Search results for: pilot optimization

Authors: Hari Singh, Abhishek Kamboj, Sudhir Kumar

Abstract:

This investigation proposes a grey-based Taguchi method to solve the multi-response problems. The grey-based Taguchi method is based on the Taguchi’s design of experimental method, and adopts Grey Relational Analysis (GRA) to transfer multi-response problems into single-response problems. In this investigation, an attempt has been made to optimize the drilling process parameters considering weighted output response characteristics using grey relational analysis. The output response characteristics considered are surface roughness, burr height and hole diameter error under the experimental conditions of cutting speed, feed rate, step angle, and cutting environment. The drilling experiments were conducted using L27 orthogonal array. A combination of orthogonal array, design of experiments and grey relational analysis was used to ascertain best possible drilling process parameters that give minimum surface roughness, burr height and hole diameter error. The results reveal that combination of Taguchi design of experiment and grey relational analysis improves surface quality of drilled hole.

Keywords: metal matrix composite, drilling, optimization, step drill, surface roughness, burr height, hole diameter error

Procedia PDF Downloads 325

Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli

Abstract:

In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.

Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks

Procedia PDF Downloads 93

Authors: Ilona Krone

Abstract:

Maternal smoking during pregnancy increases the risk of perinatal/postnatal negative health outcomes; however, only 1 in 5 pregnant smokers quit smoking. That is a clinical and public health problem. Pregnant smokers have negative paternal support, and higher levels of perceived stress than non-smokers and quitters return to smoking in a stressful situation. A crisis like the COVID-19 outbreak causes significant uncertainty and stress. For pregnant women, additional stress may increase due to concerns for their fetus. Strategies targeting maternal stress and isolation may be particularly useful to prevent negative outcomes for women and their fetuses. Within the post-doctoral study, cooperating with leading specialists, an innovative program for pregnant smokers will be developed. Feasibility for reducing craving, distress intolerance, Covid 19 related stress, and fear in pregnant women in Latvia will be assessed.

Keywords: COVID 19, mindfulness, motivation, pregnancy, smoking cessation

Procedia PDF Downloads 224

Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

Abstract:

In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

Procedia PDF Downloads 419

Authors: Ferzat Anka

Abstract:

Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

Procedia PDF Downloads 81

Authors: Huanhuan Qiang, Sijia Jin

Abstract:

Population aging has become a global trend, and China has entered an aging society, implementing an active aging system focused on home and community-based care. However, most urban communities where elderly people live face issues such as monotonous planning, unappealing landscapes, and inadequate aging infrastructure, which do not meet the requirements for active aging. Intergenerational friendliness and mutual assistance are key components in China's active aging policy framework. Therefore, residential development should prioritize enhancing intergenerational friendliness. Residential and public spaces are central to community life and well-being, offering new and challenging venues to improve relationships among residents of different ages. They are crucial for developing intergenerational communities with diverse generations and non-blood relationships. This paper takes the Maigaoqiao community in Nanjing, China, as a case study, examining intergenerational interactions in public spaces. Based on Maslow's hierarchy of needs and using time geography analysis, it identifies the spatiotemporal behavior characteristics of intergenerational groups in outdoor activities. Then construct an intergenerational-friendly evaluation system and an IPA quadrant model for public spaces in residential areas. Lastly, it explores optimization strategies for public spaces to promote intergenerational friendly interactions, focusing on five aspects: accessibility, safety, functionality, a sense of belonging, and interactivity.

