Search results for: topology optimization

Authors: Antonin Ponsich, Eric Alfredo Rincon Garcia, Roman Anselmo Mora Gutierrez, Miguel Angel Gutierrez Andrade, Sergio Gerardo De Los Cobos Silva, Pedro Lara Velzquez

Abstract:

The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes in such a way that federal or state requirements are fulfilled. In Mexico, this process has been historically carried out by the National Electoral Institute (INE), by optimizing an integer nonlinear programming model, in which population equality and compactness of the designed districts are considered as two conflicting objective functions, while contiguity is included as a hard constraint. The solution technique used by the INE is a Simulated Annealing (SA) based algorithm, which handles the multi-objective nature of the problem through an aggregation function. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (MOEA), the second version of the Non-dominated Sorting Genetic Algorithm (NSGA-II), to this hard combinatorial problem. First results show that, when compared with the SA algorithm, the NSGA-II obtains promising results. The MOEA manages to produce well-distributed solutions over a wide-spread front, even though some convergence troubles for some instances constitute an issue, which should be corrected in future adaptations of MOEAs to the redistricting problem.

Keywords: multi-objective optimization, NSGA-II, redistricting, zone design problem

Procedia PDF Downloads 345

Authors: Szymon Kowieski, Zygmunt Mikno

Abstract:

The study involved the optimization of process parameters during resistance spot welding of Al-coated martensitic boron steel 22MnB5, applied in hot stamping, performed using a programme with a multiple current impulse mode and a programme with variable pressure force. The aim of this research work was to determine the possibilities of a growth in welded joint strength and to identify the expansion of a welding lobe. The process parameters were adjusted on the basis of welding process simulation and confronted with experimental data. 22MnB5 steel is known for its tendency to obtain high hardness values in weld nuggets, often leading to interfacial failures (observed in the study-related tests). In addition, during resistance spot welding, many production-related factors can affect process stability, e.g. welding lobe narrowing, and lead to the deterioration of quality. Resistance spot welding performed using the above-named welding programme featuring 3 levels of force made it possible to achieve 82% of welding lobe extension. Joints made using the multiple current impulse program, where the total welding time was below 1.4s, revealed a change in a peeling mode (to full plug) and an increase in weld tensile shear strength of 10%.

Keywords: 22MnB5, hot stamping, interfacial fracture, resistance spot welding, simulation, single lap joint, welding lobe

Procedia PDF Downloads 354

Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

Abstract:

Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

Procedia PDF Downloads 301

Authors: Michael Dreyfuss, Yahel Giat

Abstract:

Limited battery range and long recharging times are the greatest obstacles to the successful adoption of electric cars. One of the suggestions to overcome these problems is that carmakers retain ownership of batteries and provide battery swapping service so that customers exchange their depleted batteries for recharged batteries. Motivated by this example, we consider the problem of optimal spares allocation in an exchangeable-item, multi-location repair system. We generalize the standard service measures of fill rate and average waiting time to reflect the fact that customers penalize the service provider only if they have to wait more than a ‘tolerable’ time window. These measures are denoted as the window fill rate and the truncated waiting time, respectively. We find that the truncated waiting time is convex and therefore a greedy algorithm solves the spares allocation problem efficiently. We show that the window fill rate is generally S-shaped and describe an efficient algorithm to find a near-optimal solution and detail a priori and a posteriori upper bounds to the distance from optimum. The theory is complemented with a large scale numerical example demonstrating the spare battery allocation in battery swapping stations.

