Search results for: allocation optimization

Authors: K. K. Riabchenko, T. V Rybitskaya, A. A. Starostenko

Abstract:

Sper Charm-Tau Factory is a double ring e+e- collider to be operated in the center-of-mass energy range from 2 to 6 GeV, with a peak luminosity of about 1035 cm-2s-1 (Crab Waist collision) and with longitudinally polarized electrons at the IP (interaction point). One of the important elements of the cτ-factory is the superconducting two-aperture quadrupole of the final focus. It was decided to make a full-scale prototype quadrupole. The main objectives of our study included: 1) 3D modeling of the quadrupole in the Opera program, 2) Optimization of the geometry of the quadrupole lens, 3) Study of the influence of magnetic properties and geometry of a quadrupole on integral harmonics. In addition to this, the ways of producing unwanted harmonics have been studied. In the course of this work, a 3D model of a two-aperture iron superconducting quadrupole lens was created. A three-dimensional simulation of the magnetic field was performed, and the geometrical parameters of the lens were selected. Calculations helped to find sources of possible errors and methods for correcting unwanted harmonics. In addition to this, calculations show that there are no obstacles to the production of a prototype lens.

Keywords: super cτ-factory, final focus, twin aperture quadrupole lens, integral harmonics

Procedia PDF Downloads 109

Authors: Mengjiao Hu

Abstract:

Nowadays, China's consumption pattern is entering the "experience era"; people's consumption behavior is no longer simply "buy, buy, buy" but the transition from "consumption in space" to "consumption of space". The street is a basic public product and an important public space in the city, and commerce along the street is an important space for people to consume in the "experience era". Therefore, in this way, it is particularly important to create the vitality of the gray space along the street. From the perspective of vitality construction, this paper takes Sha Zheng Street in Chongqing as the empirical object, combined with the theoretical knowledge of behavioral architecture, and based on the current situation of the commercial gray space along Sha Zheng Street, this paper explores the influence factors and the constraints behind the spatial vitality and then puts forward a general strategy to improve the spatial vitality of the commercial gray space along the street. The author hopes that through the exploration of the vitality of commercial gray space along the street, environmental design can be introduced into the integrated design vision of the urban public environment, and the urban designers can be inspired to create a street environment with a living atmosphere with a small start.

Keywords: vitality creation, gray space, street commerce, sha zheng street

Procedia PDF Downloads 77

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

Abstract:

Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder, to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

Procedia PDF Downloads 73

Authors: Francis O. Nwawuru, Jeremiah N. Ezeora

Abstract:

In this paper, a new algorithm for solving the system of split equilibrium and fixed point problems in real Hilbert spaces is considered. The equilibrium bifunction involves a nite family of pseudo-monotone mappings, which is an improvement over monotone operators. More so, it turns out that the solution of the finite family of nonexpansive mappings. The regularized parameters do not depend on Lipschitz constants. Also, the computations of the stepsize, which plays a crucial role in the convergence analysis of the proposed method, do require prior knowledge of the norm of the involved bounded linear map. Furthermore, to speed up the rate of convergence, an inertial term technique is introduced in the proposed method. Under standard assumptions on the operators and the control sequences, using a modified Halpern iteration method, we establish strong convergence, a desired result in applications. Finally, the proposed scheme is applied to solve some optimization problems. The result obtained improves numerous results announced earlier in this direction.

Keywords: equilibrium, Hilbert spaces, fixed point, nonexpansive mapping, extragradient method, regularized equilibrium

Procedia PDF Downloads 34

Authors: Jiani Gao, Qingping Luo, Xinlei Fang

Abstract:

In order to try to achieve better rights and interests for both doctors and patients in the new medical environment, the paper will focus on the renewal and development of medical buildings. In today's highly developed society, many factors have a profound guiding significance for the development of medical buildings. By doing social research, the paper has found that these factors come from all aspects. These factors include the optimization of traditional medical model, rapid alternation of medical technology and equipment, the reform of the social, medical security system, changes in the age structure of the population, the birth of intelligent medical care under the Internet, and the deepening of the concept of green sustainable building development, etc. The purpose of this paper is to capture sensitively these various factors that may affect the evolution of medical buildings in the context of the current era, and to put forward, by using an adaptable development strategy, some feasible suggestions on the design of medical buildings when facing these changes and challenges. Specifically speaking, the adaptable development strategy includes some basic principles and methods, such as using modular design, adopting scalable streamline, selecting a long-span structural system and using replaceable materials and components, etc.

