Search results for: high-performance cycle model application

Authors: Fethi Bouksila, Magnus Persson, Ronny Berndtsson, Akissa Bahri

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Under salinity conditions, we evaluate the performance of Hilhost (2000) model to predict pore electrical conductivity ECp from dielectric permittivity and bulk electrical conductivity (ECa) using Time and Frequency Domain Reflectometry sensors (TDR, FDR). Using FDR_WET sensor, RMSE of ECp was 4.15 dS m-1. By replacing the standard soil parameter (K0) in Hilhost model by K0-ECa relationship, the RMSE of ECp decreased to 0.68 dS m-1. WET sensor could give similar accuracy to estimate ECp than TDR if calibrated values of K0 were used instead of standard values in Hilhost model.

Keywords: hilhost model, soil salinity, time domain reflectometry, frequency domain reflectometry, dielectric methods

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Worku Dejene Bekele, András Marczika Csilla Sörös

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Silver nanoparticles are silver metal with a size of 1-100nm. The most common source of silver nanoparticles is inorganic salts. Nanoparticles can be ingested through our foods and constitute nanoparticles and silver ions, whether as an additive or by migrants and, in some cases, as a pollutant. Silver nanoparticles are the most widely applicable engineered nanomaterials, especially for antimicrobial function. Ag nanoparticles give different advantages in the case of food safety, quality, and overall acceptability; however, they affect the health of humans and animals, putting them at risk of health problems and environmental pollution. Silver nanoparticles have been used widely in food packaging technologies, especially in water treatments, meat and meat products, fruit, and many other food products. This is for bio-preservation from food products. The primary goal of this review is to determine the safety and health impact of Ag nanoparticles application in food packaging and analysis of the human organs more affected by this preservative technology, to assess the implications of a nanoparticle on food safety, to determine the effects of nanoparticles on consumers health and to determine the impact of nanotechnology on product acceptability. But currently, much research has demonstrated that there is cause to believe that silver nanoparticles may have toxicological effects on biological organs and systems. The silver nanoparticles affect DNA expression, gastrointestinal barriers, lungs, and other breathing organs illness. Silver particles and molecules are very toxic. During its application in food packaging, food industries used the thinnest particle. This particle can potentially affect the gastrointestinal tracts-it suffers from mucus production, DNA, lungs, and other breezing organs. This review is targeted to demonstrate the knowledge gap that industrials use in the application of silver nanoparticles in food packaging and preservation and its health effects on the consumer.

Keywords: food preservatives, health impact, nanoparticle, silver nanoparticle

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Authors: Hung-Chi Chang

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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

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Authors: Z. A. Al Marhoon, H. S. Al Ramis, C. Teodoriu

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Well-integrity is one of the major elements considered for drilling geothermal, oil, and gas wells. Well-integrity is minimizing the risk of unplanned fluid flow in the well bore throughout the well lifetime. Well integrity is maximized by applying technical concepts along with practical practices and strategic planning. These practices are usually governed by standardization and regulation entities. Practices during well construction can affect the integrity of the seal at the time of abandonment. On the other hand, achieving a perfect barrier system is impracticable due to the needed cost. This results in a needed balance between regulations requirements and practical applications. The guidelines are only effective when they are attainable in practical applications. Various governmental regulations and international standards have different guidelines on what constitutes high-quality isolation from unwanted flow. Each regulating or standardization body differ in requirements based on the abandonment objective. Some regulation account more for the environmental impact, water table contamination, and possible leaks. Other regulation might lean towards driving more economical benefits while achieving an acceptable isolation criteria. The research methodology used in this topic is derived from a literature review method combined with a compare and contrast analysis. The literature review on various zonal isolation regulations and standards has been conducted. A review includes guidelines from NORSOK (Norwegian governing entity), BSEE (USA offshore governing entity), API (American Petroleum Institute) combined with ISO (International Standardization Organization). The compare and contrast analysis is conducted by assessing the objective of each abandonment regulations and standardization. The current state of well barrier regulation is in balancing action. From one side of this balance, the environmental impact and complete zonal isolation is considered. The other side of the scale is practical application and associated cost. Some standards provide a fair amount of details concerning technical requirements and are often flexible with the needed associated cost. These guidelines cover environmental impact with laws that prevent major or disastrous environmental effects of improper sealing of wells. Usually these regulations are concerned with the near future of sealing rather than long-term. Consequently, applying these guidelines become more feasible from a cost point of view to the required plugging entities. On the other hand, other regulation have well integrity procedures and regulations that lean toward more restrictions environmentally with an increased associated cost requirements. The environmental impact is detailed and covered with its entirety, including medium to small environmental impact in barrier installing operations. Clear and precise attention to long-term leakage prevention is present in these regulations. The result of the compare and contrast analysis of the literature showed that there are various objectives that might tip the scale from one side of the balance (cost) to the other (sealing quality) especially in reference to zonal isolation. Furthermore, investing in initial well construction is a crucial part of ensuring safe final well abandonment. The safety and the cost saving at the end of the well life cycle is dependent upon a well-constructed isolation systems at the beginning of the life cycle. Long term studies on zonal isolation using various hydraulic or mechanical materials need to take place to further assess permanently abandoned wells to achieve the desired balance. Well drilling and isolation techniques will be more effective when they are operationally feasible and have reasonable associated cost to aid the local economy.