Keywords: convex-concave optimization, exchangeable item, M/G/infinity, multiple location, repair system, spares allocation, window fill rate

Procedia PDF Downloads 469

Authors: Mahdiye Khorasani, Arjun Vijay, Ali Mashayekh, Christian Trapp

Abstract:

The performance of Proton Exchange Membrane Fuel Cell (PEMFC) is highly dependent on the pressure and mass flow of media (Hydrogen and air) throughout the cells and the stack. Higher pressure, on the one hand, results in higher output power of the stack but, on the other hand, increases the electrical power demand of the compressor. In this work, a simulation model of a PEMFC system for vehicle and airplane applications is developed. With this new model, the effect of different pressures and air mass flow rates are investigated to discover the optimum operating point in a PEMFC system, and innovative operation strategies are implemented to optimize reactants flow while minimizing electrical power demand of the compressor for optimum performance. Additionally, a fuel cell system test bench is set up, which contains not only all the auxiliary components for conditioning the gases, reactants, and flows but also a dynamic titling table for testing different orientations of the stack to simulate the flight conditions during take-off and landing and off-road-vehicle scenarios. The results of simulation will be tested and validated on the test bench for future works.

Keywords: air mass flow effect, optimization of operation, pressure effect, PEMFC system, PEMFC system simulation

Procedia PDF Downloads 137

Authors: P. K. Singhal, R. Naresh, V. Sharma

Abstract:

This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

Procedia PDF Downloads 352

Authors: Emanuele Bonamente, Andrea Aquino, Franco Cotana

Abstract:

The exploitation of the low-temperature geothermal resource via ground-source heat pumps is often limited by the high investment cost mainly due to borehole drilling. From the monitoring of a prototypal system currently used by a commercial building, it was found that a simple upgrade of the conventional layout, obtained including a thermal storage between the ground-source heat exchangers and the heat pump, can optimize the ground energy exploitation requiring for shorter/fewer boreholes. For typical applications, a reduction of up to 66% with respect to the conventional layout can be easily achieved. Results from the monitoring campaign of the prototype are presented in this paper, and upgrades of the thermal storage using phase change materials (PCMs) are proposed using computational fluid dynamics simulations. The PCM thermal storage guarantees an improvement of the system coefficient of performance both for summer cooling and winter heating (up to 25%). A drastic reduction of the storage volume (approx. 1/10 of the original size) is also achieved, making it possible to easily place it within the technical room, avoiding extra costs for underground displacement. A preliminary optimization of the PCM geometry is finally proposed.

Keywords: computational fluid dynamics (CFD), geothermal energy, ground-source heat pumps, phase change materials (PCM)

Procedia PDF Downloads 238

Authors: Meshal Alsaiari

Abstract:

Fused Deposition Modeling is one of the additive manufacturing technologies the industry is shifting to nowadays due to its simplicity and low affordable cost. The fabrication processing parameters predominantly influence FDM part strength and mechanical properties. This presentation will demonstrate the influences of the two manufacturing parameters on the tensile testing evaluation indexes, infill density, and Printing Orientation, which were analyzed to create a piping spacer suitable for oil and gas applications. The tensile specimens are made of two polymers, Acrylonitrile Styrene Acrylate (ASA) and High high-impact polystyrene (HIPS), to characterize the mechanical properties performance for creating the final product. The mechanical testing was carried out per the ASTM D638 testing standard, following Type IV requirements. Taguchi's experiment design using an L-9 orthogonal array was used to evaluate the performance output and identify the optimal manufacturing factors. The experimental results demonstrate that the tensile test is more pronounced with 100% infill for ASA and HIPS samples. However, the printing orientations varied in reactions; ASA is maximum at 0 degrees while HIPS shows almost similar percentages between 45 and 90 degrees. Taguchi-Gray integrated methodology was adopted to minimize the response and recognize optimal fabrication factors combinations.

