Search results for: asynchronous input

Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Abhinav Mane, Kedar Karvande, Shubham Patel, Abhayraj Lodha

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Gravity filters are one of the most commonly used, economically viable and moderately efficient water purification systems. Their efficiency is mainly based on the type of filter media installed and its location within the filter mass. Several researchers provide valuable input in decision of the type of filter media. However, the choice is mainly restricted to the chemical combinations of different substances. This makes it very much dependent on the factory made filter media, and no cheap alternatives could be found and used. This paper presents the use of disinfectants and filter medias either available naturally or could be prepared using natural resources in conventional mechanism of gravity filter. A small scale laboratory investigation was made with variation in filter media thickness and its location from the top surface of the filter. A rigid steel frame based custom fabricated test setup was used to facilitate placement of filter media at different height within the filter mass. Finely grinded sun dried Neem (Azadirachta indica) extracts and porous burnt clay pads were used as two distinct filter media and placed in isolation as well as in combination with each other. Ground water available in Marathwada region of Maharashtra, India which mainly consists of harmful materials like Arsenic, Chlorides, Iron, Magnesium and Manganese, etc. was treated in the filters fabricated in the present study. The evaluation was made mainly in terms of the input/output water quality assessment through laboratory tests. The present paper should give a cheap and eco-friendly solution to prepare gravity filter at the merit of household skills and availability.

Keywords: fliter media, gravity filters, natural disinfectants, porous clay pads

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Authors: Kusay Wheib, Alexandra Krvchenko

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Crop yields are influenced by many factors, including natural ones, such as soil and environmental characteristics of the agricultural land, as well as manmade ones, such as management applications. One of the factors that frequently affect crop yields in undulating Midwest landscapes is topography, which controls the movement of water and nutrients necessary for plant life. The main objective of this study is to examine how field topography influences performance of different management practices in undulated terrain of southwest Michigan. A total of 26 agricultural fields, ranging in size from 1.1 to 7.4 ha, from the Scale-Up at Kellogg Biological Station were included in the study. The two studied factors were crop species with three levels, i.e., corn (Zea mays L.) soybean (Glycine max L.), and wheat (Triticum aestivum L.), and management practice with three levels, i.e., conventional, low input, and organic managements. They were compared under three contrasting topographical settings, namely, summit (includes summits and shoulders), slope (includes backslopes), and depression (includes footslope and toeslope). Yield data of years 2007 through 2012 was processed, cleaned, and filtered, average yield then was calculated for each field, topographic setting, and year. Topography parameters, including terrain, slope, curvature, flow direction and wetness index were computed under ArcGIS environment for each topographic class of each field to seek their effects on yield. Results showed that topographical depressions produced greatest yields in most studied fields, while managements with chemical inputs, both low input and conventional, resulted in higher yields than the organic management.

Keywords: sustainable agriculture, precision agriculture, topography, yield

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Franklin N. Mabe, Samuel A. Donkoh, Seidu Al-Hassan

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In order to increase and bridge the differences in rice yield, many farmers have resorted to adopting Farmer Innovation Systems (FISs) and Improved Agricultural Technologies (IATs). This study econometrically analysed the impacts of adoption of FISs and IATs on rice yield using multinomial endogenous switching regression (MESR). Nine-hundred and seven (907) rice farmers from Guinea Savannah Zone (GSZ), Forest Savannah Transition Zone (FSTZ) and Coastal Savannah Zone (CSZ) were used for the study. The study used both primary and secondary data. FBO advice, rice farming experience and distance from farming communities to input markets increase farmers’ adoption of only FISs. Factors that increase farmers’ probability of adopting only IATs are access to extension advice, credit, improved seeds and contract farming. Farmers located in CSZ have higher probability of adopting only IATs than their counterparts living in other agro-ecological zones. Age and access to input subsidy increase the probability of jointly adopting FISs and IATs. FISs and IATs have heterogeneous impact on rice yield with adoption of only IATs having the highest impact followed by joint adoption of FISs and IATs. It is important for stakeholders in rice subsector to champion the provision of improved rice seeds, the intensification of agricultural extension services and contract farming concept. Researchers should endeavour to researched into FISs.