Keywords: plug and abandon, P&A regulation, P&A standards, international guidelines, gap analysis

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Authors: Hanik Park, Kyungsook Jeon, Suchul Shin, Youngchul Park

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The air vent head prevents the inflow of seawater into the cargo holds when it is used for the ballast tank on heavy weather. In this study, the flow characteristics and the grid size were created by the application of Computational Fluid Dynamics by taking into the consideration of comparison of test results. Then, the accuracy of the analysis was verified by comparing with experimental results. Based on this analysis, accurate turbulence model and grid size can be selected. Thus, the design characteristic of air vent head for bulk carrier contributes the reliability based on the research results.

Keywords: bulk carrier, FEM, SST, vent

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Authors: Watchareeporn Chaimongkol

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In this paper, we compare the statistical measures accuracy of composite forecasting model to estimate automobile customer demand in Thailand. A modified simple exponential smoothing and autoregressive integrate moving average (ARIMA) forecasting model is built to estimate customer demand of passenger cars, instead of using information of historical sales data. Our model takes into account special characteristic of the Thai automobile market such as sales promotion, advertising and publicity, petrol price, and interest rate for loan. We evaluate our forecasting model by comparing forecasts with actual data using six accuracy measurements, mean absolute percentage error (MAPE), geometric mean absolute error (GMAE), symmetric mean absolute percentage error (sMAPE), mean absolute scaled error (MASE), median relative absolute error (MdRAE), and geometric mean relative absolute error (GMRAE).

Keywords: composite forecasting, simple exponential smoothing model, autoregressive integrate moving average model selection, accuracy measurements

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Authors: R. Yuan, S. Sivasankaran, N. Dutta, K. Ebrahimi

