/mature leaves. Regulation included transcription factor families, e.g., bHLH, MYB and WRKY mostly induced by ABA and/or JA (or MeJA) and regulated during abiotic or biotic stress. The information of tissue-specific regulation and co-expression of TFs and genes in the TIA pathway can be utilized in manipulating alkaloid biosynthesis in C. roseus.

Keywords: SRA database, bHLH, MYB, WRKY, co-expression

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2618 Metaheuristics to Solve Tasks Scheduling

Authors: Rachid Ziteuni, Selt Omar

Abstract:

In this paper, we propose a new polynomial metaheuristic elaboration (tabu search) for solving scheduling problems. This method allows us to solve the scheduling problem of n tasks on m identical parallel machines with unavailability periods. This problem is NP-complete in the strong sens and finding an optimal solution appears unlikely. Note that all data in this problem are integer and deterministic. The performance criterion to optimize in this problem which we denote Pm/N-c/summs of (wjCj) is the weighted sum of the end dates of tasks.

Keywords: scheduling, parallel identical machines, unavailability periods, metaheuristic, tabu search

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2617 Self-Tuning Power System Stabilizer Based on Recursive Least Square Identification and Linear Quadratic Regulator

Authors: J. Ritonja

Abstract:

Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification

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2616 Determination of Four Anions in the Ground Layer of Tomb Murals by Ion Chromatography

Authors: Liping Qiu, Xiaofeng Zhang

Abstract:

The ion chromatography method for the rapid determination of four anions (F⁻、Cl⁻、SO₄²⁻、NO₃⁻) in burial ground poles was optimized. The L₉(₃⁴) orthogonal test was used to determine the optimal parameters of sample pretreatment: accurately weigh 2.000g of sample, add 10mL of ultrapure water, and extract for 40min under the conditions of shaking temperature 40℃ and shaking speed 180 r·min-1. The eluent was 25 mmol/L KOH solution, the analytical column was Ion Pac® AS11-SH (250 mm × 4.0 mm), and the purified filtrate was measured by a conductivity detector. Under this method, the detection limit of each ion is 0.066~0.078mg/kg, the relative standard deviation is 0.86%~2.44% (n=7), and the recovery rate is 94.6~101.9.

Keywords: ion chromatography, tomb, anion (F⁻, Cl⁻, SO₄²⁻, NO₃⁻), environmental protection

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2615 Application of Nonlinear Model to Optimize the Coagulant Dose in Drinking Water Treatment

Authors: M. Derraz, M.Farhaoui

Abstract:

In the water treatment processes, the determination of the optimal dose of the coagulant is an issue of particular concern. Coagulant dosing is correlated to raw water quality which depends on some parameters (turbidity, ph, temperature, conductivity…). The objective of this study is to provide water treatment operators with a tool that enables to predict and replace, sometimes, the manual method (jar testing) used in this plant to predict the optimum coagulant dose. The model is constructed using actual process data for a water treatment plant located in the middle of Morocco (Meknes).

Keywords: coagulation process, aluminum sulfate, model, coagulant dose

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2614 Can Demyelinative Lesion Cause To Behaviora Change?

Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

Abstract:

Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

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2613 Numerical Investigation of Turbulent Flow Control by Suction and Injection on a Subsonic NACA23012 Airfoil by Proper Orthogonal Decomposition Analysis and Perturbed Reynolds Averaged Navier‐Stokes Equations

Authors: Azam Zare

Abstract:

Separation flow control for performance enhancement over airfoils at high incidence angle has become an increasingly important topic. This work details the characteristics of an efficient feedback control of the turbulent subsonic flow over NACA23012 airfoil using forced reduced‐order model based on the proper orthogonal decomposition/Galerkin projection and perturbation method on the compressible Reynolds Averaged Navier‐Stokes equations. The forced reduced‐order model is used in the optimal control of the turbulent separated flow over a NACA23012 airfoil at Mach number of 0.2, Reynolds number of 5×106, and high incidence angle of 24° using blowing/suction controlling jets. The Spallart-Almaras turbulence model is implemented for high Reynolds number calculations. The main shortcoming of the POD/Galerkin projection on flow equations for controlling purposes is that the blowing/suction controlling jet velocity does not show up explicitly in the resulting reduced order model. Combining perturbation method and POD/Galerkin projection on flow equations introduce a forced reduced‐order model that can predict the time-varying influence of the blowing/suction controlling jet velocity. An optimal control theory based on forced reduced‐order system is used to design a control law for a nonlinear reduced‐order model, which attempts to minimize the vorticity content in the turbulent flow field over NACA23012 airfoil. Numerical simulations were performed to help understand the behavior of the controlled suction jet at 12% to 18% chord from leading edge and a pair of blowing/suction jets at 15% to 18% and 24% to 30% chord from leading edge, respectively. Analysis of streamline profiles indicates that the blowing/suction jets are efficient in removing separation bubbles and increasing the lift coefficient up to 22%, while the perturbation method can predict the flow field in an accurate Manner.