Keywords: medical architecture, adaptable development, medical model, space design

Procedia PDF Downloads 144

Authors: Ensieh Hajeb, Hefzollah Mohammadiyan, Mohamad Baqer Heidari

Abstract:

In this paper layout plans and determine the best place to install a heat recovery boilers , gas turbines , and simulation models built to evaluate the performance of the design and operating conditions, heat recovery boiler design using model built on the basis of operating conditions , the effect of various parameters on the performance of the designed heat recovery boiler , heat recovery boiler installation was designed to evaluate the technical and economic impact on performance would be Turbo generator. Given the importance of this issue, that is the main goal of economic efficiency and reduces costs; this project has been implemented similar plans in which the target is implementation specific patterns. The project will also help us in the process of gas refineries and the actual efficiency of the process after adding a system to analyze the turbine and predict potential problems and how to fix them and appropriate measures according to the results of simulation analysis and results of the process gain. The results of modeling and the effect of different parameters on this line, the software has been ThermoFlow.

Keywords: boiler, gas turbine, turbo generator, power flow

Procedia PDF Downloads 394

Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

Abstract:

Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

Procedia PDF Downloads 449

Authors: Hamed K. Arzani, Ahmad Amiri, Hamid K. Arzani, Salim Newaz Kazi, Ahmad Badarudin

Abstract:

The new design of heat exchangers utilizing an annular distributor opens a new gateway for realizing higher energy optimization. To realize this goal, graphene nanoplatelet-based water nanofluids with promising thermophysical properties were synthesized in the presence of covalent and noncovalent functionalization. Thermal conductivity, density, viscosity and specific heat capacity were investigated and employed as a raw data for ANSYS-Fluent to be used in two-phase approach. After validation of obtained results by analytical equations, two special parameters of convective heat transfer coefficient and pressure drop were investigated. The study followed by studying other heat transfer parameters of annular pass in the presence of graphene nanopletelesbased water nanofluids at different weight concentrations, input powers and temperatures. As a result, heat transfer performance and friction loss are predicted for both synthesized nanofluids.

Keywords: heat transfer, nanofluid, turbulent flow, forced convection flow, graphene nanoplatelet

Procedia PDF Downloads 415

Authors: Mouslem Damkhi

Abstract:

This paper focuses on possible states of a football tournament final table according to the number of participating teams. Each team holds a position in the table with which it is possible to determine the highest and lowest points for that team. This paper proposes an optimized search space based on the minimum and maximum number of points which can be gained by each team to produce and enumerate the possible states for a football tournament final table. The proposed search space minimizes producing the invalid states which cannot occur during a football tournament. The generated states are filtered by a validity checking algorithm which seeks to reach a tournament graph based on a generated state. Thus, the algorithm provides a way to determine which team’s wins, draws and loses values guarantee a particular table position. The paper also presents and discusses the experimental results of the approach on the tournaments with up to eight teams. Comparing with a blind search algorithm, our proposed approach reduces generating the invalid states up to 99.99%, which results in a considerable optimization in term of the execution time.

Keywords: combinatorics, enumeration, graph, tournament

Procedia PDF Downloads 108

Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

Abstract:

It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: education, evolutionary algorithms, evolution strategies, interactive learning applications

Procedia PDF Downloads 323

Authors: Ding Liangxiao

Abstract:

