Search results for: hybrid forecasting models

Authors: Marcel Heimar Ribeiro Utiyama, Fernanda Caveiro Correia, Dario Henrique Alliprandini

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The importance of the correct allocation of improvement programs is of growing interest in recent years. Due to their limited resources, companies must ensure that their financial resources are directed to the correct workstations in order to be the most effective and survive facing the strong competition. However, to our best knowledge, the literature about allocation of improvement programs does not analyze in depth this problem when the flow shop process has two capacity constrained resources. This is a research gap which is deeply studied in this work. The purpose of this work is to identify the best strategy to allocate improvement programs in a flow shop with two capacity constrained resources. Data were collected from a flow shop process with seven workstations in an industrial control and automation company, which process 13.690 units on average per month. The data were used to conduct a simulation with the System Dynamics-Factory Physics model. The main variables considered, due to their importance on lead time reduction, were the mean time between failures and the mean time to repair. The lead time reduction was the output measure of the simulations. Ten different strategies were created: (i) focused time to repair improvement, (ii) focused time between failures improvement, (iii) distributed time to repair improvement, (iv) distributed time between failures improvement, (v) focused time to repair and time between failures improvement, (vi) distributed time to repair and between failures improvement, (vii) hybrid time to repair improvement, (viii) hybrid time between failures improvements, (ix) time to repair improvement strategy towards the two capacity constrained resources, (x) time between failures improvement strategy towards the two capacity constrained resources. The ten strategies tested are variations of the three main strategies for improvement programs named focused, distributed and hybrid. Several comparisons among the effect of the ten strategies in lead time reduction were performed. The results indicated that for the flow shop analyzed, the focused strategies delivered the best results. When it is not possible to perform a large investment on the capacity constrained resources, companies should use hybrid approaches. An important contribution to the academy is the hybrid approach, which proposes a new way to direct the efforts of improvements. In addition, the study in a flow shop with two strong capacity constrained resources (more than 95% of utilization) is an important contribution to the literature. Another important contribution is the problem of allocation with two CCRs and the possibility of having floating capacity constrained resources. The results provided the best improvement strategies considering the different strategies of allocation of improvement programs and different positions of the capacity constrained resources. Finally, it is possible to state that both strategies, hybrid time to repair improvement and hybrid time between failures improvement, delivered best results compared to the respective distributed strategies. The main limitations of this study are mainly regarding the flow shop analyzed. Future work can further investigate different flow shop configurations like a varying number of workstations, different number of products or even different positions of the two capacity constrained resources.

Keywords: allocation of improvement programs, capacity constrained resource, hybrid strategy, lead time, mean time to repair, mean time between failures

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Authors: Tadeusz Nowicki, Radosław Pytlak, Robert Waszkowski, Jerzy Bertrandt, Anna Kłos

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This paper presents methods for formal modeling of activities in the area of sanitary inspectors outbreak of food-borne diseases. The models allow you to measure the characteristics of the activities of sanitary inspection and as a result allow improving the performance of sanitary services and thus food security.

Keywords: food-borne disease, epidemic, sanitary inspection, mathematical models

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Lourenco Camnahas, Eileen Willis, Greg Fisher, Jessie Gunson, Pascale Dettwiller, Charlene Thornton