Keywords: flow control, POD, Galerkin projection, separation

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2612 Numerical Modeling of Storm Swells in Harbor by Boussinesq Equations Model

Authors: Mustapha Kamel Mihoubi, Hocine Dahmani

Abstract:

The purpose of work is to study the phenomenon of agitation of storm waves at basin caused by different directions of waves relative to the current provision thrown numerical model based on the equation in shallow water using Boussinesq model MIKE 21 BW. According to the diminishing effect of penetration of a wave optimal solution will be available to be reproduced in reduced model. Another alternative arrangement throws will be proposed to reduce the agitation and the effects of the swell reflection caused by the penetration of waves in the harbor.

Keywords: agitation, Boussinesq equations, combination, harbor

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2611 Numerical Modeling of the Depth-Averaged Flow over a Hill

Authors: Anna Avramenko, Heikki Haario

Abstract:

This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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2610 Cognition and Communication Disorders Effect on Death Penalty Cases

Authors: Shameka Stanford

Abstract:

This presentation will discuss how cognitive and communication disorders in the areas of executive functioning, receptive and expressive language can impact the problem-solving and decision making of individuals with such impairments. More specifically, this presentation will discuss approaches the legal defense team of capital case lawyers can add to their experience when servicing individuals who have a history of educational decline, special education, and limited intervention and treatment. The objective of the research is to explore and identify the correlations between impaired executive function skills and decision making and competency for individuals facing death penalty charges. To conduct this research, experimental design, randomized sampling, qualitative analysis was employed. This research contributes to the legal and criminal justice system related to how they view, defend, and characterize, and judge individuals with documented cognitive and communication disorders who are eligible for capital case charges. More importantly, this research contributes to the increased ability of death penalty lawyers to successfully defend clients with a history of academic difficulty, special education, and documented disorders that impact educational progress and academic success.

Keywords: cognitive impairments, communication disorders, death penalty, executive function

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2609 Cognitive Behavioral Modification in the Treatment of Aggressive Behavior in Children

Authors: Dijana Sulejmanović

Abstract:

Cognitive-behavioral modification (CBM) is a combination of cognitive and behavioral learning principles to shape and encourage the desired behaviors. A crucial element of cognitive-behavioral modification is that a change the behavior precedes awareness of how it affects others. CBM is oriented toward changing inner speech and learning to control behaviors through self-regulation techniques. It aims to teach individuals how to develop the ability to recognize, monitor and modify their thoughts, feelings, and behaviors. The review of literature emphasizes the efficiency the CBM approach in the treatment of children's hyperactivity and negative emotions such as anger. The results of earlier research show how impulsive and hyperactive behavior, agitation, and aggression may slow down and block the child from being able to actively monitor and participate in regular classes, resulting in the disruption of the classroom and the teaching process, and the children may feel rejected, isolated and develop long-term poor image of themselves and others. In this article, we will provide how the use of CBM, adapted to child's age, can incorporate measures of cognitive and emotional functioning which can help us to better understand the children’s cognitive processes, their cognitive strengths, and weaknesses, and to identify factors that may influence their behavioral and emotional regulation. Such a comprehensive evaluation can also help identify cognitive and emotional risk factors associated with aggressive behavior, specifically the processes involved in modulating and regulating cognition and emotions.