Keywords: farmer innovation systems, improved agricultural technologies, multinomial endogenous switching regression, treatment effect

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Authors: Taekyoon Park, Seokgoo Lee, Sungho Kim, Ung Lee, Jong Min Lee, Chonghun Han

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CO2 capture and storage/sequestration (CCS) is a key technology for addressing the global warming issue. This paper proposes an integrated model for the whole chain of CCS, from a power plant to a reservoir. The integrated model is further utilized to determine optimal operating conditions and study responses to various changes in input variables.

Keywords: CCS, caron dioxide, carbon capture and storage, simulation, optimization

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Authors: Elizabeth Crafton, Donald Ott, Teresa Cutright

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Harmful algal blooms (HABs), more notably cyanobacteria-dominated HABs, compromise water quality, jeopardize access to drinking water and are a risk to public health and safety. HABs are representative of ecosystem imbalance largely caused by environmental changes, such as eutrophication, that are associated with the globally expanding human population. Cyanobacteria-dominated HABs are anticipated to increase in frequency, magnitude, and are predicted to plague a larger geographical area as a result of climate change. The weather pattern is important as storm-driven, pulse-input of nutrients have been correlated to cyanobacteria-dominated HABs. The mobilization of aqueous and particulate nutrients and the response of the phytoplankton community is an important relationship in this complex phenomenon. This relationship is most apparent in high-impact areas of adequate sunlight, > 20ᵒC, excessive nutrients and quiescent water that corresponds to ideal growth of HABs. Typically the impact of particulate phosphorus is dismissed as an insignificant contribution; which is true for areas that are not considered high-impact. The objective of this study was to assess the impact of a simulated storm-driven, pulse-input of reactive phosphorus and the response of three different cyanobacteria assemblages (~5,000 cells/mL). The aqueous and particulate sources of phosphorus and changes in HAB were tracked weekly for 4 weeks. The first cyanobacteria composition consisted of Planktothrix sp., Microcystis sp., Aphanizomenon sp., and Anabaena sp., with 70% of the total population being non-diazotrophic and 30% being diazotrophic. The second was comprised of Anabaena sp., Planktothrix sp., and Microcystis sp., with 87% diazotrophic and 13% non-diazotrophic. The third composition has yet to be determined as these experiments are ongoing. Preliminary results suggest that both aqueous and particulate sources are contributors of total reactive phosphorus in high-impact areas. The results further highlight shifts in the cyanobacteria assemblage after the simulated pulse-input. In the controls, the reactors dosed with aqueous reactive phosphorus maintained a constant concentration for the duration of the experiment; whereas, the reactors that were dosed with aqueous reactive phosphorus and contained soil decreased from 1.73 mg/L to 0.25 mg/L of reactive phosphorus from time zero to 7 days; this was higher than the blank (0.11 mg/L). Suggesting a binding of aqueous reactive phosphorus to sediment, which is further supported by the positive correlation observed between total reactive phosphorus concentration and turbidity. The experiments are nearly completed and a full statistical analysis will be completed of the results prior to the conference.

Keywords: Anabaena, cyanobacteria, harmful algal blooms, Microcystis, phosphorous, response surface methodology

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Authors: A. Abbas, X. Tridon, J. Michelon

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In the electronic or in the photovoltaic industries, components are made from wafers which are stacks of thin film layers of a few nanometers to serval micrometers thickness. Early evaluation of the bounding quality between different layers of a wafer is one of the challenges of these industries to avoid dysfunction of their final products. Traditional pump-probe experiments, which have been developed in the 70’s, give a partial solution to this problematic but with a non-negligible drawback. In fact, on one hand, these setups can generate and detect ultra-high ultrasounds frequencies which can be used to evaluate the adhesion quality of wafer layers. But, on the other hand, because of the quiet long acquisition time they need to perform one measurement, these setups remain shut in punctual measurement to evaluate global sample quality. This last point can lead to bad interpretation of the sample quality parameters, especially in the case of inhomogeneous samples. Asynchronous Optical Sampling (ASOPS) systems can perform sample characterization with picosecond acoustics up to 106 times faster than traditional pump-probe setups. This last point allows picosecond ultrasonic to unlock the acoustic imaging field at the nanometric scale to detect inhomogeneities regarding sample mechanical properties. This fact will be illustrated by presenting an image of the measured acoustical reflection coefficients obtained by mapping, with an ASOPS setup, a 255nm thin-film tungsten layer deposited on a silicone substrate. Interpretation of the coefficient reflection in terms of bounding quality adhesion will also be exposed. Origin of zones which exhibit good and bad quality bounding will be discussed.