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This paper investigates the software capability and computer-aided engineering (CAE) method of modelling transient heat transfer process occurred in the vehicle underhood region during vehicle thermal soak phase. The heat retention from the soak period will be beneficial to the cold start with reduced friction loss for the second 14°C worldwide harmonized light-duty vehicle test procedure (WLTP) cycle, therefore provides benefits on both CO₂ emission reduction and fuel economy. When vehicle undergoes soak stage, the airflow and the associated convective heat transfer around and inside the engine bay is driven by the buoyancy effect. This effect along with thermal radiation and conduction are the key factors to the thermal simulation of the engine bay to obtain the accurate fluids and metal temperature cool-down trajectories and to predict the temperatures at the end of the soak period. Method development has been investigated in this study on a light-duty passenger vehicle using coupled aerodynamic-heat transfer thermal transient modelling method for the full vehicle under 9 hours of thermal soak. The 3D underhood flow dynamics were solved inherently transient by the Lattice-Boltzmann Method (LBM) method using the PowerFlow software. This was further coupled with heat transfer modelling using the PowerTHERM software provided by Exa Corporation. The particle-based LBM method was capable of accurately handling extremely complicated transient flow behavior on complex surface geometries. The detailed thermal modelling, including heat conduction, radiation, and buoyancy-driven heat convection, were integrated solved by PowerTHERM. The 9 hours cool-down period was simulated and compared with the vehicle testing data of the key fluid (coolant, oil) and metal temperatures. The developed CAE method was able to predict the cool-down behaviour of the key fluids and components in agreement with the experimental data and also visualised the air leakage paths and thermal retention around the engine bay. The cool-down trajectories of the key components obtained for the 9 hours thermal soak period provide vital information and a basis for the further development of reduced-order modelling studies in future work. This allows a fast-running model to be developed and be further imbedded with the holistic study of vehicle energy modelling and thermal management. It is also found that the buoyancy effect plays an important part at the first stage of the 9 hours soak and the flow development during this stage is vital to accurately predict the heat transfer coefficients for the heat retention modelling. The developed method has demonstrated the software integration for simulating buoyancy-driven heat transfer in a vehicle underhood region during thermal soak with satisfying accuracy and efficient computing time. The CAE method developed will allow integration of the design of engine encapsulations for improving fuel consumption and reducing CO₂ emissions in a timely and robust manner, aiding the development of low-carbon transport technologies.

Keywords: ATCT/WLTC driving cycle, buoyancy-driven heat transfer, CAE method, heat retention, underhood modeling, vehicle thermal soak

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini

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This study evaluated the uncertainties involved in the solar radiation projections generated by the Brazilian Earth System Model (BESM) of the Weather and Climate Prediction Center (CPTEC) belonging to Coupled Model Intercomparison Phase 5 (CMIP5), with the aim of identifying efficiency in the projections for solar radiation of said model and in this way establish the viability of its use. Two different scenarios elaborated by Intergovernmental Panel on Climate Change (IPCC) were evaluated: RCP 4.5 (with more optimistic contour conditions) and 8.5 (with more pessimistic initial conditions). The method used to verify the accuracy of the present model was the Nash coefficient and the Statistical bias, as it better represents these atmospheric patterns. The BESM showed a tendency to overestimate the data ​​of solar radiation projections in most regions of the state of Rio Grande do Sul and through the validation methods adopted by this study, BESM did not present a satisfactory accuracy.

Keywords: climate changes, projections, solar radiation, uncertainty

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Authors: Aijaz A. Shaikh, Richard Glavee-Geo, Heikki Karjaluoto

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Adoption of Information Systems (IS) is receiving increasing attention such that its implications have been closely monitored and studied by the IS management community, industry and professional gatekeepers. Building on previous research regarding the adoption of technology, this paper develops and validates an integrated model of the adoption of mobile banking. The model originates from the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB). This paper intends to offer a preliminary scrutiny of the antecedents of the adoption of mobile banking services in the context of a developing country. Data was collected from Pakistan. The findings showed that an integrated TAM and TPB model greatly explains the adoption intention of mobile banking; and perceived behavioural control and its antecedents play a significant role in predicting adoption Theoretical and managerial implications of findings are presented and discussed.

Keywords: developing country, mobile banking service adoption, technology acceptance model, theory of planned behavior

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Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

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Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

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Authors: Giuliano Raimondo, Jörg Wangemann, Peer Drechsel

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In systems development involving Fuel Cells generators, it is important to have from an early stage of the project a dynamic model for the electrical behavior of the stack to be shared between involved development parties. It allows independent and early design and tests of fuel cell related power electronic. This paper presents an empirical Fuel Cell system model derived from characterization tests on a real system. Moreover, it is illustrated how the obtained model is used to build and validate a real-time Fuel Cell system emulator which is used for aerospace electrical integration testing activities.