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Stock-out of pharmaceuticals is a common issue at all level of health services in Timor-Leste, a small post-conflict country. This lead to the research questions: what are the current methods used to quantify pharmaceutical supplies; what factors contribute to the on-going pharmaceutical stock-out? The study examined factors that influence the pharmaceutical supply chain system. Methodology: Privett and Goncalvez dependency model has been adopted for the design of the qualitative interviews. The model examines pharmaceutical supply chain management at three management levels: management of individual pharmaceutical items, health facilities, and health systems. The interviews were conducted in order to collect information on inventory management, logistics management information system (LMIS) and the provision of pharmaceuticals. Andersen' behavioural model for healthcare utilization also informed the interview schedule, specifically factors linked to environment (healthcare system and external environment) and the population (enabling factors). Forty health professionals (bureaucrats, clinicians) and six senior officers from a United Nations Agency, a global multilateral agency and a local non-governmental organization were interviewed on their perceptions of factors (healthcare system/supply chain and wider environment) impacting on stock out. Additionally, policy documents for the entire healthcare system, along with population data were collected. Findings: An analysis using Pozzebon’s critical interpretation identified a range of difficulties within the system from poor coordination to failure to adhere to policy guidelines along with major difficulties with inventory management, quantification, forecasting, and budgetary constraints. Weak logistics management information system, lack of capacity in inventory management, monitoring and supervision are additional organizational factors that also contributed to the issue. There were various methods of quantification of pharmaceuticals applied in the government sector, and non-governmental organizations. Lack of reliable data is one of the major problems in the pharmaceutical provision. Global Fund has the best quantification methods fed by consumption data and malaria cases. There are other issues that worsen stock-out: political intervention, work ethic and basic infrastructure such as unreliable internet connectivity. Major issues impacting on pharmaceutical quantification have been identified. However, current data collection identified limitations within the Andersen model; specifically, a failure to take account of predictors in the healthcare system and the environment (culture/politics/social. The next step is to (a) compare models used by three non-governmental agencies with the government model; (b) to run the Andersen explanatory model for pharmaceutical expenditure for 2 to 5 drug items used by these three development partners in order to see how it correlates with the present model in terms of quantification and forecasting the needs; (c) to repeat objectives (a) and (b) using the government model; (d) to draw a conclusion about the strength.

Keywords: inventory management, pharmaceutical forecasting and quantification, pharmaceutical stock-out, pharmaceutical supply chain management

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Authors: Young Nam Jo, Moon Jeong Kang, Hong Hee Yoo

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Most human vibration models have been modeled as a multibody system consisting of some rigid bodies and spring-dampers. These models are developed for certain posture and conditions. So, the models cannot be used in vibration analysis in various posture and conditions. The purpose of this study is to develop a human vibration model that represent human vibration characteristics under various conditions by employing a musculoskeletal model. To do this, the human vibration model is developed based on biomechanical models. In addition, muscle models are employed instead of spring-dampers. Activations of muscles are controlled by PD controller to maintain body posture under vertical vibration is applied. Each gain value of the controller is obtained to minimize the difference of apparent mass and acceleration transmissibility between experim ent and analysis by using an optimization method.

Keywords: human vibration analysis, hill type muscle model, PD control, whole-body vibration

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Authors: Muhammad Muzamil Khan, Asadullah Madni, Nina Filipczek, Jiayi Pan, Nayab Tahir, Hassan Shah, Vladimir Torchilin

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Lipid-polymer hybrid nanoparticles (LPHNP) are delivery systems for controlled drug delivery at tumor sites. The superior biocompatible properties of lipid and structural advantages of polymer can be obtained via this system for controlled drug delivery. In the present study, cisplatin-loaded lipid-chitosan hybrid nanoparticles were formulated by the single step ionic gelation method based on ionic interaction of positively charged chitosan and negatively charged lipid. Formulations with various chitosan to lipid ratio were investigated to obtain the optimal particle size, encapsulation efficiency, and controlled release pattern. Transmission electron microscope and dynamic light scattering analysis demonstrated a size range of 181-245 nm and a zeta potential range of 20-30 mV. Compatibility among the components and the stability of formulation were demonstrated with FTIR analysis and thermal studies, respectively. The therapeutic efficacy and cellular interaction of cisplatin-loaded LPHNP were investigated using in vitro cell-based assays in A2780/ADR ovarian carcinoma cell line. Additionally, the cisplatin loaded LPHNP exhibited a low toxicity profile in rats. The in-vivo pharmacokinetics study also proved a controlled delivery of cisplatin with enhanced mean residual time and half-life. Our studies suggested that the cisplatin-loaded LPHNP being a promising platform for controlled delivery of cisplatin in cancer therapy.