Keywords: adhesion, picosecond ultrasonics, pump-probe, thin film

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Authors: Irfan Ahmad Afip

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This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: Anupama Purohit

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The paper is a study on the inevitable cross-linguistic effect found in the early multilingual learners. The cross-linguistic behaviour like code-mixing, code-switching, foreign accent, literal translation, redundancy and syntactic manipulation effected due to other languages on the English language output of a non-native pre-school child are discussed here. A case study method is adopted in this paper to support the claim of the title. A simultaneously tetra lingual pre-school child’s (within 1;3 to 4;0) language behaviour is analysed here. The sample output data of the child is gathered from the diary entries maintained by her family, regular observations and video recordings done since her birth. She is getting the input of her mother tongue, Sambalpuri, from her grandparents only; Hindi, the local language from her play-school and the neighbourhood; English only from her mother and occasional visit of other family friends; Odia only during the reading of the Odia story book. The child is exposed to code-mixing of all the languages throughout her childhood. But code-mixing, literal translation, redundancy and duplication were absent in her initial stage of multilingual acquisition. As the child was more proficient in English in comparison to her other first languages and had never heard code-mixing in English language; it was expected from her input pattern of English (one parent, English language) that she would maintain purity in her use of English while talking to the English language interlocutor. But with gradual increase in the language proficiency in each of the languages of the child, her handling of the multiple codes becomes deft cross-linguistically. It can be deduced from the case study that after attaining certain milestone proficiency in each language, the child’s linguistic faculty can operate at a metalinguistic level. The functional use of each morpheme, their arrangement in words and in the sentences, the supra segmental features, lexical-semantic mapping, culture specific use of a language and the pragmatic skills converge to give a typical childlike multilingual output in an intelligible manner to the multilingual people (with the same set of languages in combination). The result is appealing because for expressing the same ideas which the child used to speak (may be with grammatically wrong expressions) in one language, gradually, she starts showing cross-linguistic effect in her expressions. So the paper pleads for the separatist view from the very beginning of the holophrastic phase (as the child expresses in addressee-specific language); but development of a metalinguistic ability that helps the child in communicating in a sophisticated way according to the linguistic status of the addressee is unique to the multilingual child. This metalinguistic ability is independent of the mode if input of a multilingual child.

Keywords: code-mixing, cross-linguistic effect, early multilingualism, literal translation

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Sh. Heidari, A. J. Andrews, A. Oberoi

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Electrochemical storage of hydrogen in activated carbon electrodes as part of a reversible fuel cell offers a potentially attractive option for storing surplus electrical energy from inherently variable solar and wind energy resources. Such a system – which we have called a proton flow battery – promises to have a roundtrip energy efficiency comparable to lithium ion batteries, while having higher gravimetric and volumetric energy densities. In this paper, a theoretical model is presented of the process of H+ ion (proton) conduction through an acid electrolyte into a highly porous activated carbon electrode where it is neutralised and absorbed on the inner surfaces of pores. A Butler-Volmer type equation relates the rate of adsorption to the potential difference between the activated carbon surface and the electrolyte. This model for the hydrogen storage electrode is then incorporated into a more general computer model based on MATLAB software of the entire electrochemical cell including the oxygen electrode. Hence a theoretical voltage-current curve is generated for given input parameters for a particular activated carbon electrode. It is shown that theoretical VI curves produced by the model can be fitted accurately to experimental data from an actual electrochemical cell with the same characteristics. By obtaining the best-fit values of input parameters, such as the exchange current density and charge transfer coefficient for the hydrogen adsorption reaction, an improved understanding of the adsorption reaction is obtained. This new model will assist in designing improved proton flow batteries for storing solar and wind energy.

