Search results for: optimal number

Authors: Mars Burke, Alvin Gatto

Abstract:

Rotary-wing aircraft serve as indispensable components in the advancement of aviation, valued for their ability to operate in diverse and challenging environments without the need for conventional runways. This versatility makes them ideal for applications such as environmental conservation, precision agriculture, emergency medical support, and rapid-response operations in rugged terrains. However, although highly maneuverable, rotary-wing platforms generally have lower aerodynamic efficiency than fixed-wing aircraft. This study aims to improve aerodynamic performance by examining a 1/7th-scale rotor blade model equipped with a NACA0012 airfoil using CROTOR software. The analysis focuses on optimal spanwise locations for separating morphing and fixed blade sections at 85%, 90%, and 95% of the blade radius with up to +20 degrees of twist incorporated into the design. Key performance metrics assessed in this investigation include lift coefficient (CL), drag coefficient (CD), lift-to-drag ratio (CL/CD), Mach number, power, thrust coefficient, and Figure of Merit (FOM). Results indicate that the 0.90 r/R position is optimal for dividing the morphing and fixed sections, achieving a significant improvement of over 7% in both lift-to-drag ratio and FOM. These findings underscore the substantial impact on the overall performance of the rotor system and rotational aerodynamics that geometric modifications through the inclusion of a morphing capability can ultimately realise.

Keywords: helicopter, rotor blade, rotary morphing, rotational aerodynamics, twist morphing, adaptive structures

Procedia PDF Downloads 24

Authors: B. R. Raut

Abstract:

The seismic performance of 20-storey benchmark building with semi-active dampers is investigated under various earthquake ground motions. The Semi-Active Variable Friction Dampers (SAVFD) and Magnetorheological Dampers (MR) are used in this study. A recently proposed predictive control algorithm is employed for SAVFD and a simple mechanical model based on a Bouc–Wen element with clipped optimal control algorithm is employed for MR damper. A parametric study is carried out to ascertain the optimum parameters of the semi-active controllers, which yields the minimum performance indices of controlled benchmark building. The effectiveness of dampers is studied in terms of the reduction in structural responses and performance criteria. To minimize the cost of the dampers, the optimal location of the damper, rather than providing the dampers at all floors, is also investigated. The semi-active dampers installed in benchmark building effectively reduces the earthquake-induced responses. Lesser number of dampers at appropriate locations also provides comparable response of benchmark building, thereby reducing cost of dampers significantly. The effectiveness of two semi-active devices in mitigating seismic responses is cross compared. Among two semi-active devices majority of the performance criteria of MR dampers are lower than SAVFD installed with benchmark building. Thus the performance of the MR dampers is far better than SAVFD in reducing displacement, drift, acceleration and base shear of mid to high-rise building against seismic forces.

Keywords: benchmark building, control strategy, input excitation, MR dampers, peak response, semi-active variable friction dampers

Procedia PDF Downloads 288

Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

Abstract:

In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

Procedia PDF Downloads 464

Authors: Hyungoo Kang, Jinkoo Kim

Abstract:

This study investigated the determination of the optimal location and friction force of friction dampers to effectively reduce the seismic response of a reinforced concrete structure designed without considering seismic load. To this end, the genetic algorithm process was applied and the results were compared with those obtained by simplified methods such as distribution of dampers based on the story shear or the inter-story drift ratio. The seismic performance of the model structure with optimally positioned friction dampers was evaluated by nonlinear static and dynamic analyses. The analysis results showed that compared with the system without friction dampers, the maximum roof displacement and the inter-story drift ratio were reduced by about 30% and 40%, respectively. After installation of the dampers about 70% of the earthquake input energy was dissipated by the dampers and the energy dissipated in the structural elements was reduced by about 50%. In comparison with the simplified methods of installation, the genetic algorithm provided more efficient solutions for seismic retrofit of the model structure.