The technological advancements in Micro-Electro-Mechanical Systems (MEMS) have significantly contributed to the development of new, flexible capacitive pressure sensors,which are pivotal in transforming wearable and medical device technologies. This study employs the sophisticated simulation tools available in COMSOL Multiphysics® to develop and analyze a MEMS-based sensor with a tri-layered design. This sensor comprises top and bottom electrodes made from gold (Au), noted for their excellent conductivity, a middle dielectric layer made from a composite of Silver Nanowires (AgNWs) embedded in Thermoplastic Polyurethane (TPU), and a flexible, durable substrate of Polydimethylsiloxane (PDMS). This research was directed towards understanding how changes in the physical characteristics of the AgNWs/TPU dielectric layer—specifically, its thickness and surface area—impact the sensor's operational efficacy. We assessed several key electrical properties: capacitance, electric potential, and membrane displacement under varied pressure conditions. These investigations are crucial for enhancing the sensor's sensitivity and ensuring its adaptability across diverse applications, including health monitoring systems and dynamic user interface technologies. To ensure the reliability of our simulations, we applied the Effective Medium Theory to calculate the dielectric constant of the AgNWs/TPU composite accurately. This approach is essential for predicting how the composite material will perform under different environmental and operational stresses, thus facilitating the optimization of the sensor design for enhanced performance and longevity. Moreover, we explored the potential benefits of innovative three-dimensional structures for the dielectric layer compared to traditional flat designs. Our hypothesis was that 3D configurations might improve the stress distribution and optimize the electrical field interactions within the sensor, thereby boosting its sensitivity and accuracy. Our simulation protocol includes comprehensive performance testing under simulated environmental conditions, such as temperature fluctuations and mechanical pressures, which mirror the actual operational conditions. These tests are crucial for assessing the sensor's robustness and its ability to function reliably over extended periods, ensuring high reliability and accuracy in complex real-world environments. In our current research, although a full dynamic simulation analysis of the three-dimensional structures has not yet been conducted, preliminary explorations through three-dimensional modeling have indicated the potential for mechanical and electrical performance improvements over traditional planar designs. These initial observations emphasize the potential advantages and importance of incorporating advanced three-dimensional modeling techniques in the development of Micro-Electro-Mechanical Systems (MEMS)sensors, offering new directions for the design and functional optimization of future sensors. Overall, this study not only highlights the powerful capabilities of COMSOL Multiphysics® for modeling sophisticated electronic devices but also underscores the potential of innovative MEMS technology in advancing the development of more effective, reliable, and adaptable sensor solutions for a broad spectrum of technological applications.

Keywords: MEMS, flexible sensors, COMSOL Multiphysics, AgNWs/TPU, PDMS, 3D modeling, sensor durability

Procedia PDF Downloads 23

Authors: Josiane R. Pires, Marco A. S. González, Bruna L. Brenner, Luciana S. Roos

Abstract:

The concern with sustainability brought the need for optimization of the buildings to reduce consumption of natural resources. Almost 1/3 of energy demanded by Brazilian housings is used to provide thermal solutions. AEC sector may contribute applying bioclimatic strategies on building design. The aim of this research is to investigate the viability of applying some alternative solutions in residential buildings. The research was developed with computational simulation on single family social housing, examining envelope type, absorptance, and insolation. The analysis of the thermal performance applied both Brazilian standard NBR 15575 and degree-hour method, in the scenery of Porto Alegre, a southern Brazilian city. We used BIM modeling through Revit/Autodesk and used Energy Plus to thermal simulation. The payback of the investment was calculated comparing energy savings and building costs, in a period of 50 years. The results shown that with the increment of envelope’s insulation there is thermal comfort improvement and energy economy, with a pay-back period of 24 to 36 years, in some cases.

Keywords: civil construction, design, thermal performance, energy, economic analysis

Procedia PDF Downloads 538

Authors: Taha Benarbia, Kay W. Axhausen, Anugrah Ilahi

Abstract:

Electric car sharing system as ecologic transportation increasing in the world. The complexity of managing electric car sharing systems, especially one-way trips and battery autonomy have direct influence to on supply and demand of system. One must be able to precisely model the demand and supply of these systems to better operate electric car sharing and estimate its effect on mobility management and the accessibility that it provides in urban areas. In this context, our work focus to develop performances optimization model of the system based on discrete event simulation and stochastic Petri net. The objective is to search optimal decisions and management parameters of the system in order to fulfil at best demand while minimizing undesirable situations. In this paper, we present new model of electric cars sharing with relocation based on monitoring system. The proposed approach also help to precise the influence of battery charging level on the behaviour of system as important decision parameter of this complex and dynamical system.

Keywords: electric car-sharing systems, smart mobility, Petri nets modelling, discrete event simulation

Procedia PDF Downloads 164

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

Abstract:

People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 134

Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid

Abstract:

Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.