Keywords: electrochemical hydrogen storage, proton flow battery, butler-volmer equation, activated carbon

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Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: S. Mogili, J. S. Kuang, N. Zhang

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Knee joints, the beam column connections found at the roof level of a moment resisting frame buildings, are inherently different from conventional interior and exterior beam column connections in the way that forces from adjoining members are transferred into joint and then resisted by the joint. A knee connection has two distinct load resisting mechanisms, each for closing and opening actions acting simultaneously under reversed cyclic loading. In spite of many distinct differences in the behaviour of shear resistance in knee joints, there are no special design provisions in the major design codes available across the world due to lack of in-depth research on the knee connections. To understand the relative importance of opening and closing actions in design, it is imperative to study knee joints under varying shear stresses, especially at higher opening-to-closing shear stress ratios. Three knee joint specimens, under different input shear stresses, were designed to produce a varying ratio of input opening to closing shear stresses. The design was carried out in such a way that the ratio of flexural strength of beams with consideration of axial forces in opening to closing actions are maintained at 0.5, 0.7, and 1.0, thereby resulting in the required variation of opening to closing joint shear stress ratios among the specimens. The behaviour of these specimens was then carefully studied in terms of closing and opening capacities, hysteretic behaviour, and envelope curves to understand the differences in joint performance based on which an attempt to suggest design guidelines for knee joints is made emphasizing the relative importance of opening and closing actions. Specimens with relatively higher opening stresses were observed to be more vulnerable under the action of seismic loading.

Keywords: Knee-joints, large-scale testing, opening and closing shear stresses, seismic performance

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Authors: M. Mashiur Rahman, Ulrik Birk Henriksen, Jesper Ahrenfeldt, Maria Puig Arnavat

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Using biomass gasification to make producer gas is one of the promising sustainable energy options available for small scale plant and rural applications for power and electricity. Tar content in producer gas is the main problem if it is used directly as a fuel. A low-tar biomass (LTB) gasifier of approximately 30 kW capacity has been developed to solve this. Moving bed gasifier with internal recirculation of pyrolysis gas has been the basic principle of the LTB gasifier. The gasifier focuses on the concept of mixing the pyrolysis gases with gasifying air and burning the mixture in separate combustion chamber. Five tests were carried out with the use of wood pellets and wood chips separately, with moisture content of 9-34%. The LTB gasifier offers excellent opportunities for handling extremely low-tar in the producer gas. The gasifiers producer gas had an extremely low tar content of 21.2 mg/Nm³ (avg.) and an average lower heating value (LHV) of 4.69 MJ/Nm³. Tar content found in different tests in the ranges of 10.6-29.8 mg/Nm³. This low tar content makes the producer gas suitable for direct use in internal combustion engine. Using mass and energy balances, the average gasifier capacity and cold gas efficiency (CGE) observed 23.1 kW and 82.7% for wood chips, and 33.1 kW and 60.5% for wood pellets, respectively. Average heat loss in term of higher heating value (HHV) observed 3.2% of thermal input for wood chips and 1% for wood pellets, where heat loss was found 1% of thermal input in term of enthalpy. Thus, the LTB gasifier performs better compared to typical gasifiers in term of heat loss. Equivalence ratio (ER) in the range of 0.29 to 0.41 gives better performance in terms of heating value and CGE. The specific gas production yields at the above ER range were in the range of 2.1-3.2 Nm³/kg. Heating value and CGE changes proportionally with the producer gas yield. The average gas compositions (H₂-19%, CO-19%, CO₂-10%, CH₄-0.7% and N₂-51%) obtained for wood chips are higher than the typical producer gas composition. Again, the temperature profile of the LTB gasifier observed relatively low temperature compared to typical moving bed gasifier. The average partial oxidation zone temperature of 970°C observed for wood chips. The use of separate combustor in the partial oxidation zone substantially lowers the bed temperature to 750°C. During the test, the engine was started and operated completely with the producer gas. The engine operated well on the produced gas, and no deposits were observed in the engine afterwards. Part of the producer gas flow was used for engine operation, and corresponding electrical power was found to be 1.5 kW continuously, and maximum power of 2.5 kW was also observed, while maximum generator capacity is 3 kW. A thermodynamic equilibrium model is good agreement with the experimental results and correctly predicts the equilibrium bed temperature, gas composition, LHV of the producer gas and ER with the experimental data, when the heat loss of 4% of the energy input is considered.