Keywords: friction dampers, genetic algorithm, optimal design, RC buildings

Procedia PDF Downloads 246

Authors: Mohammad Ebrahim Arbabian

Abstract:

This paper investigates the impact of 3D printing, also known as additive manufacturing, on a multi-item supply chain comprising a manufacturer and retailer. Operating under a wholesale-price contract and catering to stochastic customer demand, this study delves into the largely unexplored realm of how 3D printing technology reshapes supply chain dynamics. A distinguishing aspect of 3D printing is its versatility in producing various product types, yet its slower production pace compared to traditional methods poses a challenge. We analyze the trade-off between 3D printing's limited capacity and its enhancement of production flexibility. By delineating the economic circumstances favoring 3D printing adoption by the manufacturer, we establish the Stackelberg equilibrium in the retailer-manufacturer game. Additionally, we determine optimal order quantities for the retailer considering 3D printing as an option for the manufacturer, ascertain optimal wholesale prices in the presence of 3D printing, and compute optimal profits for both parties involved in the supply chain.

Keywords: additive manufacturing, supply chain management, contract theory, Stackelberg game, optimization

Procedia PDF Downloads 66

Authors: B. Kekezoglu, C. Kocatepe, O. Arikan, Y. Hacialiefendioglu, G. Ucar

Abstract:

One of the significant problems of energy systems is to supply economic and efficient energy to consumers. Therefore studies has been continued to reduce technical losses in the network. In this paper, the technical losses analyzed for a portion of European side of Istanbul MV distribution network for different compensation scenarios by considering real system and load data and results are presented. Investigated system is modeled with CYME Power Engineering Software and optimal capacity placement has been proposed to minimize losses.

Keywords: distribution system, optimal capacitor placement, reactive power compensation, technical losses

Procedia PDF Downloads 677

Authors: Liang Ming Zhong, Yu Zhong, Wen Zhong, Fei Fei Yin

Abstract:

Trinary affinity is a description of existence: every object exists as it is known and spoken of, in a system of 2 differences (denoted dif1, dif₂) and 1 similarity (Sim), equivalently expressed as dif₁ / Sim / dif₂ and kn / 0 / tkn (kn = the known, tkn = the 'to be known', 0 = the zero point of knowing). They are mathematically verified and illustrated in this paper by the arrangement of all integers onto 3 columns, where each number exists as a difference in relation to another number as another difference, and the 2 difs as arbitrated by a third number as the Sim, resulting in a trinary affinity or trinity of 3 numbers, of which one is the known, the other the 'to be known', and the third the zero (0) from which both the kn and tkn are measured and specified. Consequently, any number is horizontally specified either as 3n, or as '3n – 1' or '3n + 1', and vertically as 'Cn + c', so that any number seems to occur at the intersection of its X and Y axes and represented by its X and Y coordinates, as any point on Earth’s surface by its latitude and longitude. Technically, i) primes are viewed and treated as progenitors, and composites as descending from them, forming families of composites, each capable of being measured and specified from its own zero called in this paper the realistic zero (denoted 0r, as contrasted to the mathematic zero, 0m), which corresponds to the constant c, and the nature of which separates the composite and prime numbers, and ii) any number is considered as having a magnitude as well as a position, so that a number is verified as a prime first by referring to its descriptive formula and then by making sure that no composite number can possibly occur on its position, by dividing it with factors provided by the composite number formulas. The paper consists of 3 parts: 1) a brief explanation of the trinary affinity of things, 2) the 8 formulas that represent ALL the primes, and 3) families of composite numbers, each represented by a formula. A composite number family is described as 3n + f₁‧f₂. Since there are an infinitely large number of composite number families, to verify the primality of a great probable prime, we have to have it divided with several or many a f₁ from a range of composite number formulas, a procedure that is as laborious as it is the surest way to verifying a great number’s primality. (So, it is possible to substitute planned division for trial division.)