Keywords: fuel cell, modelling, real time emulation, testing

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Authors: Nabi Ullah

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The single-step solvothermal method is used to prepare Cu/CuSe as an electrocatalyst for methanol electro-oxidation reaction (MOR). 1,3-butane-diol is selected as a reaction medium, whose viscosity and complex formation with Cu(II) ions dictate the catalyst morphology. The catalyst has a macroporous structure, which is composed of nanoballs with a high purity, crystallinity, and uniform morphology. The electrocatalyst is excellent for MOR, as it delivers a current density of 37.28 mA/mg at a potential of 0.6 V (vs Ag/AgCl) in the electrolyte of 1 M KOH and 0.75 M methanol at a 50 mV/s scan rate under conditions of cyclic voltammetry. The catalyst also shows good stability for 3600 s with negligible charge transfer resistance and a high electrochemical active surface area (ECSA) value of 0.100 mF/cm².

Keywords: MOR, copper selenide, electocatalyst, energy application

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Authors: V. Rangarajan, Priyanka Kaushal

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This study investigates the effectiveness of a typical Earth Air Heat Exchanger (EATHE) for energy efficient space cooling in an urban environment typified by space and soil-related constraints that preclude an optimal design. It involves the development of a three-dimensional numerical transient model that is validated by measurements at a live site in India. It is found that the model accurately predicts the soil temperatures at various depths as well as the EATHE outlet air temperature. The study shows that such an EATHE, even when designed under constraints, does provide effective space cooling especially during the hot months of the year.

Keywords: earth air heat exchanger (EATHE), India, MATLAB, model, simulation

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Seyed Sobhan Alvani, Mohammad Gohari

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By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.

Keywords: traffic index, population growth rate, cities wideness, artificial neural network

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Authors: Ennios Eros Giogos, Nefeli Katsarou, Giota Mantziorou, Elena Panou, Nikolaos Kourniatis, Socratis Giannoudis

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In the context of the postgraduate course Productive Design, Department of Interior Architecture of the University of West Attica in Athens, under the guidance of Professors Nikolaos Koyrniatis and Socratis Giannoudis, kinetic mechanisms with parametric models were examined for their further application in the design of objects. In the first phase, the students studied a motion mechanism that they chose from daily experience and then analyzed its geometric structure in relation to the geometric transformations that exist. In the second phase, the students tried to design it through a parametric model in Grasshopper3d for Rhino algorithmic processor and plan the design of its application in an everyday object. For the project presented, our team began by studying the movement of living beings, specifically the snake. By studying the snake and the role that the environment has in its movement, four basic typologies were recognized: serpentine, concertina, sidewinding and rectilinear locomotion, as well as its ability to perform spiral formations. Most typologies are characterized by ripples, a series of sinusoidal curves. For the application of the snake movement in a polymorphic space divider, the use of a coil-type joint was studied. In the Grasshopper program, the simulation of the desired motion for the polymorphic surface was tested by applying a coil on a sinusoidal curve and a spiral curve. It was important throughout the process that the points corresponding to the nodes of the real object remain constant in number, as well as the distances between them and the elasticity of the construction had to be achieved through a modular movement of the coil and not some elastic element (material) at the nodes. Using mesh (repeating coil), the whole construction is transformed into a supporting body and combines functionality with aesthetics. The set of elements functions as a vertical spatial network, where each element participates in its coherence and stability. Depending on the positions of the elements in terms of the level of support, different perspectives are created in terms of the visual perception of the adjacent space. For the implementation of the model on the scale (1:3), (0.50m.x2.00m.), the load-bearing structure that was studied has aluminum rods for the basic pillars Φ6mm and Φ 2.50 mm, for the secondary columns. Filling elements and nodes are of similar material and were made of MDF surfaces. During the design process, four trapezoidal patterns were picketed, which function as filling elements, while in order to support their assembly, a different engraving facet was done. The nodes have holes that can be pierced by the rods, while their connection point with the patterns has a half-carved recess. The patterns have a corresponding recess. The nodes are of two different types depending on the column that passes through them. The patterns and knots were designed to be cut and engraved using a Laser Cutter and attached to the knots using glue. The parameters participate in the design as mechanisms that generate complex forms and structures through the repetition of constantly changing versions of the parts that compose the object.

