Search results for: choice experiments (CE)

Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Osama Saber

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Cyanate is one such anion which is produced during protein poisoning in the body and has been studied extensively in the field of biochemistry because of its toxicity. The present work aims at confinement and storage of cyanate in the nano scale. It was achieved through the intercalation of cyanate anions into nanolayerd structures of Ni-Al LDH. In addition, the effect of aging time on the intercalation of cyanate was clarified using X-ray diffraction and scanning electron microscopy. Furthermore, the effect of cations on the affinity towards the intercalation of cyanate anions inside LDH structure was studied by replacement of tetra-valent cations Ti4+ instead of the tri-vallent cations Al3+ during the preparation of LDH structure. X-ray diffraction patterns of the Ni-Ti LDH showed that the interlayer spacing was 0.73 nm. This spacing was smaller than that of Ni-Al LDH suggesting that the interlayered anions into Ni-Ti LDH are different from those into Ni-Al LDH. Thermal analyses (TG, DTG, and DTA) and Infra-red spectra revealed the presence of only cyanate anions into Ni-Ti LDH while, in the case of Ni-Al LDH, both cyanate and carbonate anions were observed. SEM images showed plate-like morphology for both Ni-Ti and Ni-Al LDHs although the shapes of their plates are not similar. Our results suggested that the LDH structures containing titanium cations have higher affinity for cyanate anions than those containing aluminum cations. Therefore, this choice for cyanate in the interlayered spacing widens the applicability to study the effect of the confinement on the toxicity of cyanate by bio researchers.

Keywords: nanolayered structures, Ni-Al LDH, Ni-Ti LDH, intercalation of cyanate anions, urea hydrolysis

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Authors: Ragy Raafat Gaber Attaalla

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PIP: This review, based on 2 large-scale studies, discusses the pharmacology and physiology of oral steroid contraceptives (OCs). The pharmacological distinction between synthetic and naturally occurring steroids centers on changes in biological activity dependent on compound formulation and an individual's metabolism. OC mechanism of action is explained as the main prevention of ovulation by interference with gonadotropin-releasing hormone. Since some 52 metabolic alterations have been reported in OC users, these phenomena are dealt with in 3 categories: 1) effects on the primary target organs of the female reproductive tract (ovary, myometrium, endometrium, cervix, vagina, breasts, and hypothalamus), 2) general metabolic effects (serum proteins, carbohydrate metabolism, lipid metabolism, water and electrolyte metabolism, body weight, tryptophan metabolism, and vitamins and minerals), and 3) effects on other organ systems (liver, central nervous system, skin, genitourinary, gastrointestinal tract, eye, immune phenomena, and effect on subsequent fertility). The choice of the proper OC formulation and use of OCs by adolescents are discussed. Assessment of OC safety, contraindications, and patient monitoring are provided.

Keywords: steroid oral contraceptives, ovulation, female reproductive tract, metabolic effects

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: K. -H. Yang

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In the past, the quay crane operations have been well studied. There were a certain number of scheduling algorithms for quay crane operations, but without considering some nuisance factors that might disrupt the quay crane operations. For example, bad grapples make a crane unable to load or unload containers or a sudden strong breeze stops operations temporarily. Although these disruptive conditions randomly occur, they influence the efficiency of quay crane operations. The disruption is not considered in the operational procedures nor is evaluated in advance for its impacts. This study applies simulation and optimization approaches to develop structures of pre-analysis and post-analysis for the Quay Crane Scheduling Problem to deal with disruptive scenarios for quay crane operation. Numerical experiments are used for demonstrations for the validity of the developed approaches.

Keywords: disruptive quay crane scheduling, pre-analysis, post-analysis, disruption

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Authors: M. Sandeep Kumar, Vasu Velagapudi, A. Venugopal

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When machining is carried out on a workpiece, residual stresses are induced in the workpiece due to nonuniform thermal and mechanical loads. These stresses play a vital role in the surface integrity of the final product or the output. Inconel 718 is commonly used in critical structural components of aircraft engines due to its properties at high temperatures. Therefore it is important to keep down the stresses induced due to machining. This can be achieved through proper lubricating conditions. In this work, experiments were carried out to check the influence of the developed nanofluid as cutting fluids on residual stresses developed during the course of machining. The results of MQL/Nanofluids were compared with MQL/Vegetable oil and dry machining lubricating condition. Results indicate the reduction in residual stress with the use of MQL/Nanofluid.