Keywords: biomass gasification, low-tar biomass gasifier, tar elimination, engine, deposits, condensate

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

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Authors: Walter Sebron, Hans Tschürtz, Peter Krebs

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The choice of applicable analysis methods in safety or systems engineering depends on the depth of knowledge about a system, and on the respective lifecycle phase. However, the analysis method chain still shows gaps as it should support system analysis during the lifecycle of a system from a rough concept in pre-project phase until end-of-life. This paper’s goal is to discuss an analysis method, the VISSE Shell Model Analysis (VISMA) method, which aims at closing the gap in the early system lifecycle phases, like the conceptual or pre-project phase, or the project start phase. It was originally developed to aid in the definition of the system boundary of electronic system parts, like e.g. a control unit for a pump motor. Furthermore, it can be also applied to non-electronic system parts. The VISMA method is a graphical sketch-like method that stratifies a system and its parts in inner and outer shells, like the layers of an onion. It analyses a system in a two-step approach, from the innermost to the outermost components followed by the reverse direction. To ensure a complete view of a system and its environment, the VISMA should be performed by (multifunctional) development teams. To introduce the method, a set of rules and guidelines has been defined in order to enable a proper shell build-up. In the first step, the innermost system, named system under consideration (SUC), is selected, which is the focus of the subsequent analysis. Then, its directly adjacent components, responsible for providing input to and receiving output from the SUC, are identified. These components are the content of the first shell around the SUC. Next, the input and output components to the components in the first shell are identified and form the second shell around the first one. Continuing this way, shell by shell is added with its respective parts until the border of the complete system (external border) is reached. Last, two external shells are added to complete the system view, the environment and the use case shell. This system view is also stored for future use. In the second step, the shells are examined in the reverse direction (outside to inside) in order to remove superfluous components or subsystems. Input chains to the SUC, as well as output chains from the SUC are described graphically via arrows, to highlight functional chains through the system. As a result, this method offers a clear and graphical description and overview of a system, its main parts and environment; however, the focus still remains on a specific SUC. It helps to identify the interfaces and interfacing components of the SUC, as well as important external interfaces of the overall system. It supports the identification of the first internal and external hazard causes and causal chains. Additionally, the method promotes a holistic picture and cross-functional understanding of a system, its contributing parts, internal relationships and possible dangers within a multidisciplinary development team.

Keywords: analysis methods, functional safety, hazard identification, system and safety engineering, system boundary definition, system safety

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Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Suhib A. Abu-Seini, Kyung-Doo Kim

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A heat loss model for ATLAS facility was introduced using SPACE code predefined correlations and various dialing factors. As all previous simulations were carried out using a heat loss free input; the facility was considered to be completely insulated and the core power was reduced by the experimentally measured values of heat loss to compensate to the account for the loss of heat, this study will consider heat loss throughout the simulation. The new heat loss model will be affecting SPACE code simulation as heat being leaked out of the system throughout a transient will alter many parameters corresponding to temperature and temperature difference. For that, a Station Blackout followed by a multiple Steam Generator Tube Rupture accident will be simulated using both the insulated system approach and the newly introduced heat loss input of the steady state. Major parameters such as system temperatures, pressure values, and flow rates to be put into comparison and various analysis will be suggested upon it as the experimental values will not be the reference to validate the expected outcome. This study will not only show the significance of heat loss consideration in the processes of prevention and mitigation of various incidents, design basis and beyond accidents as it will give a detailed behavior of ATLAS facility during both processes of steady state and major transient, but will also present a verification of how credible the data acquired of ATLAS are; since heat loss values for steady state were already mismatched between SPACE simulation results and ATLAS data acquiring system. Acknowledgement- This work was supported by the Korean institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea.

Keywords: ATLAS, heat loss, simulation, SPACE, station blackout, steam generator tube rupture, verification

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Authors: Jisoo Song

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Today’s mobile applications are communicating with servers more and more in order to access external services or information. Also, server-side code changes are more frequent than client-side code changes in a mobile application. The frequent changes lead to an increase in testing cost increase. To reduce costs, UI based test automation can be one of the solutions. It is a common automation technique in system-level testing. However, it can be unsuitable for mobile applications. When you automate tests based on UI elements for mobile applications, there are some limitations such as the overhead of script maintenance or the difficulty of finding invisible defects that UI elements cannot represent. To overcome these limitations, we present a new automation technique based on Rest API. You can automate system-level tests through test scripts that you write. These scripts call a series of Rest API in a user’s action sequence. This technique does not require testers to know the internal implementation details, only input and expected output of Rest API. You can easily modify test cases by modifying Rest API input values and also find problems that might not be evident from the UI level by validating output values. For example, when an application receives price information from a payment server and user cannot see it at UI level, Rest API based scripts can check whether price information is correct or not. More than 10 mobile applications at our company are being tested automatically based on Rest API scripts whenever application source code, mostly server source code, is built. We are finding defects right away by setting a script as a build job in CI server. The build job starts when application code builds are completed. This presentation will also include field cases from our company.