Keywords: polymorphic, locomotion, sinusoidal curves, parametric

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Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a mathematical tool, is used for modeling in different areas of computer sciences, biological networks, chemical systems and many other disciplines. A Petri net model of a given system is created by the graphical representation that describes the properties and behavior of the system. While looking for the behavior of any system, 1-safe Petri nets are of particular interest to many in the application part. Boolean Petri nets correspond to those class in 1- safe Petri nets that generate all the binary n-vectors in their reachability analysis. We study the class by changing different parameters like the token counts in the places and how the structure of the tree changes in the reachability analysis. We discuss here an extended class of Boolean Petri nets that generates n-ary trees in their reachability-based analysis.

Keywords: marking vector, n-vector, petri nets, reachability

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Authors: Mehmet Savsar

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This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

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Authors: Suleiman Aliyu

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Integrating IoT applications with Fog systems presents challenges in optimization due to diverse environments and conflicting objectives. This study explores achieving Pareto optimal deployments for Fog-based IoT systems to address growing QoS demands. We introduce Pareto optimality to balance competing performance metrics. Using the FogTorch optimization framework, we propose a hybrid approach (Backtracking search with branch and bound) for scalable IoT deployments. Our research highlights the advantages of Pareto optimality over single-objective methods and emphasizes the role of FogTorch in this context. Initial results show improvements in IoT deployment cost in Fog systems, promoting resource-efficient strategies.

Keywords: pareto optimality, fog application deployment, resource allocation, internet of things

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Authors: Jianming Cai

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Exposure to ionizing radiation causes severe damage to human body and an safe and effective radioprotector is urgently required for alleviating radiation damage. In 2008, flagellin, an agonist of TLR5, was found to exert radioprotective effects on radiation injury through activating NF-kB signaling pathway. From then, the radioprotective effects of TLR ligands has shed new lights on radiation protection. CpG-ODN is an unmethylated oligonucleotide which activates TLR9 signaling pathway. In this study, we demonstrated that CpG-ODN has therapeutic effects on radiation injuries induced by γ ray and 12C6+ heavy ion particles. Our data showed that CpG-ODN increased the survival rate of mice after whole body irradiation and increased the number of leukocytes as well as the bone marrow cells. CpG-ODN also alleviated radiation damage on intestinal crypt through regulating apoptosis signaling pathway including bcl2, bax, and caspase 3 etc. By using a radiation-induced pulmonary fibrosis model, we found that CpG-ODN could alleviate structural damage, within 20 week after whole–thorax 15Gy irradiation. In this model, Th1/Th2 imbalance induced by irradiation was also reversed by CpG-ODN. We also found that TGFβ-Smad signaling pathway was regulated by CpG-ODN, which accounts for the therapeutic effects of CpG-ODN in radiation-induced pulmonary injury. On another hand, for high LET radiation protection, we investigated protective effects of CpG-ODN against 12C6+ heavy ion irradiation and found that after CpG-ODN treatment, the apoptosis and cell cycle arrest induced by 12C6+ irradiation was reduced. CpG-ODN also reduced the expression of Bax and caspase 3, while increased the level of bcl2. Then we detected the effect of CpG-ODN on heavy ion induced immune dysfunction. Our data showed that CpG-ODN increased the survival rate of mice and also the leukocytes after 12C6+ irradiation. Besides, the structural damage of immune organ such as thymus and spleen was also alleviated by CpG-ODN treatment. In conclusion, we found that TLR9 ligand, CpG-ODN reduced radiation injuries in response to γ ray and 12C6+ heavy ion irradiation. On one hand, CpG-ODN inhibited the activation of apoptosis induced by radiation through regulating bcl2, bax and caspase 3. On another hand, through activating TLR9, CpG-ODN recruit MyD88-IRAK-TRAF6 complex, activating TAK1, IRF5 and NF-kB pathway, and thus alleviates radiation damage. This study provides novel insights into protection and therapy of radiation damages.