Keywords: nanofluids, MQL, residual stress, Inconel-718

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Authors: Lenka Morávková, Zuzana Sedláková, Jiří Vejražka, Věra Jandová, Pavel Izák

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The need to minimize the costs of biogas upgrading leads to a continuous search for new and more effective membrane materials. The improvement of biogas combustion efficiency is connected with polar gases removal from a feed stream. One of the possibilities is the use of water–swollen polyamide layer of thin film composite reverse osmosis membrane for simultaneous carbon dioxide and hydrogen sulphide removal. Transport properties and basic characteristics of a thin film composite membrane were compared in the term of appropriate water-swollen membrane choice for biogas upgrading. SEM analysis showed that the surface of the best performing composites changed significantly upon swelling by water. The surface changes were found to be a proof that the selective skin polyamide layer was swollen well. Further, the presence of a sufficient number of associative centers, namely amido groups, inside the upper layer of the hydrophilic thin composite membrane can play an important role in the polar gas separation from a non-polar gas. The next key factor is a high porosity of the membrane support.

Keywords: biogas upgrading, carbon dioxide separation, hydrogen sulphide separation, water-swollen membrane

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Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

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Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

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Authors: Yani Shi, Jiaqi Yan

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A new product is important for companies to extend consumers and manifest competitiveness. New product often involves new features that consumers might not be familiar with while it may also have a competitive advantage to attract consumers compared to established products. However, although most online retailers employ recommendation agents (RA) to influence consumers’ product choice decision, recommended new products are not accepted and chosen as expected. We argue that it might also be caused by providing a new product recommendation in the wrong way at the wrong time. This study seeks to discuss how new product evaluations sourced from third parties could be employed in RAs as evidence of the superiority for the new product and how the new product recommendation could be provided to a consumer at the right time so that it can be accepted and finally chosen during the consumer’s decision-making process. A 2*2 controlled laboratory experiment was conducted to understand the selection of new product recommendation sources and recommendation timing. Human subjects were randomly assigned to one of the four treatments to minimize the effects of individual differences on the results. Participants were told to make purchase choices from our product categories. We find that a new product recommended right after a similar existing product and with the source of the expert review will be more likely to be accepted. Based on this study, both theoretical and practical contributions are provided regarding new product recommendation.

Keywords: new product recommendation, recommendation timing, recommendation source, recommendation agents

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Authors: Opeyemi Elujulo, Aderonke Okoya, Kehinde Awokoya

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Molecularly imprinted polymers (MIP) for the adsorption of pyridine (PYD) was obtained from PYD (the template), styrene (the functional monomer), divinyl benzene (the crosslinker), benzoyl peroxide (the initiator), and water (the porogen). When the template was removed by solvent extraction, imprinted binding sites were left in the polymer material that are capable of selectively rebinding the target molecule. The material was characterized by Fourier transform infrared spectroscopy and differential scanning calorimetry. Batch adsorption experiments were performed to study the adsorption of the material in terms of adsorption kinetics, isotherms, and thermodynamic parameters. The results showed that the imprinted polymer exhibited higher affinity for PYD compared to non-imprinted polymer (NIP).

Keywords: molecularly imprinted polymer, bulk polymerization, environmental pollutant, adsorption

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Authors: Raúl Pereda García, Julio Manuel de Luis Ruiz, Elena Castillo López, Rubén Pérez Álvarez, Felipe Piña García

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New technologies for the capture of point clouds have experienced a great advance in recent years. In this way, its use has been extended in geomatics, providing measurement solutions that have been popularized without there being, many times, a detailed study of its accuracy. This research focuses on the study of the viability of topographic works with drones incorporating different sensors sensitive to the visible spectrum. The fundamentals have been applied to a road, located in Cantabria (Spain), where a platform extension and the reform of a riprap were being constructed. A total of six flights were made during two months, all of them with GPS as part of the photogrammetric process, and the results were contrasted with those measured with total station. The obtained results show that the choice of the camera and the planning of the flight have an important impact on the accuracy. In fact, the representations with a level of detail corresponding to 1/1000 scale are admissible, depending on the existing vegetation, and obtaining better results in the area of the riprap. This set of techniques is, therefore, suitable for the control of earthworks in road works but with certain limitations which are exposed in this paper.

Keywords: drone, earth movement control, global position system, surveying technology.