Keywords: cisplatin, lipid-polymer hybrid nanoparticle, chitosan, in vitro cell line study

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Authors: MyungGu Yeo, JongHan Ha, Gi-Hoon Yang, JaeYoon Lee, SeungHyun Ahn, Hyeongjin Lee, HoJun Jeon, YongBok Kim, Minseong Kim, GeunHyung Kim

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Tissue engineering is a rapidly growing interdisciplinary research area that may provide options for treating damaged tissues and organs. As a promising technique for regenerating various tissues, this technology requires biomedical scaffolds, which serve as an artificial extracellular matrix (ECM) to support neotissue growth. Electrospun micro/nanofibers have been used widely in tissue engineering because of their high surface-area-to-volume ratio and structural similarity to extracellular matrix. However, low mechanical sustainability, low 3D shape-ability, and low cell infiltration have been major limitations to their use. In this work, we propose new hybrid scaffolds interlayered with cell-laden electrospun micro/nano fibers and poly(caprolactone) microstructures. Also, we applied various concentrations of alginate and electric field strengths to determine optimal conditions for the cell-electrospinning process. The combination of cell-laden bioink (2 ⅹ 10^5 osteoblast-like MG63 cells/mL, 2 wt% alginate, 2 wt% poly(ethylene oxide), and 0.7 wt% lecithin) and a 0.16 kV/mm electric field showed the highest cell viability and fiber formation in this process. Using these conditions and PCL microstructures, we achieved mechanically stable hybrid scaffolds. In addition, the cells embedded in the fibrous structure were viable and proliferated. We suggest that the cell-embedded hybrid scaffolds fabricated using the cell-electrospinning process may be useful for various soft- and hard-tissue regeneration applications.

Keywords: bioink, cell-laden scaffold, micro/nanofibers, poly(caprolactone)

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Authors: Saih Mohamed, Rouijaa Hicham, Ghammaz Abdelilah

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This paper presents circuit models to analyze the conducted susceptibility of multiconductor shielded cables in frequency domains using Branin’s method, which is referred to as the method of characteristics. These models, Which can be used directly in the time and frequency domains, take into account the presence of both the transfer impedance and admittance. The conducted susceptibility is studied by using an injection current on the cable shield as the source. Two examples are studied, a coaxial shielded cable and shielded cables with two parallel wires (i.e., twinax cables). This shield has an asymmetry (one slot on the side). Results obtained by these models are in good agreement with those obtained by other methods.

Keywords: circuit models, multiconductor shielded cables, Branin’s method, coaxial shielded cable, twinax cables

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: Sidique Gawusu, Xiaobing Zhang

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Turbulence models play a significant role in all computational fluid dynamics based modelling approaches. There is, however, no general turbulence model suitable for all flow scenarios. Therefore, a successful numerical modelling approach is only achievable if a more appropriate closure model is used. This paper evaluates different turbulence models in numerical modelling of oil-water flow within the Eulerian-Eulerian approach. A comparison among the obtained numerical results and published benchmark data showed reasonable agreement. The domain was meshed using structured mesh, and grid test was performed to ascertain grid independence. The evaluation of the models was made through analysis of velocity and pressure profiles across the domain. The models were tested for their suitability to accurately obtain a scalable and precise numerical experience. As a result, it is found that all the models except Standard-ω provide comparable results. The study also revealed new insights on flow in porous media, specifically oil reservoirs.