Keywords: trinary affinity, difference, similarity, realistic zero

Procedia PDF Downloads 215

Authors: Kazuyoshi Mori

Abstract:

In this paper, we consider the parametrization of Anantharam’s model within the framework of the factorization approach. In the parametrization, we investigate the number of required parameters of Anantharam’s model. We consider single-input single-output systems in this paper. By the investigation, we find three cases that are (1) there exist plants which require only one parameter and (2) two parameters, and (3) the number of parameters is at most three.

Keywords: linear systems, parametrization, coprime factorization, number of parameters

Procedia PDF Downloads 216

Authors: Pushpendra S. Bharti

Abstract:

Process yield of electric discharge machining (EDM) is directly related to optimal combination(s) of process parameters. Optimization of process parameters of EDM is a multi-objective optimization problem owing to the contradictory behavior of performance measures. This paper employs Grey Relation Analysis (GRA) method as a multi-objective optimization technique for the optimal selection of process parameters combination. In GRA, multi-response optimization is converted into optimization of a single response grey relation grade which ultimately gives the optimal combination of process parameters. Experiments were carried out on die-sinking EDM by taking D2 steel as work piece and copper as electrode material. Taguchi's orthogonal array L36 was used for the design of experiments. On the experimental values, GRA was employed for the parametric optimization. A significant improvement has been observed and reported in the process yield by taking the parametric combination(s) obtained through GRA.

Keywords: electric discharge machining, grey relation analysis, material removal rate, optimization

Procedia PDF Downloads 413

Authors: M. Alipanah, A. Ranjbar, E. Farnad, F. Alipanah

Abstract:

Entropy generation of an Al2O3-water nanofluid due to heat transfer and fluid friction irreversibility has been investigated in a square cavity subject to different side wall temperatures using a nanofluid for natural convection flow. This study has been carried out for the pertinent parameters in the following ranges: Rayleigh number between 104 to 107 and volume fraction between 0 to 0.05. Based on the obtained dimensionless velocity and temperature values, the distributions of local entropy generation, average entropy generation and average Bejan number are determined. The results are compared for a pure fluid and a nanofluid. It is totally found that the heat transfer and entropy generation of the nanofluid is more than the pure fluid and minimum entropy generation and Nusselt number occur in the pure fluid at any Rayleigh number. Results depict that the addition of nanoparticles to the pure fluid has more effect on the entropy generation as the Rayleigh number goes up.

Keywords: entropy generation, natural convection, bejan number, nuselt number, nanofluid

Procedia PDF Downloads 502

Authors: Fernando L. P. Santos, Luiz G. Lyra, Helenice O. Florentino, Daniela R. Cantane

Abstract:

Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility.

Keywords: genetic algorithm, dengue, Aedes aegypti, biological control, chemical control

Procedia PDF Downloads 353

Authors: Abdul Halim Abdul Razik, Ali Elkamel, Leonardo Simon

Abstract:

Wheat straw is one of the alternative feedstocks that may be utilized for bioethanol production especially when sustainability criteria are the major concerns. To increase market competitiveness, optimal supply chain plays an important role since wheat straw is a seasonal agricultural residue. In designing the supply chain optimization model, economic profitability of the thermochemical and biochemical conversion routes options were considered. It was found that torrefied pelletization with gasification route to be the most profitable option to produce bioethanol from the lignocellulosic source of wheat straw.

Keywords: bio-ethanol, optimization, supply chain, wheat straw

Procedia PDF Downloads 739

Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

Abstract:

The main aim of the paper is to implement a technique using distributed generation in distribution systems to reduce the distribution system losses and to improve voltage profiles. The fuzzy logic technique is used to select the proper location of DG and an analytical method is proposed to calculate the size of DG unit at any power factor. The optimal sizes of DG units are compared with optimal sizes obtained using the genetic algorithm. The suggested method is programmed under Matlab software and is tested on IEEE 33 bus system and the results are presented.