Keywords: intergenerational friendliness, demand theory, spatiotemporal behavior, IPA analysis, existing residential public space

Procedia PDF Downloads 13

Authors: Eric Mwenda, Shadrack Ngene

Abstract:

Human-wildlife conflicts (HWCs) are the main threat to conservation in Africa. This is because wildlife needs overlap with those of humans. In Kenya, about 70% of wildlife occurs outside protected areas. As a result, wildlife and human range overlap, causing HWCs. The HWCs in Kenya occur in the drylands adjacent to protected areas. The top five counties with the highest incidences of HWC are Taita Taveta, Narok, Lamu, Kajiado, and Laikipia. The common wildlife species responsible for HWCs are elephants, buffaloes, hyenas, hippos, leopards, baboons, monkeys, snakes, and crocodiles. To ensure individuals affected by the conflicts are compensated, Kenya has developed a model of HWC compensation claims data collection and payment. We collected data on HWC from all eight Kenya Wildlife Service (KWS) Conservation Areas from 2009 to 2019. Additional data was collected from stakeholders' consultative workshops held in the Conservation Areas and a literature review regarding payment of injuries and ongoing insurance schemes being practiced in areas. This was followed by the description of the claims administration process and calculation of the pricing of the compensation claims. We further developed a digital platform for data capture and processing of all reported conflict cases and payments. Our product recognized four categories of HWC (i.e., human death and injury, property damage, crop destruction, and livestock predation). Personal bodily injury and human death were provided based on the Continental Scale of Benefits. We proposed a maximum of Kenya Shillings (KES) 3,000,000 for death. Medical, pharmaceutical, and hospital expenses were capped at a maximum of KES 150,000, as well as funeral costs at KES 50,000. Pain and suffering were proposed to be paid for 12 months at the rate of KES 13,500 per month. Crop damage was to be based on farm input costs at a maximum of KES 150,000 per claim. Livestock predation leading to death was based on Tropical Livestock Unit (TLU), which is equivalent to KES 30,000, whick includes Cattle (1 TLU = KES 30,000), Camel (1.4 TLU = KES 42,000), Goat (0.15 TLU = 4,500), Sheep (0.15 TLU = 4,500), and Donkey (0.5 TLU = KES 15,000). Property destruction (buildings, outside structures and harvested crops) was capped at KES 150,000 per any one claim. We conclude that it is possible to use an administrator to collect data on HWC compensation claims and make payments using technology. The success of the new approach will depend on a piloting program. We recommended that a pilot scheme be initiated for eight months in Taita Taveta, Kajiado, Baringo, Laikipia, Narok, and Meru Counties. This will test the claims administration process as well as harmonize data collection methods. The results of this pilot will be crucial in adjusting the scheme before country-wide roll out.

Keywords: human-wildlife conflicts, compensation, human death and injury, crop destruction, predation, property destruction

Procedia PDF Downloads 59

Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

Abstract:

Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

Procedia PDF Downloads 367

Authors: Debasis Sengupta, Sudipta Das

Abstract:

The class of life distributions with decreasing mean residual life (DMRL) is well known in the field of reliability modeling. It contains the IFR class of distributions and is contained in the NBUE class of distributions. While upper and lower bounds of the reliability distribution function of aging classes such as IFR, IFRA, NBU, NBUE, and HNBUE have discussed in the literature for a long time, there is no analogous result available for the DMRL class. We obtain the upper and lower bounds for the reliability function of the DMRL class in terms of first order finite moment. The lower bound is obtained by showing that for any fixed time, the minimization of the reliability function over the class of all DMRL distributions with a fixed mean is equivalent to its minimization over a smaller class of distribution with a special form. Optimization over this restricted set can be made algebraically. Likewise, the maximization of the reliability function over the class of all DMRL distributions with a fixed mean turns out to be a parametric optimization problem over the class of DMRL distributions of a special form. The constructive proofs also establish that both the upper and lower bounds are sharp. Further, the DMRL upper bound coincides with the HNBUE upper bound and the lower bound coincides with the IFR lower bound. We also prove that a pair of sharp upper and lower bounds for the reliability function when the distribution is increasing mean residual life (IMRL) with a fixed mean. This result is proved in a similar way. These inequalities fill a long-standing void in the literature of the life distribution modeling.

