Search results for: adaptive thermal comfort model

Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller

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Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.

Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach

Procedia PDF Downloads 372

Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

Procedia PDF Downloads 318

Authors: M. J. Kang, Y. N. Jo, H. H. Yoo

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Pendulum tests were used to identify a stretch reflex and diagnose spasticity. Some researches tried to make a mathematical model to simulate the motions. Thighs are subject to compressive forces due to gravity during a pendulum test. Therefore, it affects knee trajectories. However, the most studies on the pendulum tests did not consider that conditions. We used Kelvin-Voight model as compression model of skin and muscles. In this study, we investigated viscoelastic behaviors of skin and muscles using gelatin blocks from experiments of the vibration of the compliantly supported beam. Then we calculated a dynamic stiffness and loss factors from the experiment and estimated a damping coefficient of the model. We also did pendulum tests of human lower limbs to validate the stiffness and damping coefficient of a skin model. To simulate the pendulum motion, we derive equations of motion. We used stretch reflex activation model to estimate muscle forces induced by the stretch reflex. To validate the results, we compared the activation with electromyography signals during experiments. The compression behavior of skin and muscles in this study can be applied to analyze sitting posture as wee as developing surgical techniques.

Keywords: Kelvin-Voight model, pendulum test, skin and muscles under compression, stretch reflex

Procedia PDF Downloads 448

Authors: Isara Muangthai, Lin Sue Jane

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Electricity is vital to every country’s economy in the world. For Thailand, the electricity generation sector plays an important role in the economic system, and it is the largest source of CO2 emissions. The aim of this paper is to use the decomposition analysis to investigate the key factors contributing to the changes of CO2 emissions from the electricity sector. The decomposition analysis has been widely used to identify and assess the contributors to the changes in emission trends. Our study adopted the Divisia index decomposition to identify the key factors affecting the evolution of CO2 emissions from Thailand’s thermal power sector during 2000-2011. The change of CO2 emissions were decomposed into five factors, including: Emission coefficient, heat rate, fuel intensity, electricity intensity, and economic growth. Results have shown that CO2 emission in Thailand’s thermal power sector increased 29,173 thousand tons during 2000-2011. Economic growth was found to be the primary factor for increasing CO2 emissions, while the electricity intensity played a dominant role in decreasing CO2 emissions. The increasing effect of economic growth was up to 55,924 million tons of CO2 emissions because the growth and development of the economy relied on a large electricity supply. On the other hand, the shifting of fuel structure towards a lower-carbon content resulted in CO2 emission decline. Since the CO2 emissions released from Thailand’s electricity generation are rapidly increasing, the Thailand government will be required to implement a CO2 reduction plan in the future. In order to cope with the impact of CO2 emissions related to the power sector and to achieve sustainable development, this study suggests that Thailand’s government should focus on restructuring the fuel supply in power generation towards low carbon fuels by promoting the use of renewable energy for electricity, improving the efficiency of electricity use by reducing electricity transmission and the distribution of line losses, implementing energy conservation strategies by enhancing the purchase of energy-saving products, substituting the new power plant technology in the old power plants, promoting a shift of economic structure towards less energy-intensive services and orienting Thailand’s power industry towards low carbon electricity generation.

Keywords: co2 emission, decomposition analysis, electricity generation, energy consumption

Procedia PDF Downloads 485

Authors: Y. S. Yusoff, G. Streftaris, H. R Waters

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Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, Myocardial Infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a Myocardial Infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a Generalized Linear Model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.

Keywords: sudden deaths, myocardial infarction, stroke, ischemic heart disease

Procedia PDF Downloads 290

Authors: C. Castro-Egler, A. Durán-Escalante, A. García-González

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This paper presents a method to generate a finite element model of the human auditory inner ear system. The geometric model has been realized using 2D images from a virtual model of temporal bones. A point cloud has been gotten manually from those images to construct a whole mesh with hexahedral elements. The main difference with the predecessor models is the spiral shape of the cochlea with its three scales completely defined: scala tympani, scala media and scala vestibuli; which are separate by basilar membrane and Reissner membrane. To validate this model, numerical simulations have been realised with two models: an isolated inner ear and a whole model of human auditory system. Ideal conditions of displacement are applied over the oval window in the isolated Inner Ear model. The whole model is made up of the outer auditory channel, the tympani, the ossicular chain, and the inner ear. The boundary condition for the whole model is 1Pa over the auditory channel entrance. The numerical simulations by FEM have been done using a harmonic analysis with a frequency range between 100-10.000 Hz with an interval of 100Hz. The following results have been carried out: basilar membrane displacement; the scala media pressure according to the cochlea length and the transfer function of the middle ear normalized with the pressure in the tympanic membrane. The basilar membrane displacements and the pressure in the scala media make it possible to validate the response in frequency of the basilar membrane.