Keywords: DG Units, sizing of DG units, analytical methods, optimum size

Procedia PDF Downloads 477

Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

Abstract:

Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: assignment, deadline, greedy approach, Hungarian algorithm, operations research, scheduling

Procedia PDF Downloads 151

Authors: Hassan M. H. Mustafa

Abstract:

This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

Procedia PDF Downloads 475

Authors: Paule Olivia Akotto

Abstract:

The recent literature suggests spending between 50%-85% of oil rents. However, there are not yet clear guidelines for allocating this windfall in the public investment system, while most of the resource-rich countries fail to improve their intergenerational mobility. We study a design of the optimal spending system in Senegal, a low-income developing country featuring newly discovered oil fields and low intergenerational mobility. We build a dynamic general equilibrium model in which rural and urban (Dakar and other urban centers henceforth OUC) households face different health, education, and employment opportunities based on their location, affecting their intergenerational mobility. The model captures the relationship between oil rents, public investment, and multidimensional inequality of opportunity. The government invests oil rents in three broad sectors: health and education, road and industries, and agriculture. Through endogenous productivity externality and human capital accumulation, our model generates the predominant position of Dakar and OUC households in terms of access to health, education, and employment in line with Senegal data. Rural households are worse off in all dimensions. We compute the optimal spending policy under two sets of simulation scenarios. Under the current Senegal public investment strategy, which weighs more health and education investments, we find that the reform maximizing the decline in inequality of opportunity between households, frontloads investment during the first eight years of the oil exploitation and spends the perpetual value of oil wealth thereafter. We will then identify the marginal winners and losers associated with this policy and its redistributive implications. Under our second set of scenarios, we will test whether the Senegalese economy can reach better equality of opportunity outcomes under this frontloading reform, by allowing the sectoral shares of investment to vary. The trade-off will be between cutting human capital investment in favor of agricultural and productive infrastructure or increasing the former. We will characterize the optimal policy by specifying where the higher weight should be. We expect that the optimal policy of the second set strictly dominates in terms of equality of opportunity, the optimal policy computed under the current investment strategy. Finally, we will quantify this optimal policy's aggregate and distributional effects on poverty, well-being, and gender earning gaps.

Keywords: developing countries, general equilibrium, inequality of opportunity, oil rents

Procedia PDF Downloads 243

Authors: Mustafa Dogru, Ruveyda Komurlu

Abstract:

Companies and professionals in the construction sector face various risks in every project depending on the characteristics, size, complexity, the location of the projects and the techniques used. Some risks’ effects may increase as the project progresses whereas new risks may emerge. Because of the ever-changing nature of the risks, risk management is a cyclical process that needs to be repeated throughout the project. Since the risks threaten the success of the project, risk management is an important part of the entire project management process. The aims of this study are to emphasize the importance of risk management in construction projects, summarize the risk identification process, and introduce a number of methods for preventing risks such as alternative design, checklists, prototyping and test-analysis-correction technique etc. Following the literature review conducted to list the techniques for preventing risks, case studies has been performed to compare and evaluate the success of the techniques in a number of completed projects with the same typology, performed domestic and international. Findings of the study suggest that controlling and minimizing the level of the risks in construction projects, taking optimal precautions for different risks, and mitigating or eliminating the effects of risks are important in order to prevent additional costs for the project. Additionally, focusing on the risks that have highest impact is the most rational way to minimize the effects of the risks on projects.

Keywords: construction projects, construction management, project management, risk management

Procedia PDF Downloads 322

Authors: Sangwon Han, Chengquan Jin

Abstract:

Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

Procedia PDF Downloads 190

Authors: Hari Mohan Kushwaha, Santosh Kumar Sahu

Abstract:

In the present study, analysis of heat transfer is carried out in the slip flow region for the fluid flowing between two parallel plates by employing the asymmetric heat fluxes at surface of the plates. The flow is assumed to be hydrodynamically and thermally fully developed for the analysis. The second order velocity slip and viscous dissipation effects are considered for the analysis. Closed form expressions are obtained for the Nusselt number as a function of Knudsen number and modified Brinkman number. The limiting condition of the present prediction for Kn = 0, Kn2 = 0, and Brq1 = 0 is considered and found to agree well with other analytical results.