Keywords: DMRL, IMRL, reliability bounds, hazard functions

Procedia PDF Downloads 399

Authors: Nancy Ann P. Gonzales, Serafin L. Ngohayon

Abstract:

The Nurturing Indigenous Knowledge Experts (NIKE) among the young generation in Ifugao was a project in Ifugao, Philippines spearheaded by the Ifugao State University (IFSU) and was sponsored by the UNESCO Association in Japan. Through the project, he Ifugao Indigenous Knowledge Workbook was developed. It contains nine chapters. The workbook was pilot-tested to students who had IK classes. The descriptive survey method of research was used. A questionnaire was used to gather data from first year Bachelor of Elementary Education and Bachelor of Political Science students. Frequency count, percentage and mean were computed. T-test was used to determine if there exists significant difference on knowledge gained before and after IK was taught to the students. Results revealed that the respondents have an increased level of IK in all the areas covered in the NIKE workbook after they enrolled in their classes. It is alarming to note that the students are knowledgeable about IK but they are not practicing it. However, according to the respondents, they will apply their IK through teaching after graduation.

Keywords: curriculum, elders, Indigenous knowledge, and students

Procedia PDF Downloads 357

Authors: Ekin Nurbaş

Abstract:

One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 154

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

Abstract:

This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 160

Authors: Pradipta Risang Ratna Sambawa, Driya Herseta, Mahendra Fajri Nugraha

Abstract:

In 2020, PT Petrokimia Gresik implemented a program to increase the ROP (Run Of Pile) production rate at the Phosphate Fertilizer 1 plant, causing an increase in scrubbing water consumption in the 100/200 area unit. This increase in water consumption causes a higher discharge of wastewater, which can further cause local flooding, especially during the rainy season. The 100/200 area of the Phosphate Fertilizer 1 plant is close to the warehouse and is often a passing area for trucks transporting raw materials. This causes the pH in the wastewater to become acidic (the worst point is up to pH 1). The problem of flooding and exposure to acidic wastewater in the 100/200 area of Phosphate Fertilizer Plant 1 was then resolved by PT Petrokimia Gresik through wastewater optimization steps called the 3R program (Reduce, Reuse, and Recycle). The 3R (Reduce, reuse, and recycle) program consists of an air consumption reduction program by considering the liquid/gas ratio in scrubbing unit of 100/200 Phosphate Fertilizer 1 plant, creating a wastewater interconnection line so that wastewater from unit 100/200 can be used as scrubbing water in the Phonska 1, Phonska 2, Phonska 3 and unit 300 Phosphate Fertilizer 1 plant and increasing scrubbing effectiveness through scrubbing effectiveness simulations. Through a series of wastewater optimization programs, PT Petrokimia Gresik has succeeded in reducing NaOH consumption for neutralization up to 2,880 kg/day or equivalent in saving up to 314,359.76 dollars/year and reducing process water consumption up to 600 m3/day or equivalent in saving up to 63,739.62 dollars/year.

Keywords: fertilizer, phosphate fertilizer, wastewater, wastewater treatment, water management

Procedia PDF Downloads 32

Authors: Hosein Ghahremani, MohammadReza Khoshchehre, Pejman Hakemi

Abstract:

This study involves numerical simulations of a vertical plate-type photo-bioreactor to investigate the performance of Microalgae Spirulina and Control and optimization of parameters for the digital controller by Taguchi method that MATLAB software and Qualitek-4 has been made. Since the addition of parameters such as temperature, dissolved carbon dioxide, biomass, and ... Some new physical parameters such as light intensity and physiological conditions like photosynthetic efficiency and light inhibitors are involved in biological processes, control is facing many challenges. Not only facilitate the commercial production photo-bioreactor Microalgae as feed for aquaculture and food supplements are efficient systems but also as a possible platform for the production of active molecules such as antibiotics or innovative anti-tumor agents, carbon dioxide removal and removal of heavy metals from wastewater is used. Digital controller is designed for controlling the light bioreactor until Microalgae growth rate and carbon dioxide concentration inside the bioreactor is investigated. The optimal values of the controller parameters of the S/N and ANOVA analysis software Qualitek-4 obtained With Reaction curve, Cohen-Con and Ziegler-Nichols method were compared. The sum of the squared error obtained for each of the control methods mentioned, the Taguchi method as the best method for controlling the light intensity was selected photo-bioreactor. This method compared to control methods listed the higher stability and a shorter interval to be answered.