Keywords: FDM, ASTM D638, tensile testing, acrylonitrile styrene acrylate

Procedia PDF Downloads 58

Authors: T. Sattarpour, D. Nazarpour

Abstract:

This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

Procedia PDF Downloads 267

Authors: Qais M. Yousef, Yasmeen A. Alshaer

Abstract:

Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

Procedia PDF Downloads 149

Authors: Hanlin Liu, Hua Li, Yintan AI

Abstract:

Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

Procedia PDF Downloads 15

Authors: Sarra Kitanou

Abstract:

Membrane bioreactor (MBR) systems are one of the most widely used wastewater treatment processes for various municipal and industrial waste streams. It is based on complex interactions between biological processes, filtration process and rheological properties of the liquid to be treated. Its complexity makes understanding system operation and optimization more difficult, and traditional methods based on experimental analysis are costly and time consuming. The present study was based on an external membrane bioreactor pilot scale with ceramic membranes compared to conventional activated sludge process (ASP) plant. Both systems received their influent from a domestic wastewater. The membrane bioreactor (MBR) produced an effluent with much better quality than ASP in terms of total suspended solids (TSS), organic matter such as biological oxygen demand (BOD) and chemical oxygen demand (COD), total Phosphorus and total Nitrogen. Other effluent quality parameters also indicate substantial differences between ASP and MBR. This study leads to conclude that in the case domestic wastewater, MBR treatment has excellent effluent quality. Hence, the replacement of the ASP by the MBRs may be justified on the basis of their improved removal of solids, nutrients, and micropollutants. Furthermore, in terms of reuse the great quality of the treated water allows it to be reused for irrigation.

Keywords: aerobic wastewater treatment, conventional activated sludge process, membrane bioreactor, reuse for irrigation

Procedia PDF Downloads 46

Authors: Payal T. Patel, Ramakant Panchal, Ketankumar G. Patel

Abstract:

Gear in stirred vessel is one of the most critical components in machinery which has power transmission system and it is rotating machinery cost and redesign being the major constraints, there is always a great scope for a mechanical engineer to apply skills to improve the design. Gear will be most effective means of transmitting power in future machinery due to their high degree of compactness. The Galliard moved in the industry from heavy industries such as textile machinery and shipbuilding to industries such as automobile manufacture tools will necessitate the affable application of gear technology. The two-stage planetary reduction gear unit is designed to meet the output specifications. In industries, where the bevel gears are used in turret vessel to transmit the power, that unit is replaced by this planetary gearbox. Use of this type of gearbox is to get better efficiency and also the manufacturing of the bevel gear is more complex than the spur gears. Design a gearbox with the epicyclic gear train. In industries, the power transmission from gearbox to vessel is done through the bevel gears, which transmit the power at a right angle. In this work, the power is to be transmitted vertically from gearbox to vessel, which will increase the efficiency and life of gears. The arrangement of the gears is quite difficult as well as it needs high manufacturing cost and maintenance cost. The design is replaced by the planetary gearbox to reduce the difficulties, and same output is achieved but with a different arrangement of the planetary gearbox.

Keywords: planetary gearbox, epicyclic gear, optimization, dynamic balancing

Procedia PDF Downloads 332

Authors: A. Umar, A. Tamimi

Abstract:

Development of new types of concrete with improved performance is a very important issue for the whole building industry. The development is based on the optimization of the concrete mix design, with an emphasis not only on the workability and mechanical properties but also to the durability and the reliability of the concrete structure in general. Self-compacting concrete (SCC) is a high-performance material designed to flow into formwork under its own weight and without the aid of mechanical vibration. At the same time it is cohesive enough to fill spaces of almost any size and shape without segregation or bleeding. Construction time is shorter and production of SCC is environmentally friendly (no noise, no vibration). Furthermore, SCC produces a good surface finish. Despite these advantages, SCC has not gained much local acceptance though it has been promoted in the Middle East for the last ten to twelve years. The reluctance in utilizing the advantages of SCC, in Bahrain, may be due to lack of research or published data pertaining to locally produced SCC. Therefore, there is a need to conduct studies on SCC using locally available material supplies. From the literature, it has been observed that the use of viscosity modifying admixtures (VMA), micro silica and glass fibers have proved to be very effective in stabilizing the rheological properties and the strength of fresh and hardened properties of self-compacting concrete (SCC). Therefore, in the present study, it is proposed to carry out investigations of SCC with combinations of various dosages of VMAs with and without micro silica and glass fibers and to study their influence on the properties of fresh and hardened concrete.