Keywords: Knudsen number, modified Brinkman number, slip flow, velocity slip

Procedia PDF Downloads 391

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

Abstract:

In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 228

Authors: Teguh Sugiarto

Abstract:

Background: The research aims to explore if there is fraud in a financial statement, use the Act stated that Benford's distribution all digits must compare the number will follow the trend of lower number. Research methods: This research uses all the analysis number being in Benford's law. After receiving the results of the analysis of all the digits, the author makes a distinction between implementation using the scale above and below 5%, the rate of occurrence of difference. With the number which have differences in the range of 5%, then can do the follow-up and the detection of the onset of fraud against the financial statements. The findings: From the research that has been done can be drawn the conclusion that the average of all numbers appear in the financial statements, and compare the rates of occurrence of numbers according to the characteristics of Benford's law. About the existence of errors and fraud in the financial statements of PT medco Energy Tbk did not occur. Conclusions: The study concludes that Benford's law can serve as indicator tool in detecting the possibility of in financial statements to case studies of PT Medco Energy Tbk for the fiscal year 2000-2010.

Keywords: Benford law, first digits, all digits number Benford law, financial statement

Procedia PDF Downloads 241

Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

Abstract:

Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

Procedia PDF Downloads 190

Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

Abstract:

The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

Procedia PDF Downloads 386

Authors: K. Sanjayani, C. Saraswathy, S. Sreenivasan, S. Sudhahar, D. Suganya, K. S. Neelukumari, N. Vijayarangan

Abstract:

Double Base Number System (DBNS) is an imminent system of representing a number using two bases namely 2 and 3, which has its application in Elliptic Curve Cryptography (ECC) and Digital Signature Algorithm (DSA).The previous binary method representation included only base 2. DBNS uses an approximation algorithm namely, Greedy Algorithm. By using this algorithm, the number of digits required to represent a larger number is less when compared to the standard binary method that uses base 2 algorithms. Hence, the computational speed is increased and time being reduced. The standard binary method uses binary digits 0 and 1 to represent a number whereas the DBNS method uses binary digit 1 alone to represent any number (canonical form). The greedy algorithm uses two ways to represent the number, one is by using only the positive summands and the other is by using both positive and negative summands. In this paper, arithmetic operations are used for elliptic curve cryptography. Elliptic curve discrete logarithm problem is the foundation for most of the day to day elliptic curve cryptography. This appears to be a momentous hard slog compared to digital logarithm problem. In elliptic curve digital signature algorithm, the key generation requires 160 bit of data by usage of standard binary representation. Whereas, the number of bits required generating the key can be reduced with the help of double base number representation. In this paper, a new technique is proposed to generate key during encryption and extraction of key in decryption.

Keywords: cryptography, double base number system, elliptic curve cryptography, elliptic curve digital signature algorithm

Procedia PDF Downloads 398

Authors: Hamidreza Fallah Lajimi , Elham Karami, Fatemeh Ali nasab, Mostafa Mahdavikia

Abstract:

Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering

Procedia PDF Downloads 479

Authors: Md Abdullah Al Faruque

Abstract:

A very large percentage of bridge failures are attributed to scouring around bridge piers and this directly influences public safety. Experiments are carried out in a 12-m long rectangular open channel flume made of transparent tempered glass. A 300 mm thick bed made up of sand particles is leveled horizontally to create the test bed and a 50 mm hollow plastic cylinder is used as a model bridge pier. Tests are carried out with varying flow depths and velocities. Data points of various scour parameters such as scour depth, width, and length are collected based on different flow conditions and visual observations of changes in the stream bed downstream the bridge pier are also made as the scour progresses. Result shows that all three major flow characteristics (flow depth, Froude number and densimetric Froude number) have one way or other affect the scour profile.