Keywords: aggressive behavior, cognitive behavioral modification, cognitive behavioral theory, modification

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2608 Transformations of Spatial Distributions of Bio-Polymers and Nanoparticles in Water Suspensions Induced by Resonance-Like Low Frequency Electrical Fields

Authors: A. A. Vasin, N. V. Klassen, A. M. Likhter

Abstract:

Water suspensions of in-organic (metals and oxides) and organic nano-objects (chitozan and collagen) were subjected to the treatment of direct and alternative electrical fields. In addition to quasi-periodical spatial patterning resonance-like performance of spatial distributions of these suspensions has been found at low frequencies of alternating electrical field. These resonances are explained as the result of creation of equilibrium states of groups of charged nano-objects with opposite signs of charges at the interparticle distances where the forces of Coulomb attraction are compensated by the repulsion forces induced by relatively negative polarization of hydrated regions surrounding the nanoparticles with respect to pure water. The low frequencies of these resonances are explained by comparatively big distances between the particles and their big masses with t\respect to masses of atoms constituting molecules with high resonance frequencies. These new resonances open a new approach to detailed modeling and understanding of mechanisms of the influence of electrical fields on the functioning of internal organs of living organisms at the level of cells and neurons.

Keywords: bio-polymers, chitosan, collagen, nanoparticles, coulomb attraction, polarization repulsion, periodical patterning, electrical low frequency resonances, transformations

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2607 Drone Swarm Routing and Scheduling for Off-shore Wind Turbine Blades Inspection

Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

Abstract:

In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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2606 BIASS in the Estimation of Covariance Matrices and Optimality Criteria

Authors: Juan M. Rodriguez-Diaz

Abstract:

The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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2605 Optimal Energy Consumption with Semiconductor Lamps

Authors: Pejman Hosseiniun, Rose Shayeghi, Alireza Farzaneh, Abolghasem Ghasempour

Abstract:

Using LED lamps as lighting resources with new technology in designing lighting systems has been studied in this article. In this respect a history of LED emergence, its different manufacturing methods and technologies were revised, then their structure, light production line, its application and benefits in lighting industry has been evaluated. Finally, there is a comparison between these lamps and ordinary lamps to assess light parameters as well as energy consumption using DIALux software. Considering the results of analogies LED lamps have lower consumption and more lighting yield, therefore they are more economically feasible. Color variety, longer usage lap (circa 10 years) and compatibility with DC voltages are other LED lamps perquisites.

Keywords: LED, lighting efficiency, lighting intensity, luminance

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2604 A Systemic Maturity Model

Authors: Emir H. Pernet, Jeimy J. Cano

Abstract:

Maturity models, used descriptively to explain changes in reality or normatively to guide managers to make interventions to make organizations more effective and efficient, are based on the principles of statistical quality control promulgated by Shewhart in the years 30, and on the principles of PDCA continuous improvement (Plan, Do, Check, Act) developed by Deming and Juran. Some frameworks developed over the concept of maturity models includes COBIT, CMM, and ITIL. This paper presents some limitations of traditional maturity models, most of them based on points of reflection and analysis done by some authors. Almost all limitations are related to the mechanistic and reductionist approach of the principles over those models are built. As Systems Theory helps the understanding of the dynamics of organizations and organizational change, the development of a systemic maturity model can help to overcome some of those limitations. This document proposes a systemic maturity model, based on a systemic conceptualization of organizations, focused on the study of the functioning of the parties, the relationships among them, and their behavior as a whole. The concept of maturity from the system theory perspective is conceptually defined as an emergent property of the organization, which arises from as a result of the degree of alignment and integration of their processes. This concept is operationalized through a systemic function that measures the maturity of an organization, and finally validated by the measuring of maturity in organizations. For its operationalization and validation, the model was applied to measure the maturity of organizational Governance, Risk and Compliance (GRC) processes.

Keywords: GRC, maturity model, systems theory, viable system model

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2603 Optimising Transcranial Alternating Current Stimulation

Authors: Robert Lenzie

Abstract:

Transcranial electrical stimulation (tES) is significant in the research literature. However, the effects of tES on brain activity are still poorly understood at the surface level, the Brodmann Area level, and the impact on neural networks. Using a method like electroencephalography (EEG) in conjunction with tES might make it possible to comprehend the brain response and mechanisms behind published observed alterations in more depth. Using a method to directly see the effect of tES on EEG may offer high temporal resolution data on the brain activity changes/modulations brought on by tES that correlate to various processing stages within the brain. This paper provides unpublished information on a cutting-edge methodology that may reveal details about the dynamics of how the human brain works beyond what is now achievable with existing methods.

Keywords: tACS, frequency, EEG, optimal

Procedia PDF Downloads 63
2602 A Kernel-Based Method for MicroRNA Precursor Identification

Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

Procedia PDF Downloads 144