Keywords: self-compacting concrete, viscosity modifying admixture, micro silica, glass fibers

Procedia PDF Downloads 618

Authors: Naum Simanovsky MD, Michael Zaidman MD, Vladimir Goldman MD.

Abstract:

105 plain AP radiographs of normal adult pelvises (210 hips) were evaluated. Different measurements of normal and dysplastic hip joints in 45 patients were analyzed. Attempt was made to establish reproducible, easy applicable in practice approach for evaluation and follow up of patients with hip dysplasia. The youngest of our patients was 11 years and the oldest was 47 years. Only one of our patients needed conversion to total hip replacement (THR) during ten years of follow-up. It was emphasized that selected set of measurements was built for purpose to serve, especially those who’s scheduled or undergone PAO. This approach was based on concept of acetabulum-femoral head complex and importance of reliable reference points of measurements. Comparative analysis of measured parameters between normal and dysplastic hips was performed. Among 10 selected parameters, we use already well established such as lateral center edge angle and head extrusion index, but to serve specific group of patients with PAO, new parameters were considered such as complex lateralization and complex proximal migration. By our opinion proposed approach is easy applicable in busy clinical practice, satisfactorily delineate hip pathology and give to surgeon who’s going to perform PAO guidelines in condensed form. It is also useful tools for postoperative follow up after PAO.

Keywords: periacetabular osteotomy, plain radiograph’s measurements, adolescents, adult

Procedia PDF Downloads 41

Authors: Ilham Ihoume, Rachid Tadili, Nora Arbaoui

Abstract:

The use of solar energy in agricultural applications has gained significant at‎tention ‎‎in recent years as a sustainable and environmentally friendly alternative to ‎‎conventional energy sources. In particular, solar drying of crops has ‎been identified ‎‎as an effective method to preserve agricultural produce while ‎minimizing energy ‎‎consumption and reducing carbon emissions. In this context, the present study ‎‎aims to evaluate the thermo-economic and ecological ‎performance of a solar-electric hybrid greenhouse dryer designed for grape ‎drying. The proposed system ‎‎integrates solar collectors, an electric heater, ‎and a greenhouse structure to create a ‎‎controlled and energy-efficient environment for grape drying. The thermo-economic assessment involves the ‎analysis of the thermal performance, energy ‎‎consumption, and cost-effectiveness of the solar-electric hybrid greenhouse dryer. ‎‎On the other ‎hand, the ecological assessment focuses on the environmental impact ‎‎of the ‎system in terms of carbon emissions and sustainability. The findings of this ‎‎‎study are expected to contribute to the development of sustainable agricultural ‎‎practices and the promotion of renewable energy technologies in the ‎context of ‎‎food production. Moreover, the results may serve as a basis for the ‎design and ‎‎optimization of similar solar drying systems for other crops and ‎regions.‎

Keywords: solar energy, sustainability, agriculture, energy ‎‎analysis‎

Procedia PDF Downloads 21

Authors: Gabriel Sitler, Yousef Sardahi, Asad Salem

Abstract:

This paper presents an optimal and robust sliding mode controller (SMC) to regulate the position of the knee joint angle for patients suffering from knee injuries. The controller imitates the role of active orthoses that produce the joint torques required to overcome gravity and loading forces and regain natural human movements. To this end, a mathematical model of the shank, the lower part of the leg, is derived first and then used for the control system design and computer simulations. The design of the controller is carried out in optimal and multi-objective settings. Four objectives are considered: minimization of the control effort and tracking error; and maximization of the control signal smoothness and closed-loop system’s speed of response. Optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained. The results show that there are trade-offs among the design objectives and many optimal solutions from which the decision-maker can choose to implement. Also, computer simulations conducted at different points from the Pareto set and assuming knee squat movement demonstrate competing relationships among the design goals. In addition, the proposed control algorithm shows robustness in tracking a standard gait signal when accounting for uncertainty in the shank’s parameters.