Keywords: case studies at SK Planet, introduction of rest API based test automation, limitations of UI based test automation

Procedia PDF Downloads 426

Authors: Norbert Tribl

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European contemporary scientific public opinion considers the concept of constitutional identity as a highlighted issue. Some scholars interpret the matter as the manifestation of a conflict of Europe. Nevertheless, constitutional identity is a bridge between the Member States and the EU rather than a river that will wash away the achievements of the integration. In accordance with the opinion of the author, the main problem of constitutional identity in Europe is the undetermined nature: the exact concept of constitutional identity has not been defined until now. However, this should be the first step to understand and use identity as a legal institution. Having regard to this undetermined nature, the legal-theoretical examination of constitutional identity is the main purpose of this study. The concept of constitutional identity appears in the Anglo-Saxon legal systems by a different approach than in the supranational system of European Integration. While the interpretation of legal institutions in conformity with the constitution is understood under it, the European concept is applied when possible conflicts arise between the legal system of the European supranational space and certain provisions of the national constitutions of the member states. The European concept of constitutional identity intends to offer input in determining the nature of the relationship between the constitutional provisions of the member states and the legal acts of the EU integration. In the EU system of multilevel constitutionalism, a long-standing central debate on integration surrounds the conflict between EU legal acts and the constitutional provisions of the member states. In spite of the fact that the Court of Justice of the European Union stated in Costa v. E.N.E.L. that the member states cannot refer to the provisions of their respective national constitutions against the integration. Based on the experience of more than 50 years since the above decision, and also in light of the Treaty of Lisbon, we now can clearly see that EU law has itself identified an obligation for the EU to protect the fundamental constitutional features of the Member States under Article 4 (2) of Treaty on European Union, by respecting the national identities of member states. In other words, the European concept intends to offer input for the determination of the nature of the relationship between the constitutional provisions of the member states and the legal acts of the EU integration.

Keywords: constitutional identity, EU law, European Integration, supranationalism

Procedia PDF Downloads 131

Authors: Xiaoqing Wang, Jianjian Zong, Li Li, Yanxing Zheng, Jinrong Tong, Mao Zhan

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With the rapid development of network and communication technology, a great deal of data has been generated in different domains of a network. These data show a trend of increasing scale and more complex structure. Therefore, an effective and flexible cross-domain data-sharing system is needed. The Cross-domain Data Sharing System(CDSS) in a net-centric environment is composed of three sub-systems. The data distribution sub-system provides data exchange service through publish-subscribe technology that supports asynchronism and multi-to-multi communication, which adapts to the needs of the dynamic and large-scale distributed computing environment. The access control sub-system adopts Attribute-Based Access Control(ABAC) technology to uniformly model various data attributes such as subject, object, permission and environment, which effectively monitors the activities of users accessing resources and ensures that legitimate users get effective access control rights within a legal time. The cross-domain access security negotiation subsystem automatically determines the access rights between different security domains in the process of interactive disclosure of digital certificates and access control policies through trust policy management and negotiation algorithms, which provides an effective means for cross-domain trust relationship establishment and access control in a distributed environment. The CDSS’s asynchronous,multi-to-multi and loosely-coupled communication features can adapt well to data exchange and sharing in dynamic, distributed and large-scale network environments. Next, we will give CDSS new features to support the mobile computing environment.

Keywords: data sharing, cross-domain, data exchange, publish-subscribe

Procedia PDF Downloads 109

Authors: A. Abdul-Ameer

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The equations governing the distance, pressure- volume flow relationships for the pipeline transportation of gaseous mixtures, are considered. A derivation based on differential calculus, for an element of this system model, is addressed. Solutions, yielding the input- output response following pressure changes, are reviewed. The technical problems associated with these analytical results are identified. Procedures resolving these difficulties providing thereby an attractive, simple, analysis route are outlined. Computed responses, validating thereby calculated predictions, are presented.

