Search results for: evolutionary optimization techniques

Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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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 117

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

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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

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Authors: Katja Ignatieva, Patrick Wong

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We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices.

Keywords: stochastic volatility, affine jump-diffusion models, high frequency data, model specification, markov chain monte carlo

Procedia PDF Downloads 97

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

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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 370

Authors: M. Soleimani, D. Cree, C. Chafe, L. Bates

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The accidental release of petroleum products into the environment could have harmful consequences to our ecosystem. Different techniques such as mechanical separation, membrane filtration, incineration, treatment processes using enzymes and dispersants, bioremediation, and sorption process using sorbents have been applied for oil spill remediation. Most of the techniques investigated are too costly or do not have high enough efficiency. This study was conducted to determine the sorption performance of hemp byproducts (cellulosic materials) in terms of sorption capacity and kinetics for hydrophobic and hydrophilic fluids. In this study, heavy oil, light oil, diesel fuel, and water/water vapor were used as sorbate fluids. Hemp stalk in different forms, including loose material (hammer milled (HM) and shredded (Sh) with low bulk densities) and densified forms (pellet form (P) and crumbled pellets (CP)) with high bulk densities, were used as sorbents. The sorption/retention tests were conducted according to ASTM 726 standard. For a quick-purpose application of the sorbents, the sorption tests were conducted for 15 min, and for an ideal sorption capacity of the materials, the tests were carried out for 24 h. During the test, the sorbent material was exposed to the fluid by immersion, followed by filtration through a stainless-steel wire screen. Water vapor adsorption was carried out in a controlled environment chamber with the capability of controlling relative humidity (RH) and temperature. To determine the kinetics of sorption for each fluid and sorbent, the retention capacity also was determined intervalley for up to 24 h. To analyze the kinetics of sorption, pseudo-first-order, pseudo-second order and intraparticle diffusion models were employed with the objective of minimal deviation of the experimental results from the models. The results indicated that HM and Sh materials had the highest sorption capacity for the hydrophobic fluids with approximately 6 times compared to P and CP materials. For example, average retention values of heavy oil on HM and Sh was 560% and 470% of the mass of the sorbents, respectively. Whereas, the retention of heavy oil on P and CP was up to 85% of the mass of the sorbents. This lower sorption capacity for P and CP can be due to the less exposed surface area of these materials and compacted voids or capillary tubes in the structures. For water uptake application, HM and Sh resulted in at least 40% higher sorption capacity compared to those obtained for P and CP. On average, the performance of sorbate uptake from high to low was as follows: water, heavy oil, light oil, diesel fuel. The kinetic analysis indicated that the second-pseudo order model can describe the sorption process of the oil and diesel better than other models. However, the kinetics of water absorption was better described by the pseudo-first-order model. Acetylation of HM materials could improve its oil and diesel sorption to some extent. Water vapor adsorption of hemp fiber was a function of temperature and RH, and among the models studied, the modified Oswin model was the best model in describing this phenomenon.

Keywords: environment, fiber, petroleum, sorption

Procedia PDF Downloads 121

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

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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

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Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Nima Mahmoudi, Hamzeh Khazaei

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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 174

Authors: S. Merazga, F. Boudeffar, A. Bouaoua, A. Cheriet, M. Berouaken, M. Mebarki, K. Ayouz, N. Gabouze

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Several anode materials as transition metal oxides (Fe3O4, SnO2 a, SnO2, LiCoO2, and Li₄Ti₅O₁₂) has been used. Although titanium oxide has attracted great attention as a; superior electrode for Li-ion batteries due tohis excellent characteristic such as: high capacity, low cost and non-toxicity. In this work, the Synthesis and Characterization of Si Doped Li₄Ti₅O₁₂ with hydrothermal Method was electrochemically evaluated. The SEM images shows that the morphology of LTO powders sizes in the range 70nm.The electrochemical properties of synthesizer nanopowders are investigated for use as an anode active material for lithium-ion batteries by galvanostatic techniques in Li-half cells, obtaining reversible discharge capacity of 173.8 mAh/g at 0.1C even upon 100 cycles.Though the doped powders exhibit an upgrade in The electrical conductivity , This is suitable for use as a high-power cathode material for lithium-ion batteries.

Keywords: LTO, li-ion, battteries, anode

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

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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

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Authors: Sara Namdarian, Hafez Salleh

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This paper scrutinizes the circumstances of the application of Augmented Reality (AR) technology to enhance the adaptability of architecture classrooms in private Malaysian university classrooms. This study aims to indicate the constraints of mono-functional classrooms in comparison to the potentials of multi-functional classrooms derived from AR application through an exploratory mixed method strategy. This paper expects to contribute towards recognition of suitable AR techniques which can be applied in the development of Adaptive-AR-Classroom-Systems (AARCS) in architecture classrooms. The findings, derived from the analysis, show current classrooms have limited functional spaces, and concludes that AR application can be used in design classrooms to provide a variety of visuals and virtual objects that are required in conducting architecture projects in higher educational centers.