Keywords: finite elements method, human auditory system model, numerical analysis, 3D modelling cochlea

Procedia PDF Downloads 365

Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

Procedia PDF Downloads 485

Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

Procedia PDF Downloads 483

Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: torsional vibration, full-size model, scale model, scaling laws

Procedia PDF Downloads 398

Authors: Amir Shafiee Kisomi, Mehrdad Mofidi

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Nowadays, fuel cells as a promising alternative for power source have been widely studied owing to their security, high energy density, low operation temperatures, renewable capability and low environmental pollutant emission. The nanoparticles of core-shell type could be widely described in a combination of a shell (outer layer material) and a core (inner material), and their characteristics are greatly conditional on dimensions and composition of the core and shell. In addition, the change in the constituting materials or the ratio of core to the shell can create their special noble characteristics. In this study, a fast technique for the fabrication of a Pd-Co/G/GCE modified electrode is offered. Thermal decomposition reaction of cobalt (II) formate salt over the surface of graphene/glassy carbon electrode (G/GCE) is utilized for the synthesis of Co nanoparticles. The nanoparticles of Pd-Co decorated on the graphene are created based on the following method: (1) Thermal decomposition reaction of cobalt (II) formate salt and (2) the galvanic replacement process Co by Pd2+. The physical and electrochemical performances of the as-prepared Pd-Co/G electrocatalyst are studied by Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray Spectroscopy (EDS), Cyclic Voltammetry (CV), and Chronoamperometry (CHA). Galvanic replacement method is utilized as a facile and spontaneous approach for growth of Pd nanostructures. The Pd-Co/G is used as an anode catalyst for ethanol oxidation in alkaline media. The Pd-Co/G not only delivered much higher current density (262.3 mAcm-2) compared to the Pd/C (32.1 mAcm-2) catalyst, but also demonstrated a negative shift of the onset oxidation potential (-0.480 vs -0.460 mV) in the forward sweep. Moreover, the novel Pd-Co/G electrocatalyst represents large electrochemically active surface area (ECSA), lower apparent activation energy (Ea), higher levels of durability and poisoning tolerance compared to the Pd/C catalyst. The paper demonstrates that the catalytic activity and stability of Pd-Co/G electrocatalyst are higher than those of the Pd/C electrocatalyst toward ethanol oxidation in alkaline media.

Keywords: thermal decomposition, nanostructures, galvanic replacement, electrocatalyst, ethanol oxidation, alkaline media

Procedia PDF Downloads 155

Authors: Nicole Nazario Bayon, Prathima Prabhu Tumkur, Nithin Krisshna Gunasekaran, Krishnan Prabhakaran, Joseph C. Hall, Govindarajan T. Ramesh

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Titanium nitride (TiN) nanoparticles have sparked interest over the past decade due to their characteristics such as thermal stability, extreme hardness, low production cost, and similar optical properties to gold. In this study, TiN nanoparticles were synthesized via a thermal benzene route to obtain a black powder of nanoparticles. The final product was drop cast onto conductive carbon tape and sputter coated with gold/palladium at a thickness of 4 nm for characterization by field emission scanning electron microscopy (FE-SEM) with energy dispersive X-Ray spectroscopy (EDX) that revealed they were spherical. ImageJ software determined the average size of the TiN nanoparticles was 79 nm in diameter. EDX revealed the elements present in the sample and showed no impurities. Further characterization by X-ray diffraction (XRD) revealed characteristic peaks of cubic phase titanium nitride, and crystallite size was calculated to be 14 nm using the Debye-Scherrer method. Dynamic light scattering (DLS) analysis revealed the size and size distribution of the TiN nanoparticles, with average size being 154 nm. Zeta potential concluded the surface of the TiN nanoparticles is negatively charged. Biocompatibility studies using MTT(3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) assay showed TiN nanoparticles are not cytotoxic at low concentrations (2, 5, 10, 25, 50, 75 mcg/well), and cell viability began to decrease at a concentration of 100 mcg/well.