Keywords: photo-bioreactor, control and optimization, Light intensity, Taguchi method

Procedia PDF Downloads 398

Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

Abstract:

Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

Procedia PDF Downloads 344

Authors: Jiahao Zhou, Lei Wang

Abstract:

In heterogeneous supercomputing clusters, designing an efficient scheduling strategy is crucial for enhancing both energy efficiency and workflow execution performance. The dynamic allocation and reclamation of computing resources are essential for improving resource utilization. However, existing studies often allocate fixed resources to jobs prior to execution, maintaining these resources until job completion, which overlooks the importance of dynamic scheduling. This paper proposes a heterogeneous hierarchical fine-grained scheduling algorithm (HeHiFiS) based on graph convolutional networks (GCN) and proximal policy optimization (PPO) to address issues such as prolonged workflow completion times and low resource utilization in heterogeneous supercomputing clusters. Specifically, GCN is employed to extract task dependency features as part of the state information, and the PPO reinforcement learning algorithm is then used to train the scheduling policy. The trained scheduling policy dynamically adjusts scheduling actions during operation based on the continuously changing states of tasks and computing resources. Additionally, we developed a heterogeneous scheduling simulation platform to validate the effectiveness of the proposed algorithm. Experimental results indicate that HeHiFiS, by incorporating resource inheritance and intra-task parallel mechanisms, significantly improves resource utilization. Compared to existing scheduling algorithms, HeHiFiS achieves over a 50% improvement in both job completion and response performance metrics.

Keywords: heterogeneous, dynamic scheduling, GCN, PPO

Procedia PDF Downloads 8

Authors: S. Rawashdi, D. Bshouty

Abstract:

This paper aimed at discussing how to urge middle and high school Arab students in Israel to be aware of the importance of and investing in learning mathematics. In the first phase of the study, three questionnaires were passed to two nine-grade classes, one on Awareness, one on Awakeness and one on Learning. One of the two classes was an outstanding class from a public school (PUBS) of 31 students, and the other a heterogeneous class from a private school (PRIS) with 31 students. The Learning questionnaire which was administrated to the Awareness and Awareness topics was passed to PRIS and the Awareness and Awareness Questionnaires were passed to the PUBS class After two months we passed the post-questionnaire to both classes to validate the long-term impact of the study. The findings of the study show that awakeness and awareness processes have an effect on the math learning process, on its context in students' daily lives and their growing interest in learning math.

Keywords: awakeness, awareness, learning mathematics, pupils

Procedia PDF Downloads 144

Authors: Bandar A. Alkhayyal

Abstract:

Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

Procedia PDF Downloads 162

Authors: Iulia E. Falcan

Abstract:

The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

Procedia PDF Downloads 174

Authors: Wenjuan Lu

Abstract:

China and Hungary have risen from a friendly and comprehensive cooperative relationship to a comprehensive strategic partnership in recent years, and the economic and trade relations between the two countries have developed smoothly. As an important country along the ‘Belt and Road’, Hungary and China have strong economic complementarities and have unique advantages in carrying China's industrial transfer and economic transformation and development. The construction of the China-Hungary Economic and Trade Cooperation Zone, which was initiated by the ‘Sino-Hungarian Borsod Industrial Zone’ and the ‘Hungarian Central European Trade and Logistics Cooperation Park’ has promoted infrastructure construction, optimized production capacity, promoted industrial restructuring, and formed brand and agglomeration effects. Enhancing the influence of Chinese companies in the European market has also promoted economic development in Hungary and even in Central and Eastern Europe. However, as the China-Hungary Economic and Trade Cooperation Zone is still in its infancy, there are still shortcomings such as small scale, single function, and no prominent platform. In the future, based on the needs of China's cooperation with ‘17+1’ and China-Hungary cooperation, on the basis of appropriately expanding the scale of economic and trade cooperation zones and appropriately increasing the number of economic and trade cooperation zones, it is better to focus on optimizing and adjusting its functions and highlighting different economic and trade cooperation. The differentiated function of the trade zones strengthens the multi-faceted cooperation of economic and trade cooperation zones and highlights its role as a platform for cooperation in information, capital, and services.