Keywords: design activity, space enhancement, design education, architectural design augmented reality

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Authors: Sachinkumar Patil, Sonali Patil, Shitalkumar Patil

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Nanoparticles played important role in the biomedicine. New advanced methods having great potential apllication in the diagnosis and therapy of cancer. Now a day’s magnetic nanoparticles used in cancer therapy. Cancer is the major disease causes death. Magnetic nanoparticles show response to the magnetic field on the basis of this property they are used in cancer therapy. Cancer treated with hyperthermia by using magnetic nanoparticles it is unconventional but more safe and effective method. Magnetic nanoparticles prepared by using different innovative techniques that makes particles in uniform size and desired effect. Magnetic nanoparticles already used as contrast media in magnetic resonance imaging. A magnetic nanoparticle has been great potential application in cancer diagnosis and treatment as well as in gene therapy. In this review we will discuss the progress in cancer therapy based on magnetic nanoparticles, mainly including magnetic hyperthermia, synthesis and characterization of magnetic nanoparticles, mechanism of magnetic nanoparticles and application of magnetic nanoparticles.

Keywords: magnetic nanoparticles, synthesis, characterization, cancer therapy, hyperthermia, application

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Authors: P. Venkata Karthik, B. Kranthi Kumar

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Fly ash is a solid waste product of coal based electric power generating plants. Fly ash is the finest of coal ash particles and it is transported from the combustion chamber by exhaust gases. Fly ash is removed by particulate emission control devices such as electrostatic precipitators or filter fabric bag-houses. It is a fine material with spherical particles. Large quantities of fly ash discharged from coal-fired power stations are a major problem not only in terms of scarcity of land available for its disposal, but also in environmental aspects. Fly ash can be one of the alternatives and can be a viable option to use as a filling material. This paper contains the problems associated with fly ash generation, need for its management and the efficacy of fly ash composite as a backfilling material. By conducting suitable geotechnical investigations and numerical modelling techniques, the fly ash composite material was tested. It also contains case studies of typical Indian opencast and underground coal mines.

Keywords: backfilling, fly ash, high concentration slurry disposal, power plant, void infilling

Procedia PDF Downloads 250

Authors: Thomas J. Bell III

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This paper explores the value of assimilating certification training within a traditional course curriculum. This innovative approach is believed to increase stakeholder value within the Computer Information System program at Texas Wesleyan University. Stakeholder value is obtained from increased job marketability and critical thinking skills that create employment-ready graduates. This paper views value as first developing the capability to earn an industry-recognized certification, which provides the student with more job placement compatibility while allowing the use of critical thinking skills in a liberal arts business program. Graduates with industry-based credentials are often given preference in the hiring process, particularly in the information technology sector. And without a pioneering curriculum that better prepares students for an ever-changing employment market, its educational value is dubiously questioned. Since certifications are trending in the hiring process, academic programs should explore the viability of incorporating certification training into teaching pedagogy and courses curriculum. This study will examine the use of the balanced scorecard across four performance dimensions (financial, customer, internal process, and innovation) to measure the stakeholder value of certification training within a traditional course curriculum. The balanced scorecard as a strategic management tool may provide insight for leveraging resource prioritization and decisions needed to achieve various curriculum objectives and long-term value while meeting multiple stakeholders' needs, such as students, universities, faculty, and administrators. The research methodology will consist of quantitative analysis that includes (1) surveying over one-hundred students in the CIS program to learn what factor(s) contributed to their certification exam success or failure, (2) interviewing representatives from the Texas Workforce Commission to identify the employment needs and trends in the North Texas (Dallas/Fort Worth) area, (3) reviewing notable Workforce Innovation and Opportunity Act publications on training trends across several local business sectors, and (4) analyzing control variables to identify specific correlations between industry alignment and job placement to determine if a correlation exists. These findings may provide helpful insight into impactful pedagogical teaching techniques and curriculum that positively contribute to certification credentialing success. And should these industry-certified students land industry-related jobs that correlate with their certification credential value, arguably, stakeholder value has been realized.