Keywords: biocompatibility, characterization, cytotoxicity, nanoparticles, synthesis, titanium nitride

Procedia PDF Downloads 180

Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

Procedia PDF Downloads 397

Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

Procedia PDF Downloads 230

Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

Procedia PDF Downloads 129

Authors: Klara Masnicova, Jiri Chaloupek

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Flammability plays an important role in applications such as thermal and acoustic insulation and other technical nonwoven textiles. The study was conducted in an attempt to investigate the flammability behavior of nonwoven textiles in relation to their structural and material characteristics, with emphasis given to the blending ratios of flammable and non-flammable fibers or fibers with reduced flammability. Nonwoven structures made of blends of viscose/oxidized polyacrylonitrile (VS/oxidized PAN fibers and polyethylene terephthalate/oxidized polyacrylonitrile (PET/oxidized PAN) fibers in several bulk densities are evaluated. The VS/oxidized PAN blend is model material. The flammability was studied using a cone calorimeter. Reaction to fire was observed using the small flame test method. Interestingly, the results show some of the blending ratios do not react to the heat in linear response to bulk density. This outcome can have a huge impact on future product development in fire safety and for the general understanding of flammability behavior of nonwovens made of staple fibers.

Keywords: bulk density, cone calorimetry, flammability, nonwoven textiles

Procedia PDF Downloads 309

Authors: Ashkan Forootan, Reza Rashedi

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Polyethylene has wide usage areas such as blow molding, pipe, film, cable insulation. However, regardless to its growing applications, it has some constraints such as the limited 70C operating temperature. Polyethylene thermo setting procedure whose molecules are knotted and 3D-molecular-network formed , is developed to conquer the above problem and to raise the applicable temperature of the polymer. This paper reports the cross-linking for two different molecular weight grades of LLDPE by adding 0.5, 1, and 2% of DCP (Dicumyl Peroxide). DCP was chosen for its prevalence among various cross-linking agents. Structural parameters such as molecular weight, melt flow index, comonomer, number of branches,etc. were obtained through the use of relative tests as Gel Permeation Chromatography and Fourier Transform Infra Red spectrometer. After calculating the percentage of gel content, properties of the pure and cross-linked samples were compared by thermal and mechanical analysis with DMTA and FTIR and the effects of cross-linking like viscous and elastic modulus were discussed by using various structural paprameters such as MFI, molecular weight, short chain branches, etc. Studies showed that cross-linked polymer, unlike the pure one, had a solid state with thermal mechanical properties in the range of 110 to 120C and this helped overcome the problem of using polyethylene in temperatures near the melting point.

Keywords: LLDPE, cross-link, structural parameters, DCP, DMTA, GPC

Procedia PDF Downloads 306

Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

Procedia PDF Downloads 404

Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

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Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear modeling, NNARX

Procedia PDF Downloads 382

Authors: Despina Vamvuka, Despina Pentari

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Forestry wastes are readily available in large quantities around the world. Based on European Green Deal for the deployment of renewable and decarbonized energy by 2050, as well as global energy crisis, energy recovery from such wastes reducing greenhouse gas emissions is very attractive. Gasification has superior environmental performance to combustion, producing a clean fuel gas utilized in internal combustion engines, gas turbines, solid oxide fuel cells, or for synthesis of liquid bio-fuels and value-added chemicals. In this work, pine needles, which are abundantly found in Mediterranean countries, were gasified by either steam or carbon dioxide via a two-step process to improve reactivity and eliminate tar, employing a fixed bed unit and a thermal analysis system. Solid, liquid and gaseous products from the whole process were characterized and their energy potential was determined. Thermal behaviour, reactivity, conversion and energy recovery were examined. The gasification process took place above 650°C. At 950°C conversion and energy recovery were 77% dry and 2 under a flow of steam and 85% dry and 2.9 under a flow of carbon dioxide, respectively. Organic matter was almost completely converted to syngas, the yield of which varied between 89% and 99%. The higher heating values of biochar, bio-oil and pyrolysis gas were 27.8 MJ/kg, 33.5 MJ/kg and 13.6 MJ/m3. Upon steam or carbon dioxide gasification, the higher heating value of syngas produced was 11.5 MJ/m3 and 12.7 MJ/m3, respectively.