Keywords: energy transition, energy modeling, uncertainty, sustainability

Procedia PDF Downloads 68

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

Abstract:

Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular, compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins, which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed, and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

Procedia PDF Downloads 52

Authors: Mujahid S. Alharbi

Abstract:

The construction of process plants in oil and gas-producing countries, such as Saudi Arabia, necessitates substantial investment in design and building. Each new plant, while unique, includes common building types, suggesting an opportunity for design standardization. This study investigates the adoption of standardized Issue For Construction (IFC) packages for non-process buildings in Saudi Aramco. A SWOT analysis presents the strengths, weaknesses, opportunities, and threats of this approach. The approach's benefits are illustrated using the Hawiyah Unayzah Gas Reservoir Storage Program (HUGRSP) as a case study. Standardization not only offers significant cost savings and operational efficiencies but also expedites project timelines, reduces the potential for change orders, and fosters local economic growth by allocating building tasks to local contractors. Standardization also improves project management by easing interface constraints between different contractors and promoting adaptability to future industry changes. This research underscores the standardization of non-process buildings as a powerful strategy for cost optimization, efficiency enhancement, and local economic development in process plant construction within the oil and gas sector.

Keywords: building, construction, management, project, standardization

Procedia PDF Downloads 47

Authors: Saud Al Mahdi

Abstract:

Traditionally,portfolio managers have been discouraged from timing the market. This means, for example, that equity managers have been forced to adhere strictly to a benchmark with static or relatively stable components, such as the SP 500 or the Russell 3000. This means that the portfolio’s exposures to all risk factors should mimic as closely as possible the corresponding exposures of the benchmark. The main risk factor, of course, is the market itself. Effectively, a long-only portfolio would be constrained to have a beta 1. More recently, however, managers have been given greater discretion to adjust their portfolio’s risk exposures (in particular, the beta of their portfolio) dynamically to match the manager’s beliefs about future performance of the risk factors themselves. This freedom translates into the manager’s ability to adjust the portfolio’s beta dynamically. These strategies have come to be known as smart beta strategies. Adjusting beta dynamically amounts to attempting to "time" the market; that is, to increase exposure when one anticipates that the market will rise, and to decrease it when one anticipates that the market will fall. Traditionally, market timing has been believed to be impossible to perform effectively and consistently. Moreover, if a majority of market participants do it, their combined actions could destabilize the market. The aim of this project is to investigate so-called smart beta strategies to determine if they really can add value, or if they are merely marketing gimmicks used to sell dubious investment strategies.

Keywords: beta, alpha, active portfolio management, trading strategies

Procedia PDF Downloads 340

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

Procedia PDF Downloads 248

Authors: Lacramioara Ochiuz, Aurelia Vasile, Iulian Stoleriu, Cristina Ghiciuc, Maria Ignat

Abstract:

Topical administration of chemotherapeutic agents (eg. carmustine, bexarotene, mechlorethamine etc.) in local treatment of cutaneous T-cell lymphoma (CTCL) is accompanied by multiple side effects, such as contact hypersensitivity, pruritus, skin atrophy or even secondary malignancies. A known method of reducing the side effects of anticancer agent is the development of modified drug release systems using drug incapsulation in biocompatible nanoporous inorganic matrices, such as mesoporous MCM-41 silica. Mesoporous MCM-41 silica is characterized by large specific surface, high pore volume, uniform porosity, and stable dispersion in aqueous medium, excellent biocompatibility, in vivo biodegradability and capacity to be functionalized with different organic groups. Therefore, MCM-41 is an attractive candidate for a wide range of biomedical applications, such as controlled drug release, bone regeneration, protein immobilization, enzymes, etc. The main advantage of this material lies in its ability to host a large amount of the active substance in uniform pore system with adjustable size in a mesoscopic range. Silanol groups allow surface controlled functionalization leading to control of drug loading and release. This study shows (I) the amino-grafting optimization of mesoporous MCM-41 silica matrix by means of co-condensation during synthesis and post-synthesis using APTES (3-aminopropyltriethoxysilane); (ii) loading the therapeutic agent (carmustine) obtaining a modified drug release systems; (iii) determining the profile of in vitro carmustine release from these systems; (iv) assessment of carmustine release kinetics by fitting on four mathematical models. Obtained powders have been described in terms of structure, texture, morphology thermogravimetric analysis. The concentration of the therapeutic agent in the dissolution medium has been determined by HPLC method. In vitro dissolution tests have been done using cell Enhancer in a 12 hours interval. Analysis of carmustine release kinetics from mesoporous systems was made by fitting to zero-order model, first-order model Higuchi model and Korsmeyer-Peppas model, respectively. Results showed that both types of highly ordered mesoporous silica (amino grafted by co-condensation process or post-synthesis) are thermally stable in aqueous medium. In what regards the degree of loading and efficiency of loading with the therapeutic agent, there has been noticed an increase of around 10% in case of co-condensation method application. This result shows that direct co-condensation leads to even distribution of amino groups on the pore walls while in case of post-synthesis grafting many amino groups are concentrated near the pore opening and/or on external surface. In vitro dissolution tests showed an extended carmustine release (more than 86% m/m) both from systems based on silica functionalized directly by co-condensation and after synthesis. Assessment of carmustine release kinetics revealed a release through diffusion from all studied systems as a result of fitting to Higuchi model. The results of this study proved that amino-functionalized mesoporous silica may be used as a matrix for optimizing the anti-cancer topical therapy by loading carmustine and developing prolonged-release systems.