Keywords: certification exam teaching pedagogy, exam preparation, testing techniques, exam study tips, passing certification exams, embedding industry certification and curriculum alignment, balanced scorecard performance evaluation

Procedia PDF Downloads 103

Authors: Mazhar B. Tayel, Eslam I. AlSaba

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The heart is the most important part in any body organisms. It effects and affected by any factor in the body. Therefore, it is a good detector of any matter in the body. When the heart signal is non-stationary signal, therefore, it should be study its variability. So, the Heart Rate Variability (HRV) has attracted considerable attention in psychology, medicine and have become important dependent measure in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability. However, remain complex issues are fraught with pitfalls. This paper presents one of the non-linear techniques to analyze HRV. It discusses 'What Poincare plot is?', 'How it is work?', 'its usage benefits especially in HRV', 'the limitation of Poincare cause of standard deviation SD1, SD2', and 'How overcome this limitation by using complex correlation measure (CCM)'. The CCM is most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2.

Keywords: heart rate variability, chaotic system, poincare, variance, standard deviation, complex correlation measure

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Authors: Sri Sai Ramya Bojedla, Falguni Pati

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Nature provides the best of solutions to humans. One such incredible gift to regenerative medicine is silk. The literature has publicized a long appreciation for silk owing to its incredible physical and biological assets. Its bioactive nature, unique mechanical strength, and processing flexibility make us curious to explore further to apply it in the clinics for the welfare of mankind. In this study, Antheraea mylitta and Bombyx mori silk fibroin microfibers are developed by two economical and straightforward steps via degumming and hydrolysis for the first time, and a bioactive composite is manufactured by mixing silk fibroin microfibers at various concentrations with polycaprolactone (PCL), a biocompatible, aliphatic semi-crystalline synthetic polymer. Reconstructive surgery in any part of the body except for the maxillofacial region deals with replacing its function. But answering both the aesthetics and function is of utmost importance when it comes to facial reconstruction as it plays a critical role in the psychological and social well-being of the patient. The main concern in developing adequate bone graft substitutes or a scaffold is the noteworthy variation in each patient's bone anatomy. Additionally, the anatomical shape and size will vary based on the type of defect. The advent of additive manufacturing (AM) or 3D printing techniques to bone tissue engineering has facilitated overcoming many of the restraints of conventional fabrication techniques. The acquired patient's CT data is converted into a stereolithographic (STL)-file which is further utilized by the 3D printer to create a 3D scaffold structure in an interconnected layer-by-layer fashion. This study aims to address the limitations of currently available materials and fabrication technologies and develop a customized biomaterial implant via 3D printing technology to reconstruct complex form, function, and aesthetics of the facial anatomy. These composite scaffolds underwent structural and mechanical characterization. Atomic force microscopic (AFM) and field emission scanning electron microscopic (FESEM) images showed the uniform dispersion of the silk fibroin microfibers in the PCL matrix. With the addition of silk, there is improvement in the compressive strength of the hybrid scaffolds. The scaffolds with Antheraea mylitta silk revealed higher compressive modulus than that of Bombyx mori silk. The above results of PCL-silk scaffolds strongly recommend their utilization in bone regenerative applications. Successful completion of this research will provide a great weapon in the maxillofacial reconstructive armamentarium.

Keywords: compressive modulus, 3d printing, maxillofacial reconstruction, natural fiber reinforced composites, silk fibroin microfibers

Procedia PDF Downloads 191

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

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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

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Authors: Moustafa Osman Mohamed

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This paper will explore the influence of energy sector in Arab Republic of Egypt which has shared its responsibilities of many environmental challenges as the second largest economy in the Middle East (after Iran). Air and water pollution, desertification, inadequate disposal of solid waste and damage to coral reefs are serious problems that influence environmental management in Egypt. The intensive reliance of high population density and strong industrial growth are wearing Egypt's resources, and the rapidly-growing population has forced Egypt to breakdown agricultural land to residential and relevant use of commercial ingestion. The depletion effects of natural resources impose the government to apply innovation techniques in emission control and focus on sustainability. The cogeneration will be presented to control thermal losses and increase efficiency of energy power system.

Keywords: cogeneration, environmental management, power electricity, energy indicators

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Authors: Pelin Su Firat, Sohyung Cho

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Biopsy or aspiration procedures are known to be complicated as they involve the penetration of a needle through human tissues, including vital organs. This research presents the design of a force sensor-guided device to be used with syringes and needles for aspiration and biopsy. The development of the device was aimed to help accomplish accurate needle placement and increase the performance of the surgeon in navigating the tool and tracking the target. Specifically, a prototype for a force-sensor embedded syringe has been created using 3D (3-Dimensional) modeling and printing techniques in which two different force sensors were used to provide significant force feedback to users during the operations when needles pernitrate different tissues. From the extensive tests using synthetic tissues, it is shown that the proposed syringe design has accomplished the desired accuracy, efficiency, repeatability, and effectiveness. Further development is desirable through usability tests.