Keywords: pressure, distance, flow, dissipation, models

Procedia PDF Downloads 461

Authors: Barbara Bialecka, Zdzislaw Adamczyk, Magdalena Cempa

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In the work, the results of investigations into the hydrothermal zeolitization of fly ash from hard coal combustion in one of Polish Power Station have been presented. The chemical composition of the ash was determined by the method of X-ray fluorescence (XRF), whereas the phases of both fly ash and the products after synthesis were identified using microscopic observations, X-ray diffraction analysis (XRD) as well as electron scanning microscopy with measurements of the chemical compositions in micro areas (SEM/EDS). The synthesis was carried out with various concentrations of NaOH solution (3M, 4M and 6M) in the following conditions: synthesis temperature – 80ᵒC, synthesis time – 16 hours, volume of NaOH solution – 350ml, fly ash mass – 14g. The main chemical components of fly ash were SiO₂ and Al₂O₃, the contents of which reached 51.62 and 28.14%mas., respectively. The input ash contained mainly such phases as mullite, quarz, magnetite, and glass. The research results indicate that the phase composition of products after zeolitization was differentiated. The material after synthesis in 3M NaOH solution was found to contain mullite, quarz, magnetite, and Na-LSX zeolite. The products of synthesis in 4M NaOH solution were very similar to those in 3M solution (mullite, quarz, magnetite, Na-LSX zeolite), but they additionally contained hydrosodalite. The material after synthesis in 6M NaOH solution contains mullite, quarz, magnetite (similarly to synthesis in 3M and 4M NaOH solition) and additionally hydrosodalite. Therefore, the products of synthesis contain relic components from the fly ash input sample in the form of mullite, quarz, and magnetite, as well as new phases, which are Na-LSX zeolite and hydrosodalite. It should be noted that the products of synthesis in the case of 4M NaOH solution contained both new phases (Na-LSX zeolite and hydrosodalite), while the products from the extreme concentration of NaOH solutions (3M and 6M) contained only one of them. Observations in the scanning electron microscope revealed the new phases’ morphology. It was found that Na-LSX zeolite formed cubic crystals, whereas hydrosodalite formed characteristic aggregations. The results of investigations into the chemical composition in the micro area of phase grains in the products after synthesis reveal some dependencies, among others a characteristic increase in the content of sodium, related to the increased concentration of NaOH solution.

Keywords: Na-LSX, fly ash, hydrosodalite, zeolite

Procedia PDF Downloads 145

Authors: Rakelane A. Mendes, Sandro T. M. Goncalves, Raphaella L. R. Silva

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The concepts of energy harvesting and wireless energy transfer have been widely discussed in recent times. There are some ways to create autonomous systems for collecting ambient energy, such as solar, vibratory, thermal, electromagnetic, radiofrequency (RF), among others. In the case of the RF it is possible to collect up to 100 μW / cm². To collect and/or transfer energy in RF systems, a device called rectenna is used, which is defined by the junction of an antenna and a rectifier circuit. The rectenna presented in this work is resonant at the frequencies of 1.8 GHz and 2.45 GHz. Frequencies at 1.8 GHz band are e part of the GSM / LTE band. The GSM (Global System for Mobile Communication) is a frequency band of mobile telephony, it is also called second generation mobile networks (2G), it came to standardize mobile telephony in the world and was originally developed for voice traffic. LTE (Long Term Evolution) or fourth generation (4G) has emerged to meet the demand for wireless access to services such as Internet access, online games, VoIP and video conferencing. The 2.45 GHz frequency is part of the ISM (Instrumentation, Scientific and Medical) frequency band, this band is internationally reserved for industrial, scientific and medical development with no need for licensing, and its only restrictions are related to maximum power transfer and bandwidth, which must be kept within certain limits (in Brazil the bandwidth is 2.4 - 2.4835 GHz). The rectenna presented in this work was designed to present efficiency above 50% for an input power of -15 dBm. It is known that for wireless energy capture systems the signal power is very low and varies greatly, for this reason this ultra-low input power was chosen. The Rectenna was built using the low cost FR4 (Flame Resistant) substrate, the antenna selected is a microfita antenna, consisting of a Meandered dipole, and this one was optimized using the software CST Studio. This antenna has high efficiency, high gain and high directivity. Gain is the quality of an antenna in capturing more or less efficiently the signals transmitted by another antenna and/or station. Directivity is the quality that an antenna has to better capture energy in a certain direction. The rectifier circuit used has series topology and was optimized using Keysight's ADS software. The rectifier circuit is the most complex part of the rectenna, since it includes the diode, which is a non-linear component. The chosen diode is the Schottky diode SMS 7630, this presents low barrier voltage (between 135-240 mV) and a wider band compared to other types of diodes, and these attributes make it perfect for this type of application. In the rectifier circuit are also used inductor and capacitor, these are part of the input and output filters of the rectifier circuit. The inductor has the function of decreasing the dispersion effect on the efficiency of the rectifier circuit. The capacitor has the function of eliminating the AC component of the rectifier circuit and making the signal undulating.