Keywords: ‘One Belt, One Road’ Initiative, China-Hungary economic and trade cooperation zone, function optimization, Central and Eastern Europe

Procedia PDF Downloads 184

Authors: Eashan Hatti

Abstract:

In software development, programmers often must make a choice between high-level programming and high-performance programs. High-level programming encourages the use of complex, pervasive abstractions. However, the use of these abstractions degrades performance-high performance demands that programs be low-level. In a compiler, the optimizer attempts to let the user have both. The optimizer takes high-level, abstract code as an input and produces low-level, performant code as an output. However, there is a problem with having the optimizer be a built-in part of the compiler. Domain-specific abstractions implemented as libraries are common in high-level languages. As a language’s library ecosystem grows, so does the number of abstractions that programmers will use. If these abstractions are to be performant, the optimizer must be extended with new optimizations to target them, or these abstractions must rely on existing general-purpose optimizations. The latter is often not as effective as needed. The former presents too significant of an effort for the compiler developers, as they are the only ones who can extend the language with new optimizations. Thus, the language becomes more high-level, yet the optimizer – and, in turn, program performance – falls behind. Programmers are again confronted with a choice between high-level programming and high-performance programs. To investigate a potential solution to this problem, we developed Peridot, a prototype programming language. Peridot’s main contribution is that it enables library developers to easily extend the language with new optimizations themselves. This allows the optimization workload to be taken off the compiler developers’ hands and given to a much larger set of people who can specialize in each problem domain. Because of this, optimizations can be much more effective while also being much more numerous. To enable this, Peridot supports metaprogramming designed for implementing program transformations. The language is split into two fragments or “levels”, one for metaprogramming, the other for high-level general-purpose programming. The metaprogramming level supports logic programming. Peridot’s key idea is that optimizations are simply implemented as metaprograms. The meta level supports several specific features which make it particularly suited to implementing optimizers. For instance, metaprograms can automatically deduce equalities between the programs they are optimizing via unification, deal with variable binding declaratively via higher-order abstract syntax, and avoid the phase-ordering problem via non-determinism. We have found that this design centered around logic programming makes optimizers concise and easy to write compared to their equivalents in functional or imperative languages. Overall, implementing Peridot has shown that its design is a viable solution to the problem of writing code which is both high-level and performant.

Keywords: optimization, metaprogramming, logic programming, abstraction

Procedia PDF Downloads 91

Authors: Chien-Song Chyang, Yu-Chi Wang

Abstract:

For sludge disposal, incineration is considered to be better than direct burial because of regulations and space limitations in Taiwan. Additionally, burial after incineration can effectively prolong the lifespan of a landfill. Therefore, it is the most satisfactory method for treating sludge at present. Of the various incineration technologies, the fluidized bed incinerator is a suitable choice due to its fuel flexibility. In this work, sludge generated from industrial plants was treated in a pilot-scale vortexing fluidized bed. The moisture content of the sludge was 48.53%, and its LHV was 454.6 kcal/kg. Primary gas and secondary gas were fixed at 3 Nm³/min and 1 Nm³/min, respectively. Diesel burners with on-off controllers were used to control the temperature; the bed temperature was set to 750±20 °C, and the freeboard temperature was 850±20 °C. The experimental data show that the NO emission increased with bed temperature. The maximum NO emission is 139 ppm, which is in agreement with the regulation. The CO emission is low than 100 ppm through the operation period. The mean particle size of fly ash collected from baghouse decreased with operating time. The ration of bottom ash to fly ash is about 3. Compared with bottom ash, the potassium in the fly ash is much higher. It implied that the potassium content is not the key factor for aggregation of bottom ash.