Keywords: gasification, biomass, steam, carbon dioxide

Procedia PDF Downloads 99

Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Amir Mohammad Fathollahi Fard, Mostafa Hajiaghaei-Keshteli, Mohammad Mahdi Paydar

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With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.

Keywords: home health care supply chain, location-allocation-routing problem, imperialist competitive algorithm, optimization

Procedia PDF Downloads 398

Authors: Hassan Qandil

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Using a statistical algorithm incorporated in MATLAB, four types of non-imaging Fresnel lenses are designed; spot-flat, linear-flat, dome-shaped and semi-cylindrical-shaped. The optimization employs a statistical ray-tracing methodology of the incident light, mainly considering effects of chromatic aberration, varying focal lengths, solar inclination and azimuth angles, lens and receiver apertures, and the optimum number of prism grooves. While adopting an equal-groove-width assumption of the Poly-methyl-methacrylate (PMMA) prisms, the main target is to maximize the ray intensity on the receiver’s aperture and therefore achieving higher values of heat flux. The algorithm outputs prism angles and 2D sketches. 3D drawings are then generated via AutoCAD and linked to COMSOL Multiphysics software to simulate the lenses under solar ray conditions, which provides optical and thermal analysis at both the lens’ and the receiver’s apertures while setting conditions as per the Dallas-TX weather data. Once the lenses’ characterization is finalized, receivers are designed based on its optimized aperture size. Several cavity shapes; including triangular, arc-shaped and trapezoidal, are tested while coupled with a variety of receiver materials, working fluids, heat transfer mechanisms, and enclosure designs. A vacuum-reflective enclosure is also simulated for an enhanced thermal absorption efficiency. Each receiver type is simulated via COMSOL while coupled with the optimized lens. A lab-scale prototype for the optimum lens-receiver configuration is then fabricated for experimental evaluation. Application-based testing is also performed for the selected configuration, including that of a photovoltaic-thermal cogeneration system and solar furnace system. Finally, some future research work is pointed out, including the coupling of the collector-receiver system with an end-user power generator, and the use of a multi-layered genetic algorithm for comparative studies.

Keywords: COMSOL, concentrator, energy, fresnel, optics, renewable, solar

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Zhengming Wu

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NanoFrazor lithography systems were developed as a first true alternative or extension to standard mask-less nanolithography methods like electron beam lithography (EBL). In contrast to EBL they are based on thermal scanning probe lithography (t-SPL). Here a heatable ultra-sharp probe tip with an apex of a few nm is used for patterning and simultaneously inspecting complex nanostructures. The heat impact from the probe on a thermal responsive resist generates those high-resolution nanostructures. The patterning depth of each individual pixel can be controlled with better than 1 nm precision using an integrated in-situ metrology method. Furthermore, the inherent imaging capability of the Nanofrazor technology allows for markerless overlay, which has been achieved with sub-5 nm accuracy as well as it supports stitching layout sections together with < 10 nm error. Pattern transfer from such resist features below 10 nm resolution were demonstrated. The technology has proven its value as an enabler of new kinds of ultra-high resolution nanodevices as well as for improving the performance of existing device concepts. The application range for this new nanolithography technique is very broad spanning from ultra-high resolution 2D and 3D patterning to chemical and physical modification of matter at the nanoscale. Nanometer-precise markerless overlay and non-invasiveness to sensitive materials are among the key strengths of the technology. However, while patterning at below 10 nm resolution is achieved, significantly increasing the patterning speed at the expense of resolution is not feasible by using the heated tip alone. Towards this end, an integrated laser write head for direct laser sublimation (DLS) of the thermal resist has been introduced for significantly faster patterning of micrometer to millimeter-scale features. Remarkably, the areas patterned by the tip and the laser are seamlessly stitched together and both processes work on the very same resist material enabling a true mix-and-match process with no developing or any other processing steps in between. The presentation will include examples for (i) high-quality metal contacting of 2D materials, (ii) tuning photonic molecules, (iii) generating nanofluidic devices and (iv) generating spintronic circuits. Some of these applications have been enabled only due to the various unique capabilities of NanoFrazor lithography like the absence of damage from a charged particle beam.