Keywords: TLR9, CpG-ODN, radiation injury, high LET radiation

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Authors: Joon-Hoon Park

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In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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Authors: L. D. Upegui, Isabel Alvarez-Solorza, Karina Garduno-Ulloa, Maren Boecker

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Introduction: The increasing prevalence rate of resistant and multiresistant bacterial strains to antibiotics is a threat to public health and requires a rapid multifunctional answer. Individuals that are affected by resistant strains present a higher morbidity and mortality than individuals that are infected with the same species of bacteria but with sensitive strains. There have been identified risk factors that are related to the misuse and overuse of antibiotics, like socio-demographic characteristics and psychological aspects of the individuals that have not been explored objectively due to a lack of valid and reliable instruments for their measurement. Objective: To validate a questionnaire for the evaluation of the levels of knowledge related to the use of antibiotics in a Mexican population. Materials and Methods: Analytical cross-sectional observational study. The questionnaire consists of 12 items to evaluated knowledge (1=no, 2=not sure, 3=yes) regarding the use of antibiotics, with higher scores corresponding to a higher level of knowledge. Data are collected in a sample of students. Data collection is still ongoing. In this abstract preliminary results of 30 respondents are reported which were collected during pilot-testing. The validation of the instrument was done using the Rasch model. Fit to the Rasch model was tested checking overall fit to the model, unidimensionality, local independence and evaluating the presence of Differential Item Functioning (DIF) by age and gender. The software Rumm2030 and the SPSS were used for the analyses. Results: The participants of the pilot-testing presented an average age of 32 years ± 12.6 and 53% were women. The preliminary results indicated that the items showed good fit to the Rasch model (chi-squared=12.8 p=0.3795). Unidimensionality (number of significant t-tests of 3%) could be proven, the items were locally independent, and no DIF was observed. Knowledge was the smallest regarding statements on the role of antibiotics in treating infections, e.g., most of the respondents did not know that antibiotics would not work against viral infections (70%) and that they could also cause side effects (87%). The knowledge score ranged from 0 to 100 points with a transformed measurement (mean of knowledge 27.1 ± 4.8). Conclusions: The instrument showed good psychometric proprieties. The low scores of knowledge about antibiotics suggest that misinterpretations on the use of these medicaments were prevalent, which could influence the production of antibiotic resistance. The application of this questionnaire will allow the objective identification of 'Hight risk groups', which will be the target population for future educational campaigns, to reduce the knowledge gaps on the general population as an effort against antibiotic resistance.

Keywords: antibiotics, knowledge, misuse, overuse, questionnaire, Rasch model, validation

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Authors: Chelali Mohammed

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In the context of the application of the competency-based approach in the system educational Algeria, the price of physical education and sport must privilege the acquisition of learning approaches and especially the approach science, which from problem situations, research and develops him information processing and application of knowledge and know-how in new situations in the words of ‘JOHN DEWEY’ ‘learning by practice’. And to achieve these goals and make teaching more EPS motivating, consistent and concrete, it is appropriate to perform a pedagogical approach freed from the constraints and open to creativity and student-centered in the light of the competency approach adopted in the formal curriculum. This approach is not unusual, but we think it is a highly professional nature requires the competence of the teacher.

Keywords: approach competencies, physical, education, teachers

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Authors: Jana Gutierez Chvalkovska, Michal Mejstrik, Matej Urban

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There are pending discussions over the mapping of country export potential in order to refocus export strategy of firms and its evidence-based promotion by the Export Credit Agencies (ECAs) and other permitted vehicles of governments. In this paper we develop our version of an applied model that offers “stepwise” elimination of unattractive markets. We modify and calibrate the model for the particular features of the Czech Republic and specific pilot cases where we apply an individual approach to each sector.