Keywords: bottom ash, fluidized-bed combustion, incineration, sludge

Procedia PDF Downloads 279

Authors: Mohammad Reza Ostad Ali Naghi Kashani

Abstract:

Nowadays, the amounts of companies which tend to have an Enterprise Resource Planning (ERP) application are increasing. Although ERP projects are expensive, time consuming, and complex, there are some successful experiences. These days, developing countries are striving to implement ERP projects successfully; however, there are many obstacles. Therefore, these projects would be failed or partially failed. This paper concerns the implementation of a successful ERP implementation, IFS, in Iran at Dana Geophysics Company (DGC). After a short review of ERP and ERP market in Iran, we propose a three phases deployment methodology (phase 1: Preparation and Business Process Management (BPM) phase 2: implementation and phase 3: testing, golive-1 (pilot) and golive-2 (final)). Then, we present five guidelines (Project Management, Change Management, Business Process Management (BPM), Training& Knowledge Management, and Technical Management), which were chose as work streams. In this case study we present lessons learned in Project management and Business process Management.

Keywords: business process management, critical success factors, ERP, project management

Procedia PDF Downloads 497

Authors: Aliaa M. El-Borai, Ehab A. Beltagy, Eman E. Gadallah, Samy A. ElAssar

Abstract:

Bioremediation technology is now used for treatment instead of traditional metal removal methods. A strain was isolated from Marsa Alam, Red sea, Egypt showed high resistance to high lead concentration and was identified by the 16S rRNA gene sequencing technique as Halomonas sp. ES015. Medium optimization was carried out using Plackett-Burman design, and the most significant factors were yeast extract, casamino acid and inoculums size. The optimized media obtained by the statistical design raised the removal efficiency from 84% to 99% from initial concentration 250 ppm of lead. Moreover, Box-Behnken experimental design was applied to study the relationship between yeast extract concentration, casamino acid concentration and inoculums size. The optimized medium increased removal efficiency to 97% from initial concentration 500 ppm of lead. Immobilized Halomonas sp. ES015 cells on sponge cubes, using optimized medium in loop bioremediation column, showed relatively constant lead removal efficiency when reused six successive cycles over the range of time interval. Also metal removal efficiency was not affected by flow rate changes. Finally, the results of this research refer to the possibility of lead bioremediation by free or immobilized cells of Halomonas sp. ES015. Also, bioremediation can be done in batch cultures and semicontinuous cultures using column technology.

Keywords: bioremediation, lead, Box–Behnken, Halomonas sp. ES015, loop bioremediation, Plackett-Burman

Procedia PDF Downloads 200

Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

Abstract:

Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

Procedia PDF Downloads 340

Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

Abstract:

Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

Procedia PDF Downloads 85

Authors: Digdem M. Siyez, Bariscan Ozturk, Erol Esen, Ender Siyez, Yelda Kagnici, Bahar Baran

Abstract:

Infertility is a reproductive disease identified with the absence of pregnancy after regular unprotected sexual intercourse that has been lasting for 12 months or more. Some of the factors that cause infertility, which has been considered as a social and societal issue since the first days of the humankind, are preventable. These are veneral diseases, age, the frequency of the intercourse and its timing, drug use, bodyweight, environmental and professional conditions. Having actual information about the reproductive health is essential to take protective and preventive measures, and it is accepted as the most effective way to reduce the rate of infertility. However, during the literature review, it has been observed that there are so few studies that focus on the prevention of the infertility. The aim of this study is to develop a psycho-education program to reduce infertility among university students and also to evaluate the program’s effectiveness. It is believed that this program will increase the information level about infertility among the university students, help them to adopt healthy attitudes, develop life skills, create awareness about the risk factors and also contribute to the literature. Throughout the study, first, the contents of sexual/reproductive health programs developed for university students were examined by the researches. Besides, “Views about Reproductive Health Psycho-education Program Survey” was developed and applied to 10221 university students from 21 universities. In accordance with the literature and the university students’ views about reproductive health psycho-education program consisting of 9 sessions each of which lasts for 90 minutes was developed. The pilot program was carried out with 16 volunteer undergraduate students attending to a state university. During the evaluation of the pilot study, at the end of each session “Session Evaluation Form” and at the end of the entire program “Program Evaluation Form” were administered to the participants. Besides, one week after the end of the program, a focus group with half of the group, and individual interviews with the rest were conducted. Based on the evaluations, it was determined that the session duration is enough, the teaching methods meet the expectation, the techniques applied are appropriate and clear, and the materials are adequate. Also, an extra session was added to psycho-education program based on the feedbacks of the participants. In order to evaluate program’s effectiveness, Solomon control group design will be used. According to this design, the research has 2 experiment groups and 2 control groups. The participants who voluntarily participated in the research after the announcement of the psycho-education program were divided into experiment and control groups. In the experiment 1 and control 1 groups, “Personal Information Test”, “Infertility Information Test” and “Infertility Attitude Scale”, “Self Identification Inventory” and “Melbourne Decision Scale” were administered as a preliminary test. Currently, at the present stage, psycho-education still continues. After this 10-week program, the same tests will be administered again as the post-tests. The decision upon which statistical method will be applied in the analysis will be made afterwards according to whether the data meets the presuppositions or not.