Keywords: turbulence modelling, simulation, multi-phase flows, water-flooding, heavy oil

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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

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

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Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

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Authors: Muhammad Jamil, Ning He, Aqib Mashood Khan, Munish Kumar Gupta

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Ti-6Al-4V has numerous applications in the medical, automobile, and aerospace industries due to corrosion resistivity, structural stability, and chemical inertness to most fluids at room temperature. These peculiar characteristics are beneficial for their application and present formidable challenges during machining. Machining of Ti-6Al-4V produces an elevated cutting temperature above 1000oC at dry conditions. This accelerates tool wear and reduces product quality. Therefore, there is always a need to employ sustainable/effective coolant/lubricant when machining such alloy. In this study, Finite Element Modeling (FEM) and experimental analysis when cutting Ti-6Al-4V under a distinctly developed dry ice mixed hybrid lubri-coolant are presented. This study aims to model the milling process of Ti-6Al-4V under a proposed novel hybrid lubri-coolant using different cutting speeds and feed per tooth DEFORM® software package was used to conduct the FEM and the numerical model was experimentally validated. A comparison of experimental and simulation results showed a maximum error of no more than 6% for all experimental conditions. In a nutshell, it can be said that the proposed model is effective in predicting the machining temperature precisely.

Keywords: friction coefficient, heat transfer, finite element modeling (FEM), milling Ti-6Al-4V

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Authors: Abebe Taye

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The interest in enhancing the performance of all-solid-state batteries featuring lithium metal anodes as a potential alternative to traditional lithium-ion batteries has prompted exploration into new avenues. A promising strategy involves transforming lithium-ion batteries into hybrid configurations by integrating lithium-ion and lithium-metal solid-state components. This study is focused on achieving stable lithium deposition and advancing the electrochemical capabilities of solid-state lithium hybrid batteries with anodes by incorporating mesocarbon microbeads (MCMBs) blended with silver nanoparticles. To achieve this, mesocarbon microbeads (MCMBs) blended with silver nanoparticles are coated on stainless-steel current collectors. These samples undergo a battery of analyses employing diverse techniques. Surface morphology is studied through scanning electron microscopy (SEM). The electrochemical behavior of the coated samples is evaluated in both half-cell and full-cell setups utilizing an argyrodite-type sulfide electrolyte. The stability of MCMBs in the electrolyte is assessed using electrochemical impedance spectroscopy (EIS). Additional insights into the composition are gleaned through X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and energy-dispersive X-ray spectroscopy (EDS). At an ultra-low N/P ratio of 0.26, stability is upheld for over 100 charge/discharge cycles in half-cells. When applied in a full-cell configuration, the hybrid anode preserves 60.1% of its capacity after 80 cycles at 0.3 C under a low N/P ratio of 0.45. In sharp contrast, the capacity retention of the cell using untreated MCMBs declines to 20.2% after a mere 60 cycles. The introduction of mesocarbon microbeads (MCMBs) combined with silver nanoparticles into the hybrid anode of solid-state lithium batteries substantially elevates their stability and electrochemical performance. This approach ensures consistent lithium deposition and removal, mitigating dendrite growth and the accumulation of inactive lithium. The findings from this investigation hold significant value in elevating the reversibility and energy density of lithium-ion batteries, thereby making noteworthy contributions to the advancement of more efficient energy storage systems.

Keywords: MCMB, lithium metal, hybrid anode, silver nanoparticle, cycling stability

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Authors: Nice Vasconcelos Coimbra, Fábio dos Santos Gonçalves, Marisa Nascimento, Ellen Cristine Giese

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The development of chemical routes for the recovery and separation of rare earth elements (REE) is seen as a priority and strategic action by several countries demanding these elements. Among the possibilities of alternative routes, the biosorption process has been evaluated in our laboratory. In this theme, the present work attempts to assess and fit the solution equilibrium data in Langmuir, Freundlich and DKR isothermal models, based on the biosorption results of the lanthanum and samarium elements by Bacillus subtilis immobilized on calcium alginate gel. It was observed that the preference of adsorption of REE by the immobilized biomass followed the order Sm (III)> La (III). It can be concluded that among the studied isotherms models, the Langmuir model presented better mathematical results than the Freundlich and DKR models.