Keywords: biopsy, syringe, force sensors, haptic feedback

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

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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

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Authors: Mehdi Ameur, Ahmed Essakdi, Tamou Nasser

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The purpose of this paper is the analysis and modeling of the photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturb and observe (P&O), incremental conductance (INC) and fuzzy logic controller(FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: photovoltaic array, maximum power point tracking, MPPT, perturb and observe, P&O, incremental conductance, INC, hill climbing, HC, fuzzy logic controller, FLC

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

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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

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Authors: Shrikaant Kulkarni, Akshata Naik Nimbalkar

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In this worki a method protocol has been developed for the synthesis of innovative Co3O4 material by using a method of chemical synthesis followed by calcination. The effect of calcination temperature on the morphology, structure and catalytic performance on material in question is investigated by using characterization tools like scanning electron microscopy (SEM), X-ray diffraction (XRD) spectroscopy and electrochemical techniques. The SEM images reveal that the morphology of the Co3O4 material undergoes a change from the rod to a beadlike shape on calcination at temperature of 700 °C. The XRD image shows that although the morphology of synthesized Co3O4 material exhibits a cubic phase but it differs in crystallinity depending upon morphology. Similarly spherical beadlike Co3O4 material has exhibited better activity than its rodlike counterpart which is reflected from electrochemical findings. Further, its performance in terms of bifunctional nature and hlods a lot much of promise as a excellent electrode material in the next generation batteries and fuel cells.

Keywords: bifunctional, next generation material, Co3O4, XRD

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Authors: Arif Armagan Gozutok, Alper Kule, Burak Tos, Selman Demirel

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Wireless communication chain requires effective ways to keep throughput efficiency high while it suffers location-dependent, time-varying burst errors. Several techniques are developed in order to assure that the receiver recovers the transmitted information without errors. The most fundamental approaches are error checking and correction besides re-transmission of the non-acknowledged packets. In this paper, stop & wait (SAW) and chase combined (CC) hybrid automated repeat request (HARQ) protocols are compared and analyzed in terms of throughput and average delay for the usage of low earth orbit (LEO) mega-constellations case. Several assumptions and technological implementations are considered as well as usage of low-density parity check (LDPC) codes together with several constellation orbit configurations.

Keywords: HARQ, LEO, satellite constellation, throughput

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Authors: Nabil Mezhoud

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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

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Authors: Vladyslav Povoroznyuk, Oksana Ivanyk, Nataliia Dzerovych

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In the diagnostics of osteoporosis, the gold standard is considered to be bone mineral density; however, X-ray densitometry is not an accurate indicator of osteoporotic fracture risk under all circumstances. In this regard, the search for new methods that could determine the indicators not only of the mineral density, but of the bone tissue quality, is a logical step for diagnostic optimization. One of these methods is the evaluation of trabecular bone quality. The aim of this study was to examine the quality and mineral density of spine bone tissue, femoral neck, and body composition of women depending on the duration of the postmenopausal period, to determine the correlation of body fat with indicators of bone mineral density and quality. The study examined 179 women in premenopausal and postmenopausal periods. The patients were divided into the following groups: Women in the premenopausal period and women in the postmenopausal period at various stages (early, middle, late postmenopause). A general examination and study of the above parameters were conducted with General Electric X-ray densitometer. The results show that bone quality and mineral density probably deteriorate with advancing of postmenopausal period. Total fat and lean mass ratio is not likely to change with age. In the middle and late postmenopausal periods, the bone tissue mineral density of the spine and femoral neck increases along with total fat mass.

Keywords: osteoporosis, bone tissue mineral density, bone quality, fat mass, lean mass, postmenopausal osteoporosis

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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 solid collection 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

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Authors: Young Cheol Choi, Eun-Jin Moon, Sung-Won Yoo, Sang-Hwa Jung, In-Hwan Yang

Abstract:

Stainless steel slag (STS) is a by-product generated from the stainless steel refining process. The recycling of STS produced in Korea for construction applications is limited due to its poor hydraulic properties. On the other hand, STS has high carbonation reactivity to CO2 as it contains gamma-C2S content. This material is ideal for mineral carbonation which is one of the techniques proposed for carbon emission reduction. The objective of this study is to investigate the feasibility of developing a zero-cement STS binder activated by carbonation as alternative cementitious material. The quantitative analyses for CO2 uptake of STS powder and STS blended cement were investigated using thermogravimetric analysis (TGA), X-ray diffraction (XRD). In addition, the compressive strength and microstructure of STS pastes after CO2 curing were evaluated. Test results showed that STS can be activated by carbonation to gain a sufficient strength as alternative cementitious material.

Keywords: gamma-C2S, CO2 uptake, carbonation, stainless steel slag

Procedia PDF Downloads 460

Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

Abstract:

We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

Procedia PDF Downloads 108