Keywords: optimal control, multi-objective optimization, sliding mode control, wearable knee exoskeletons

Procedia PDF Downloads 49

Authors: Sandeep Mohan Ahuja, Gulshan Kumar Jawa

Abstract:

Cyclone separators are crucial components in various industries tasked with efficiently separating particulate matter from gas streams. Achieving optimal performance hinges on a deep understanding of flow dynamics and particle behaviour within these separators. In this investigation, Computational Fluid Dynamics (CFD) simulations are conducted utilizing the Discrete Phase Model (DPM) to dissect the intricate flow patterns, particle trajectories, and separation efficiency within cyclone separators. The study delves into the influence of pivotal parameters like inlet velocity, particle size distribution, and cyclone geometry on separation efficiency. Through numerical simulations, a comprehensive comprehension of fluid-particle interaction phenomena within cyclone separators is attained, allowing for the assessment of separation efficiency across diverse operational conditions and geometrical setups. The insights gleaned from this study promise to advance our understanding of the complex interplay between fluid and particle within cyclone separators, thereby enabling optimization across a wide array of industrial applications. By harnessing the power of CFD simulations and the DPM, this research endeavours to furnish valuable insights for designing, operating, and evaluating the performance of cyclone separators, ultimately fostering greater efficiency and environmental sustainability within industrial processes.

Keywords: cyclone separator, computational fluid dynamics, enhancing efficiency, discrete phase model

Procedia PDF Downloads 9

Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

Abstract:

In this paper, we consider a new real-life Heterogenous Electric Vehicle Routing Problem with Time Dependant Charging Costs and a Mixed Fleet (HEVRP-TDMF), in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time-dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with three different insertion strategies. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem

Procedia PDF Downloads 438

Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

Abstract:

Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

Procedia PDF Downloads 100

Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

Abstract:

In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

Procedia PDF Downloads 18

Authors: Dominika Pihikova, Stefan Belicky, Tomas Bertok, Roman Sokol, Petra Kubanikova, Jan Tkac

Abstract:

Since aberrant glycosylation is frequently accompanied by both physiological and pathological processes in a human body (cancer, AIDS, inflammatory diseases, etc.), the analysis of tumor-associated glycan patterns have a great potential for the development of novel diagnostic approaches. Moreover, altered glycoforms may assist as a suitable tool for the specificity and sensitivity enhancement in early-stage prostate cancer diagnosis. In this paper we discuss the construction and optimization of ultrasensitive sandwich biosensor platform employing lectin as glycan-binding protein. We focus on the immunoassay development, reduction of non-specific interactions and final glycoprofiling of human serum samples including both prostate cancer (PCa) patients and healthy controls. The fabricated biosensor was measured by label-free electrochemical impedance spectroscopy (EIS) with further lectin microarray verification. Furthermore, we analyzed different biosensor interfaces with atomic force microscopy (AFM) in nanomechanical mapping mode showing a significant differences in the altitude. These preliminary results revealing an elevated content of α-2,3 linked sialic acid in PCa patients comparing with healthy controls. All these experiments are important step towards development of point-of-care devices and discovery of novel glyco-biomarkers applicable in cancer diagnosis.

Keywords: biosensor, glycan, lectin, prostate cancer

Procedia PDF Downloads 346

Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

Abstract:

Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

Procedia PDF Downloads 84

Authors: Nima Mahmoudi, Hamzeh Khazaei

Abstract:

Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

Procedia PDF Downloads 137

Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

Abstract:

Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, chemometrics, molecular modeling, molecular descriptors, QSPR

Procedia PDF Downloads 256

Authors: Noha Ibrahim, Eman S. Elzanfaly, Said A. Hassan, Ahmed E. El Gendy

Abstract:

Objectives: The purpose of the study is to develop a sensitive synchronous spectrofluorimetric method with multivariate calibration after studying and optimizing the different variables affecting the native fluorescence intensity of amlodipine and olmesartan implementing an experimental design approach. Method: In the first step, the fractional factorial design used to screen independent factors affecting the intensity of both drugs. The objective of the second step was to optimize the method performance using a Central Composite Face-centred (CCF) design. The optimal experimental conditions obtained from this study were; a temperature of (15°C ± 0.5), the solvent of 0.05N HCl and methanol with a ratio of (90:10, v/v respectively), Δλ of 42 and the addition of 1.48 % surfactant providing a sensitive measurement of amlodipine and olmesartan. The resolution of the binary mixture with a multivariate calibration method has been accomplished mainly by using partial least squares (PLS) model. Results: The recovery percentage for amlodipine besylate and atorvastatin calcium in tablets dosage form were found to be (102 ± 0.24, 99.56 ± 0.10, for amlodipine and Olmesartan, respectively). Conclusion: Method is valid according to some International Conference on Harmonization (ICH) guidelines, providing to be linear over a range of 200-300, 500-1500 ng mL⁻¹ for amlodipine and Olmesartan. The methods were successful to estimate amlodipine besylate and olmesartan in bulk powder and pharmaceutical preparation.

Keywords: amlodipine, central composite face-centred design, experimental design, fractional factorial design, multivariate calibration, olmesartan

Procedia PDF Downloads 121

Authors: Muhammad Awais Kiani, Abdul Basit Kiani, Maryam Kiani

Abstract:

Synergizing Sales and Marketing for Electronics Engineering with Web Development, explores the dynamic relationship between sales, marketing, and web development within the electronics engineering industry. This study is important for the power of digital platforms to connect with customers. Which increases brand visibility and drives sales. It highlights the need for collaboration between sales and marketing teams, as well as the integration of web development strategies to create seamless user experiences and effective lead generation. Furthermore, It also emphasizes the role of data analytics and customer insights in optimizing sales and marketing efforts in the ever-evolving landscape of electronics engineering. Sales and marketing play a crucial role in driving business growth, and in today's digital landscape, web development has become an integral part of these strategies. Web development enables businesses to create visually appealing and user-friendly websites that effectively showcase their products or services. It allows for the integration of e-commerce functionalities, enabling seamless online transactions. Furthermore, web development helps businesses optimize their online presence through search engine optimization (SEO) techniques, social media integration, and content management systems. This abstract highlights the symbiotic relationship between sales marketing in the electronics industry and web development, emphasizing the importance of a strong online presence in achieving business success.

Keywords: electronics industry, web development, sales, marketing

Procedia PDF Downloads 79

Authors: A. Aravind, M. Vetrivel, P. Abhimanyu, C. A. Akaash Emmanuel Raj, K. Sundararaj, V. R. S. Kumar

Abstract:

The choice of high-speed, low budget hatchback car with diversified options is increasing for meeting the new generation buyers trend. This paper is aimed to augment the current speed of the hatchback cars through the aerodynamic drag reduction technique. The inverted airfoils are facilitated at the bottom of the car for generating the downward force for negating the lift while increasing the current speed range for achieving a better road performance. The numerical simulations have been carried out using a 2D steady pressure-based    k-ɛ realizable model with enhanced wall treatment. In our numerical studies, Reynolds-averaged Navier-Stokes model and its code of solution are used. The code is calibrated and validated using the exact solution of the 2D boundary layer displacement thickness at the Sanal flow choking condition for adiabatic flows. We observed through the parametric analytical studies that the inverted airfoil integrated with the bottom surface at various predesigned locations of Hatchback cars can improve its overall aerodynamic efficiency through drag reduction, which obviously decreases the fuel consumption significantly and ensure an optimum road performance lucratively with maximum permissible speed within the framework of the manufactures constraints.

Keywords: aerodynamics of commercial cars, downward force, hatchback car, inverted airfoil

Procedia PDF Downloads 250

Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

Abstract:

The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance

Procedia PDF Downloads 240

Authors: Nabil Mezhoud

Abstract:

The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently.

Keywords: renewable energy sources, energy management, distributed generator, micro-grids, firefly algorithm

Procedia PDF Downloads 32