Keywords: rare earth elements, biosorption, Bacillus subtilis, adsorption isotherm models

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Authors: Hicham Salhi

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This research project focuses on the numerical investigation of the mixed convection of Hybrid nanofluids in a round bottom flask commonly used in organic chemistry synthesis. The aim of this study is to improve the thermal properties of the reaction medium and enhance the rate of chemical reactions by using hybrid nanofluids. The flat bottom wall of the flask is maintained at a constant high temperature, while the top, left, and right walls are kept at a low temperature. The nanofluids used in this study contain suspended Cu and Al2O3 nanoparticles in pure water. The governing equations are solved numerically using the finite-volume approach and the Boussinesq approximation. The effects of the volume fraction of nanoparticles (φ) ranging from 0% to 5%, the Rayleigh number from 103 to 106, and the type of nanofluid (Cu and Al2O3) on the flow streamlines, isotherm distribution, and Nusselt number are examined in the simulation. The results indicate that the addition of Cu and Al2O3 nanoparticles increases the mean Nusselt number, which improves heat transfer and significantly alters the flow pattern. Moreover, the mean Nusselt number increases with increasing Rayleigh number and volume fraction, with Cu- Al2O3 hybrid nanofluid producing the best results. This research project focuses on the numerical investigation of the mixed convection of Hybrid nanofluids in a round bottom flask commonly used in organic chemistry synthesis. The aim of this study is to improve the thermal properties of the reaction medium and enhance the rate of chemical reactions by using hybrid nanofluids. The flat bottom wall of the flask is maintained at a constant high temperature, while the top, left, and right walls are kept at a low temperature. The nanofluids used in this study contain suspended Cu and Al2O3 nanoparticles in pure water. The governing equations are solved numerically using the finite-volume approach and the Boussinesq approximation. The effects of the volume fraction of nanoparticles (φ) ranging from 0% to 5%, the Rayleigh number from 103 to 106, and the type of nanofluid (Cu and Al2O3) on the flow streamlines, isotherm distribution, and Nusselt number are examined in the simulation. The results indicate that the addition of Cu and Al2O3 nanoparticles increases the mean Nusselt number, which improves heat transfer and significantly alters the flow pattern. Moreover, the mean Nusselt number increases with increasing Rayleigh number and volume fraction, with Cu- Al2O3 hybrid nanofluid producing the best results.

Keywords: bottom flask, mixed convection, hybrid nanofluids, numerical simulation

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Kaori Mori Want

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American society is a racially diverse society and there are children books that tell the importance of respecting racial differences. Through reading books, children understand the world around them little by little along with their direct interaction with the world in reality. They find role models in books, strive to be like role models, and grow confidence in who they are. Books thus nurture the mind of children. On the other hand, because of their small presence, children books for multiracial Asian American children are scarce. Multiracial Asian American population is increasing but they are still minority in number. The lack of children’s books for these children may deprive the opportunities of them to embrace their multiraciality positively because they cannot find someone like them in any books. Children books for multiracial Asian American are still not that many, but a few have been being published recently. This paper introduces children books for multiracial Asian American children, and examines how they address issues pertaining to these children, and how they could nurture their self-esteem. Many states of the US used to ban interracial marriages and interracial families and their children once were discriminated against in American society. There was even a theory called the hybrid degeneracy theory which claimed that mixed race children were inferior mentally and physically. In this negative social environment, some multiracial Asian American people report that they had trouble embracing their multiracial identity positively. Yet, children books for these children are full of positive messages. This paper will argue the importance of children books for the mental growth of multiracial Asian American children, and how these books can contribute to the development of multiculturalism in the US in general.