Keywords: infertility, prevention, psycho-education, reproductive health

Procedia PDF Downloads 235

Authors: Parth Mehta, Vedasri Bai Khavala, Prabhu Rajagopal, Tiju Thomas

Abstract:

There is an increasing need for alternative clean fuels, and hydrogen (H₂) has long been considered a promising solution with a high calorific value (142MJ/kg). However, the storage of H₂ and expensive processes for its generation have hindered its usage. Sodium borohydride (NaBH₄) can potentially be used as an economically viable means of H₂ storage. Thus far, there have been attempts to optimize the life of NaBH₄ (half-life) in aqueous media by stabilizing it with sodium hydroxide (NaOH) for various pH values. Other reports have shown that H₂ yield and reaction kinetics remained constant for all ratios of H₂O to NaBH₄ > 30:1, without any acidic catalysts. Here we highlight the importance of pH and H₂O: NaBH₄ ratio (80:1, 40:1, 20:1 and 10:1 by weight), for NaBH₄ stabilization (half-life reaction time at room temperature) and corrosion minimization of H₂ reactor components. It is interesting to observe that at any particular pH>10 (e.g., pH = 10, 11 and 12), the H₂O: NaBH₄ ratio does not have the expected linear dependence with stability. On the contrary, high stability was observed at the ratio of 10:1 H₂O: NaBH₄ across all pH>10. When the H₂O: NaBH₄ ratio is increased from 10:1 to 20:1 and beyond (till 80:1), constant stability (% degradation) is observed with respect to time. For practical usage (consumption within 6 hours of making NaBH₄ solution), 15% degradation at pH 11 and NaBH₄: H₂O ratio of 10:1 is recommended. Increasing this ratio demands higher NaOH concentration at the same pH, thus requiring a higher concentration or volume of acid (e.g., HCl) for H₂ generation. The reactions are done with tap water to render the results useful from an industrial standpoint. The observed stability regimes are rationalized based on complexes associated with NaBH₄ when solvated in water, which depend sensitively on both pH and NaBH₄: H₂O ratio.

Keywords: hydrogen, sodium borohydride, stability optimization, H₂O:NaBH₄ ratio

Procedia PDF Downloads 127

Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

Abstract:

A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

Procedia PDF Downloads 204

Authors: Joanne F. Hayek

Abstract:

This study explores the use of gamification to promote citizen e-participation in urban planning. The research departs from a case study: the ‘Shape Your City’ web app designed and programmed by the author and presented as part of the 2021 Dubai Design Week to engage citizens in the co-creation of the future of their city through a gamified experience. The paper documents the design and development methodology of the web app and concludes with the findings of its pilot release. The case study explores the use of mobile interactive mapping, real-time data visualization, augmented reality, and machine learning as tools to enable co-planning. The paper also details the user interface design strategies employed to integrate complex cross-sector e-planning systems and make them accessible to citizens.

Keywords: gamification, co-planning, citizen e-participation, mobile interactive mapping, real-time data visualization

Procedia PDF Downloads 145