Keywords: dipole antenna, double-band, high efficiency, rectenna

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Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.

Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh

Procedia PDF Downloads 210

Authors: Etienne Bonnaud, David Lindell

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Correlations between microstructure, deformation mechanisms, and mechanical properties in additively manufactured 316L steel components have been investigated. Mechanical properties in the vertical direction (building direction) and in the horizontal direction (in plane directions) are markedly different. Vertically built specimens show lower yield stress but higher elongation than their horizontally built counterparts. Microscopic observations by electron back scattered diffraction (EBSD) for both build orientations reveal a strong [110] fiber texture in the build direction but different grain morphologies. These microstructures are used as input in subsequent crystal plasticity numerical simulations to understand their influence on the deformation mechanisms and the mechanical properties. Mean field simulations using a visco plastic self consistent (VPSC) model were carried out first but did not give results consistent with the tensile test experiments. A more detailed full-field model had to be used based on the Visco Plastic Fast Fourier Transform (VPFTT) method. A more accurate microstructure description was then input to the simulation model, where thin vertical regions of smaller grains were also taken into account. It turned out that these small grain clusters were responsible for the discrepancies in yield stress and hardening. Texture and morphology have a strong effect on mechanical properties. The different mechanical behaviors between vertically and horizontally printed specimens could be explained by means of numerical full-field crystal plasticity simulations, and the presence of thin clusters of smaller grains was shown to play a central role in the deformation mechanisms.

Keywords: additive manufacturing, crystal plasticity, full-field simulations, mean-field simulations, texture

Procedia PDF Downloads 53

Authors: Ahmad Ammar, Umar Khan Khattak, Muhammad Majid

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Empirically based lumped hydrologic models have an extensive track record of use for various watershed managements and flood related studies. This study focuses on the impacts of LULC change for 10 year period on the discharge in watershed using lumped model HEC-HMS. The Indus above Tarbela region acts as a source of the main flood events in the middle and lower portions of Indus because of the amount of rainfall and topographic setting of the region. The discharge pattern of the region is influenced by the LULC associated with it. In this study the Landsat TM images were used to do LULC analysis of the watershed. Satellite daily precipitation TRMM data was used as input rainfall. The input variables for model building in HEC-HMS were then calculated based on the GIS data collected and pre-processed in HEC-GeoHMS. SCS-CN was used as transform model, SCS unit hydrograph method was used as loss model and Muskingum was used as routing model. For discharge simulation years 2000 and 2010 were taken. HEC-HMS was calibrated for the year 2000 and then validated for 2010.The performance of the model was assessed through calibration and validation process and resulted R2=0.92 during calibration and validation. Relative Bias for the years 2000 was -9% and for2010 was -14%. The result shows that in 10 years the impact of LULC change on discharge has been negligible in the study area overall. One reason is that, the proportion of built-up area in the watershed, which is the main causative factor of change in discharge, is less than 1% of the total area. However, locally, the impact of development was found significant in built up area of Mansehra city. The analysis was done on Mansehra city sub-watershed with an area of about 16 km2 and has more than 13% built up area in 2010. The results showed that with an increase of 40% built-up area in the city from 2000 to 2010 the discharge values increased about 33 percent, indicating the impact of LULC change on discharge value.

Keywords: LULC change, HEC-HMS, Indus Above Tarbela, SCS-CN

Procedia PDF Downloads 488