Keywords: export strategy, modeling export, calibration, export promotion

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Authors: Enrique Barbieri

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The basic disease-spread model described by three states denoting the susceptible (S), infectious (I), and removed (recovered and deceased) (R) sub-groups of the total population N, or SIR model, has been considered. Heuristic mitigating action profiles of the pharmaceutical and non-pharmaceutical types may be developed in a control design setting for the purpose of reducing the transmission rate or improving the recovery rate parameters in the model. Even though the transmission and recovery rates are not control inputs in the traditional sense, a linear observer and feedback controller can be tuned to generate an asymptotic estimate of the transmission rate for a linearized, discrete-time version of the SIR model. Then, a set of mitigating actions is suggested to steer the basic reproduction number toward unity, in which case the disease does not spread, and the infected population state does not suffer from multiple waves. The special case of piecewise constant transmission rate is described and applied to a seventh-order SEIQRDP model, which segments the population into four additional states. The offline simulations in discrete time may be used to produce heuristic policies implemented by public health and government organizations.

Keywords: control of SIR, observer, SEIQRDP, disease spread

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Authors: Anastasis D. Petrou

Abstract:

Innovation and strategy discussions do highlight open innovation as a new paradigm in business. Yet, a number of stumbling blocks in the form of closed innovation principles weaved into the fabric of a traditional business model stand in the way of the new paradigm’s momentum to increase value in various business contexts. The paper argues that businesses considering an engagement with the open innovation paradigm would need to take steps to improve their multiplicative, absorptive and relational capabilities, respectively. The needed improvements would amount to a business model evolutionary transformation and eventually bring about a paradigm overhaul in business. The transformation is worth staging over time to ensure that open innovation is developed across interconnected and partnered areas of strategic importance. This article develops an open innovation strategy (OIS) capabilities model, and employs examples from different industries to briefly discuss OIS’s potential to augment business value in a number of suggested areas for future research.

Keywords: close innovation, open innovation paradigm, open innovation strategy (OIS) paradigm, OIS capabilities model, multiplicative capability, absorptive capability, relational capability

Procedia PDF Downloads 520

Authors: Robert Prohaska, Arnaud Konan, Kenneth Kelly, Adam Ragatz, Adam Duran

Abstract:

In an effort to evaluate the in-use performance of electrified Power Take-off (PTO) usage on bucket utility trucks operating under real-world conditions, data from 20 medium- and heavy-duty vehicles operating in California, USA were collected, compiled, and analyzed by the National Renewable Energy Laboratory's (NREL) Fleet Test and Evaluation team. In this paper, duty-cycle statistical analyses of class 5, medium-duty quick response trucks and class 8, heavy-duty material handler trucks are performed to examine and characterize vehicle dynamics trends and relationships based on collected in-use field data. With more than 100,000 kilometers of driving data collected over 880+ operating days, researchers have developed a robust methodology for identifying PTO operation from in-field vehicle data. Researchers apply this unique methodology to evaluate the performance and utilization of the conventional and electric PTO systems. Researchers also created custom representative drive-cycles for each vehicle configuration and performed modeling and simulation activities to evaluate the potential fuel and emissions savings for hybridization of the tractive driveline on these vehicles. The results of these analyses statistically and objectively define the vehicle dynamic and kinematic requirements for each vehicle configuration as well as show the potential for further system optimization through driveline hybridization. Results are presented in both graphical and tabular formats illustrating a number of key relationships between parameters observed within the data set that relates specifically to medium- and heavy-duty utility vehicles operating under real-world conditions.

Keywords: drive cycle, heavy-duty (HD), hybrid, medium-duty (MD), PTO, utility

Procedia PDF Downloads 396

Authors: Chang, Ya-Ju, Hsieh, Pei-Hsin, Wu, Jui-Chuang, Chen-Yang, Yui Whei

Abstract:

A mesoporous silica material was prepared to apply to the lateral-flow immunochromatography for detecting a model biosample. The probe antibody is immobilized on the silica surface as the test line to capture its affinity antigen, which laterally flows through the chromatography strips. The antigen is labeled with nano-gold particles, such that the detection can be visually read out from the test line without instrument aids. The result reveals that the mesoporous material provides a vast area for immobilizing the detection probes. Biosening surfaces corresponding with a positive proportion of detection signals is obtained with the biosample loading.

Keywords: mesoporous silica, immunochromatography, lateral-flow strips, biosensors, nano-gold particles

Procedia PDF Downloads 609