Keywords: critical mixed race studies in the US, hapa children literature, interracial marriage, multiraciality

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Authors: Mahmoud Aly, Mohamed Ismail, Mohamed Badereldin, Amro Mostafa

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Introduction: The models of soul houses were appeared in the prehistory, old kingdom, and middle kingdom period. They represented the imagination of the deceased about his house in the afterlife, some of these soul houses were two floors, and the study will examine five models of soul houses which were discovered near Saqqara site by an Egyptian mission. These models had been transferred to The Grand Egyptian Museum (GEM) to be ready to display at the new museum. We focus upon five models of soul houses (GEM Numbers, 1276,1280,1281,1282,8711) they related to the old kingdom period. These models were all made of pottery, the five models have oval shape and were decorated with relief. Methodology: The study will focus on the development of soul houses during the different periods in ancient Egypt and the kinds of offerings which will reflect the economic situation in the Egyptian society and kinds of oils which were famous in ancient Egypt. Conclusion: This research focuses on the function of soul house and the kind of offerings which were put in it, This study will be useful for the heritage and ancient civilizations, specially when we talk about opening new museums like The Grand Egyptian Museum, which will display a new collection of soul houses.

Keywords: archaeology study, grand egyptian museum, relief, soul houses

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Authors: Annie B. V., Anu A. G., Harikumar R.

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Microgrid (MG) is a self-governing miniature section of the power system. Nowadays the majority of loads and energy storage devices are inherently in DC form. This necessitates a greater scope of research in the various types of energy storage devices in DC microgrids. In a modern power system, DC microgrid is a manageable electric power system usually integrated with renewable energy sources (RESs) and DC loads with the help of power electronic converters. The stability of the DC microgrid mainly depends on the power imbalance. Power imbalance due to the presence of intermittent renewable energy resources (RERs) is supplied by energy storage devices. Battery, supercapacitor, flywheel, etc. are some of the commonly used energy storage devices. Owing to the high energy density provided by the batteries, this type of energy storage system is mainly utilized in all sorts of hybrid energy storage systems. To minimize the stability issues, a Supercapacitor (SC) is usually interfaced with the help of a bidirectional DC/DC converter. SC can exchange power during transient conditions due to its high power density. This paper analyses the stability issues of DC microgrids with hybrid energy storage systems (HESSs) arises from a reduction in SC operating voltage due to self-discharge. The stability of DC microgrid and power management is analyzed with different control strategies.

Keywords: DC microgrid, hybrid energy storage system (HESS), power management, small signal modeling, supercapacitor

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Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

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Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

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Authors: Nerella Srinivas

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This study investigates the role of intellectual property (IP) management in pharmaceutical development, focusing on tools, strategies, and business models for leveraging IP effectively. Using a mixed-methods approach, we conducted case studies and qualitative analyses of IP management frameworks within the pharmaceutical sector. Our methodology included a review of IP tools tailored for pharmaceutical applications, strategic IP models for maximizing competitive advantages, and best practices for organizational efficiency. Findings emphasize the importance of understanding IP law and adopting adaptive strategies, illustrating how IP management can drive industry growth.

Keywords: intellectual property management, pharmaceutical products, IP tools, IP strategies, best practices, business models, innovation

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Authors: Gwani M., Umar M. Kangiwa, Bello A. Umar, Gado A. Abubakar

Abstract:

The increasing demand for sustainable energy solutions has driven significant interest in the development of innovative designs of wind turbines. The horizontal axis wind turbine (HAWT) and the vertical axis wind turbine (VAWT) are the dominant type of wind turbine used for power generation. However, these turbines have their respective merits and demerits, which affect their performance. This study introduces a Hybrid Cross Axis Wind Turbine (HCAWT), which integrates the blades of both horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs) in a cross-axis configuration with a Savonius rotor to form a hybrid system. The HCAWT combines the self-starting capabilities of Savonius rotors with the high-efficiency characteristics of Darrieus rotors and HAWT, aiming to optimize performance across a range of wind conditions. The performance of the HCAWT was tested and evaluated against a cross-axis wind turbine (CAWT) and a conventional VAWT under similar experimental conditions. The study’s results indicate that the HCAWT outperformed both the CAWT and the conventional VAWT. The power coefficient (Cp) of the HCAWT increases by 83% and 132% compared to that of the CAWT and conventional VAWT, respectively. The findings show that the HCAWT offers better start-up performance and maintains higher efficiency at lower wind speeds compared to CAWT and conventional VAWT. The findings suggest that the HCAWT offers significant improvements in energy capture, particularly in turbulent wind conditions, and greater adaptability to changing wind conditions, making it a viable option for both urban and rural energy applications.