Keywords: carmustine, silica, controlled, release

Procedia PDF Downloads 245

Authors: Florence Ibeh, David Oyewmi Oyekunle, David Boohene

Abstract:

The continuous advancement of information technology has completely transformed how businesses and organizations operate on a global scale. The widespread availability of virtual communication tools enables individuals to opt for remote work. While remote employment offers various benefits, such as facilitating corporate growth and enhancing customer support, it also presents distinct challenges. Therefore, investigating the intricacies of virtual team morale is crucial for ensuring the achievement of project objectives. For this study, content analysis of pre-existing secondary data was employed to examine the phenomenon. Essential elements vital for improving the success of projects within virtual teams were identified. These factors include technology adoption, creating a distraction-free work environment, effective leadership, trust-building, clear communication channels, well-defined task allocation, active team participation, and motivation. Furthermore, the study established a substantial correlation between morale levels and the participation and productivity of virtual team members. Higher levels of morale were associated with optimal performance among virtual teams. The study determined that the key factors for enhancing project performance in virtual teams are the adoption of technology, a focused environment, effective leadership, trust, communication, well-defined tasks, collaborative teamwork, and motivation. Additionally, the study discovered that modifying the optimal strategies employed by in-office teams can enhance the diminished morale prevalent in remote teams to sustain a high level of team morale for virtual teams. The findings of this study are highly significant in the dynamic field of project management. Currently, there is limited information regarding strategies that address challenges arising from external factors in virtual teams, such as ambient noise and disruptions caused by family members. The findings underscore the significance of selecting appropriate communication technologies, delineating distinct roles and responsibilities for virtual team members, and nurturing a culture of accountability and trust. Promoting seamless collaboration and instilling motivation among virtual team members are deemed highly effective in augmenting employee engagement and performance within virtual team setting.

Keywords: virtual teams, morale, project performance, distract-free environment, technology adaptation

Procedia PDF Downloads 67

Authors: M. Ahmed Eldesouky, S. Nasr, A. Beltagy

Abstract:

Groundwater is generally considered as the best source for aquaculture as it is well protected from contamination. The most common problem limiting the use of groundwater in Egypt is its high iron, manganese and ammonia content. This problem is often overcome by applying the treatment before use. Aeration in many cases is not enough to oxidize iron and manganese in complex forms with organics. Most of the treatment we use potassium permanganate as an oxidizer followed by a pressurized closed green sand filter. The aim of present study is to investigate the optimum characteristics of groundwater to give lowest iron, manganese and ammonia, maximum production and quality of fish in aquaculture in El-Max Research Station. The major design goal of the system was determined the optimum time for harvesting the treated water, pH, and Glauconite weight to use it for aquaculture process in the research site and achieve the Egyptian law (48/1982) and EPA level required for aquaculture. The water characteristics are [Fe = 0.116 mg/L, Mn = 1.36 mg/L,TN = 0.44 mg/L , TP = 0.07 mg/L , Ammonia = 0.386 mg/L] by using the glauconite filter we obtained high efficiency for removal for [(Fe, Mn and Ammonia] ,but in the Lab we obtained result for (Fe, 43-97), ( Mn,92-99 ), and ( Ammonia, 66-88 )]. We summarized the results to show the optimum time, pH, Glauconite weight, and the best model for design in the region.