Keywords: bridge pier scour, densimetric Froude number, flow depth, Froude number, sand

Procedia PDF Downloads 172

Authors: Wesam Jasim, Dongbing Gu

Abstract:

This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotors path tracking. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR to stabilize the quadrotor and successfully track different paths. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.

Keywords: iLQR controller, optimal control, path tracking, quadrotor UAVs

Procedia PDF Downloads 454

Authors: Xiyang Li, Qi Yu, Lun Zhang

Abstract:

In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

Procedia PDF Downloads 92

Authors: Jui-Teng Liao

Abstract:

The selected-response (SR) format has been commonly adopted to assess academic reading in both formal and informal testing (i.e., standardized assessment and classroom assessment) because of its strengths in content validity, construct validity, as well as scoring objectivity and efficiency. When developing a second language (L2) reading test, researchers indicate that the longer the test (e.g., more test items) is, the higher reliability and validity the test is likely to produce. However, previous studies have not provided specific guidelines regarding the optimal length of a test or the most suitable number of test items or reading passages. Additionally, reading tests often include different question types (e.g., factual, vocabulary, inferential) that require varying degrees of reading comprehension and cognitive processes. Therefore, it is important to investigate the impact of question types on the number of items in relation to the score reliability of L2 reading tests. Given the popularity of the SR question format and its impact on assessment results on teaching and learning, it is necessary to investigate the degree to which such a question format can reliably measure learners’ L2 reading comprehension. The present study, therefore, adopted the generalizability (G) theory to investigate the score reliability of the SR format in L2 reading tests focusing on how many test items a reading test should include. Specifically, this study aimed to investigate the interaction between question types and the number of items, providing insights into the appropriate item count for different types of questions. G theory is a comprehensive statistical framework used for estimating the score reliability of tests and validating their results. Data were collected from 108 English as a second language student who completed an English reading test comprising factual, vocabulary, and inferential questions in the SR format. The computer program mGENOVA was utilized to analyze the data using multivariate designs (i.e., scenarios). Based on the results of G theory analyses, the findings indicated that the number of test items had a critical impact on the score reliability of an L2 reading test. Furthermore, the findings revealed that different types of reading questions required varying numbers of test items for reliable assessment of learners’ L2 reading proficiency. Further implications for teaching practice and classroom-based assessments are discussed.

Keywords: second language reading assessment, validity and reliability, Generalizability theory, Academic reading, Question format

Procedia PDF Downloads 92

Authors: Thomas Weber, Nina Strobel, Thomas Kohne, Eberhard Abele

Abstract:

In context of the energy transition in Germany, the importance of so-called virtual power plants in the energy supply continues to increase. The progressive dismantling of the large power plants and the ongoing construction of many new decentralized plants result in great potential for optimization through synergies between the individual plants. These potentials can be exploited by mathematical optimization algorithms to calculate the optimal application planning of decentralized power and heat generators and storage systems. This also includes linear or linear mixed integer optimization. In this paper, procedures for reducing the number of decision variables to be calculated are explained and validated. On the one hand, this includes combining n similar installation types into one aggregated unit. This aggregated unit is described by the same constraints and target function terms as a single plant. This reduces the number of decision variables per time step and the complexity of the problem to be solved by a factor of n. The exact operating mode of the individual plants can then be calculated in a second optimization in such a way that the output of the individual plants corresponds to the calculated output of the aggregated unit. Another way to reduce the number of decision variables in an optimization problem is to reduce the number of time steps to be calculated. This is useful if a high temporal resolution is not necessary for all time steps. For example, the volatility or the forecast quality of environmental parameters may justify a high or low temporal resolution of the optimization. Both approaches are examined for the resulting calculation time as well as for optimality. Several optimization models for virtual power plants (combined heat and power plants, heat storage, power storage, gas turbine) with different numbers of plants are used as a reference for the investigation of both processes with regard to calculation duration and optimality.

Keywords: CHP, Energy 4.0, energy storage, MILP, optimization, virtual power plant

Procedia PDF Downloads 181