Keywords: renewable energy, hybrid, cross axis wind turbine, energy efficiency

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Authors: Maxim A. Kadatskiy, Konstantin V. Khishchenko

Abstract:

Iron alloys are widespread components in various types of structural materials which are exposed to intensive thermal and mechanical loads. Various quantum-statistical cell models with the approximation of self-consistent field can be used for the prediction of the behavior of these materials under extreme conditions. The application of these models is even more valid, the higher the temperature and the density of matter. Results of Hugoniot calculation for iron alloys in the framework of three quantum-statistical (the Thomas–Fermi, the Thomas–Fermi with quantum and exchange corrections and the Hartree–Fock–Slater) models are presented. Results of quantum-statistical calculations are compared with results from other reliable models and available experimental data. It is revealed a good agreement between results of calculation and experimental data for terra pascal pressures. Advantages and disadvantages of this approach are shown.

Keywords: alloy, Hugoniot, iron, terapascal pressure

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Authors: My Ali El Khakani

Abstract:

Single-wall Carbon nanotubes (SWCNTs) possess an unprecedented combination of unique properties that make them highly promising for suitable for a new generation of photovoltaic (PV) devices. Prior to discussing the integration of SWCNTs films into effective PV devices, we will briefly highlight our work on the synthesis of SWCNTs by means of the KrF pulsed laser deposition technique, their purification and transfer onto n-silicon substrates to form p-n junctions. Some of the structural and optoelectronic properties of SWCNTs relevant to PV applications will be emphasized. By varying the SWCNTs film density (µg/cm2), we were able to point out the existence of an optimum value that yields the highest photoconversion efficiency (PCE) of ~10%. Further control of the doping of the p-SWCNTs films, through their exposure to nitric acid vapors, along with the insertion of an optimized hole-extraction-layer in the p-SWCNTs/n-Si hybrid devices permitted to achieve a PCE value as high as 14.2%. Such a high PCE value demonstrates the full potential of these p-SWCNTs/n-Si devices for sunlight photoconversion. On the other hand, by examining both the optical transmission and electrical conductance of the SWCNTs’ films, we established a figure of merit (FOM) that was shown to correlate well with the PCE performance. Such a direct relationship between the FOM and the PCE can be used as a guide for further PCE enhancement of these novel p-SWCNTs/n-Si PV devices.

Keywords: carbon nanotubes (CNTs), CNTs-silicon hybrid devices, photoconversion, photovoltaic devices, pulsed laser deposition

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Authors: Ali Heidari

Abstract:

This paper presents the principles for improving flood mitigation operation in multipurpose dams and maximizing reservoir performance during flood occurrence with a focus on the real-time operation of gated spillways. The criteria of operation include the safety of dams during flood management, minimizing the downstream flood risk by decreasing the flood hazard and fulfilling water supply and other purposes of the dam operation in mid and long terms horizons. The parameters deemed to be important include flood inflow, outlet capacity restrictions, downstream flood inundation damages, economic revenue of dam operation, and environmental and sedimentation restrictions. A simulation model was used to determine the real-time release of the Dez dam located in the Dez rivers in southwest Iran, considering the gate regulation curves for the gated spillway. The results of the simulation model show that there is a possibility to improve the current procedures used in the real-time operation of the dams, particularly using gate regulation curves and early flood forecasting system results. The Dez dam operation data shows that in one of the best flood control records, % 17 of the total active volume and flood control pool of the reservoir have not been used in decreasing the downstream flood hazard despite the availability of a flood forecasting system.

Keywords: dam operation, flood control criteria, Dez dam, Iran

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

Abstract:

The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

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