Keywords: aquaculture, ammonia in groundwater, groundwater, iron and manganese in water, groundwater treatment

Procedia PDF Downloads 214

Authors: Atabak Rahimzadeh Ilkhch

Abstract:

Friction stir processing (FSP) has promised for application of thermo-mechanical processing techniques where aims to change the micro structural and mechanical properties of materials in order to obtain high performance and reducing the production time and cost. There are lots of studies focused on the microstructure of friction stir welded aluminum alloys. The main focus of this research is on the grain size obtained in the weld zone. Moreover in second part focused on temperature distribution effect over the entire weld zone and its effects on the microstructure. Also, there is a need to have more efforts on investigating to obtain the optimal value of effective parameters such as rotational speed on microstructure and to use the optimum tool designing method. the final results of this study will be present the variation of structural and mechanical properties of materials in the base of applying Friction stir processing and effect of (FSP) processing and tensile testing on surface quality. in the hand, this research addresses the FSP f AA-7020 aluminum and variation f ration of rotation and translational speeds.

Keywords: friction stir processing, AA-7020, thermo-mechanical, microstructure, temperature

Procedia PDF Downloads 262

Authors: Ghada Moussa, Mamoud Owais

Abstract:

Transit Route Network Design Problem (TrNDP) is the most important component in Transit planning, in which the overall cost of the public transportation system highly depends on it. The main purpose of this study is to develop a novel solution methodology for the TrNDP, which goes beyond pervious traditional sophisticated approaches. The novelty of the solution methodology, adopted in this paper, stands on the deterministic operators which are tackled to construct bus routes. The deterministic manner of the TrNDP solution relies on using linear and integer mathematical formulations that can be solved exactly with their standard solvers. The solution methodology has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this research is able to improve the given network solution in terms of number of constructed routes, direct transit service coverage, transfer directness and solution reliability. Although the set of routes resulted from the methodology would stand alone as a final efficient solution for TrNDP, it could be used as an initial solution for meta-heuristic procedures to approach global optimal. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.

Keywords: integer programming, transit route design, transportation, urban planning

Procedia PDF Downloads 250

Authors: Soheila Sadeghi

Abstract:

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

Procedia PDF Downloads 17

Authors: Pablo Chico De Guzman, Cesar Sanchez

Abstract:

Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

Procedia PDF Downloads 187

Authors: Young Min Kim, Deokyeong Choe, Chul Soo Shin

Abstract:

Monascus pigments, commonly used as a natural colorant in Asia, have many biological activities, such as cholesterol level control, anti-obesity, anti-cancer, and anti-oxidant, that have recently been elucidated. Especially, amino acid derivatives of Monascus pigments are receiving much attention because they have higher biological activities than original Monascus pigments. Previously, there have been two ways to produce amino acid derivatives: one-step production and two-step production. However, the one-step production has low purity, and the two-step production—precursor(orange pigments) fermentation and derivatives synthesis—has low productivity and growth rate during its precursor fermentation step. In this study, it was verified that pH is a key factor that affects the stability of orange pigments and the growth rate of Monascus. With an optimal pH profile obtained by pH-stat fermentation, we designed a process of precursor(orange pigments) fermentation that is a pH-controlled fed-batch fermentation. The final concentration of orange pigments in this process increased to 5.5g/L which is about 30% higher than the concentration produced from the previously used precursor fermentation step.

Keywords: cultivation process, fed-batch fermentation, monascus pigments, pH stability

Procedia PDF Downloads 286

Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

Abstract:

Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

Procedia PDF Downloads 510

Authors: Julio Macedo

Abstract:

Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

Procedia PDF Downloads 72

Authors: Carolina Silva, João Nuno Oliveira, Rui Sousa, João Paulo Silva

Abstract:

This study uses genetic algorithms to solve a job scheduling problem in a weaving factory. The underline problem regards an NP-Hard problem concerning unrelated parallel machines, with sequence-dependent setup times. This research uses real data regarding a weaving industry located in the North of Portugal, with a capacity of 96 looms and a production, on average, of 440000 meters of fabric per month. Besides, this study includes a high level of complexity once most of the real production constraints are applied, and several real data instances are tested. Topics such as data analyses and algorithm performance are addressed and tested, to offer a solution that can generate reliable and due date results. All the approaches will be tested in the operational environment, and the KPIs monitored, to understand the solution's impact on the production, with a particular focus on the total number of weeks of late deliveries to clients. Thus, the main goal of this research is to develop a solution that allows for the production of automatically optimized production plans, aiming to the tardiness minimizing.

Keywords: genetic algorithms, textile industry, job scheduling, optimization

Procedia PDF Downloads 140