Keywords: nanofabrication, grayscale lithography, 2D materials device, nano-optics, photonics, spintronic circuits

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

Procedia PDF Downloads 130

Authors: Jung–Min Yang

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Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: asynchronous sequential machines, corrective control, model matching, input/output control

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Authors: Hycham Aboutaleb, Bruno Monsuez

Abstract:

Current systems complexity has reached a degree that requires addressing conception and design issues while taking into account all the necessary aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponential growing effort, cost and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework and a environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and defines the refined functional as well as non functional requirements modeling tools needs to meet to be useful in model-based system engineering.

Keywords: system modeling, modeling language, modeling requirements, framework

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Authors: Faramarz Khosravi, Gokhan Izbirak

Abstract:

A weighted statistical stochastic based Analytical Hierarchy Process (AHP) model for modeling the potential barriers and enablers of sustainability for measuring and assessing the sustainability level is proposed. For context-dependent potential barriers and enablers, the proposed model takes the basis of the properties of the variables describing the sustainability functions and was developed into a realistic analytical model for the sustainable behavior of an organization. This thus serves as a means for measuring the sustainability of the organization. The main focus of this paper was the application of the AHP tool in a statistically-based model for measuring sustainability. Hence a strong weighted stochastic AHP based procedure was achieved. A case study scenario of a widely reported major Canadian electric utility was adopted to demonstrate the applicability of the developed model and comparatively examined its results with those of an equal-weighted model method. Variations in the sustainability of a company, as fluctuations, were figured out during the time. In the results obtained, sustainability index for successive years changed form 73.12%, 79.02%, 74.31%, 76.65%, 80.49%, 79.81%, 79.83% to more exact values 73.32%, 77.72%, 76.76%, 79.41%, 81.93%, 79.72%, and 80,45% according to priorities of factors that have found by expert views, respectively. By obtaining relatively necessary informative measurement indicators, the model can practically and effectively evaluate the sustainability extent of any organization and also to determine fluctuations in the organization over time.

Keywords: AHP, sustainability fluctuation, environmental indicators, performance measurement

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Authors: Devesh Motwani, Amey Kashyap

Abstract:

Interest in cost effective drilling has increased substantially in the past years. Economics associated with drilling fluids is needed to be considered seriously for lesser cost per foot in planning and drilling of a wellbore and the various environmental concerns imposed by international communities related with the constituents of the drilling fluid. Viscofier such as Guar Gum is a high molecular weight polysaccharide from Guar plants, is used to increase viscosity in water-based and brine-based drilling fluids thus enabling more efficient cleaning of the bore. Other applications of this Viscofier are to reduce fluid loss by giving a better colloidal solution, decrease fluid friction and so minimising power requirements and used in hydraulic fracturing to increase the recovery of oil and gas. Guar gum is also used as a surfactant, synthetic polymer and defoamer. This paper presents experimental results to verifying the properties of guar gum as a viscofier and filtrate retainer as well as observing the impact of different quantities of guar gum and Carboxymethyl cellulose (CMC) in a standard sample of water based bentonite mud solution. This is in attempt to make a drilling fluid which contains half of the quantity of drilling mud used and yet is equally viscous to the standardised mud sample. Thus we can see that mud economics will be greatly affected by this approach. However guar gum is thermally stable till 60-65°C thus limited to be used in drilling shallow wells and for a wider thermal range, suitable chrome free additives are required.

Keywords: economics, guargum, viscofier, CMC, thermal stability

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Authors: Mohammad Reza Oftadeh

Abstract:

The purpose of the article is to describe project objective structure (POS) concept that was developed on research activities and experiences about project management, Balanced Scorecard (BSC) and European Foundation Quality Management Excellence Model (EFQM Excellence Model). Furthermore, this paper tries to define a balanced, systematic, and integrated measurement approach to meet project objectives and project strategic goals based on a process-oriented model. In this paper, POS is suggested in order to measure project performance in the project life cycle. After using the POS model, the project manager can ensure in order to achieve the project objectives on the project charter. This concept can help project managers to implement integrated and balanced monitoring and control project work.

Keywords: project objectives, project performance management, PMBOK, key performance indicators, integration management

Procedia PDF Downloads 382