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Danish Laidin, Peter Gostomski, Aaron Marshall, Carlo Carere

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Groundwater contamination of nitrate (NO3-) is becoming more prevalent in regions of intensive and extensive agricultural activities. Household nitrate removal involves using ion exchange membranes and reverse osmosis (RO) systems, whereas industrial nitrate removal may use organic carbon substrates (e.g. methanol) for heterotrophic microbial denitrification. However, these approaches both require high capital investment and operating costs. In this study, denitrification was demonstrated using bio-electrochemical systems (BESs) inoculated from sediments and microbial enrichment cultures. The BES reactors were operated continuously as microbial electrolytic cells (MECs) with a poised potential of -0.7V and -1.1V vs Ag/AgCl. Three parallel MECs were inoculated using hydrogen-driven denitrifying enrichments, stream sediments, and biofilm harvested from a denitrifying biotrickling filter, respectively. These reactors were continuously operated for over a year as various operating conditions were investigated to determine the optimal conditions for electroactive denitrification. The mass loading rate of nitrate was varied between 10 – 70 mg NO3-/d, and the maximum observed nitrate removal rate was 22 mg NO3- /(cm2∙d) with a current of 2.1 mA. For volumetric load experiments, the dilution rate of 1 mM NO3- feed was varied between 0.01 – 0.1 hr-1 to achieve a nitrate loading rate similar to the mass loading rate experiments. Under these conditions, the maximum rate of denitrification observed was 15.8 mg NO3- /(cm2∙d) with a current of 1.7mA. Hydrogen (H2) was supplied intermittently to investigate the hydrogenotrophic potential of the denitrifying biofilm electrodes. H2 supplementation at 0.1 mL/min resulted in an increase of nitrate removal from 0.3 mg NO3- /(cm2∙d) to 3.4 mg NO3- /(cm2∙d) in the hydrogenotrophically subcultured reactor but had no impact on the reactors which exhibited direct electron transfer properties. Results from this study depict the denitrification performance of the immobilized biofilm electrodes, either by direct electron transfer or hydrogen-driven denitrification, and the contribution of the planktonic cells present in the growth medium. Other results will include the microbial community analysis via 16s rDNA amplicon sequencing, varying the effect of poising cathodic potential from 0.7V to 1.3V vs Ag/AgCl, investigating the potential of using in-situ electrochemically produced hydrogen for autotrophic denitrification and adjusting the conductivity of the feed solution to mimic groundwater conditions. These findings highlight the overall performance of sediment inoculated MECs in removing nitrate and will be used for the future development of sustainable solutions for the treatment of nitrate polluted groundwater.

Keywords: bio-electrochemical systems, groundwater, electroactive denitrification, microbial electrolytic cell

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Authors: Ashwani Kumar Aggarwal

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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Yew Mun Yip, Dawei Zhang

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Proteins are the biological machinery that executes specific vital functions in every cell of the human body by folding into their 3D structures. When a protein misfolds from its native structure, the machinery will malfunction and lead to misfolding diseases. Although in vitro experiments are able to conclude that the mutations of the amino acid sequence lead to incorrectly folded protein structures, these experiments are unable to decipher the folding process. Therefore, molecular dynamic (MD) simulations are employed to simulate the folding process so that our improved understanding of the folding process will enable us to contemplate better treatments for misfolding diseases. MD simulations make use of force fields to simulate the folding process of peptides. Secondary structures are formed via the hydrogen bonds formed between the backbone atoms (C, O, N, H). It is important that the hydrogen bond energy computed during the MD simulation is accurate in order to direct the folding process to the native structure. Since the atoms involved in a hydrogen bond possess very dissimilar electronegativities, the more electronegative atom will attract greater electron density from the less electronegative atom towards itself. This is known as the polarization effect. Since the polarization effect changes the electron density of the two atoms in close proximity, the atomic charges of the two atoms should also vary based on the strength of the polarization effect. However, the fixed atomic charge scheme in force fields does not account for the polarization effect. In this study, we introduce the polarized structure-specific backbone charge (PSBC) model. The PSBC model accounts for the polarization effect in MD simulation by updating the atomic charges of the backbone hydrogen bond atoms according to equations derived between the amount of charge transferred to the atom and the length of the hydrogen bond, which are calculated from quantum-mechanical calculations. Compared to other polarizable models, the PSBC model does not require quantum-mechanical calculations of the peptide simulated at every time-step of the simulation and maintains the dynamic update of atomic charges, thereby reducing the computational cost and time while accounting for the polarization effect dynamically at the same time. The PSBC model is applied to two different β-peptides, namely the Beta3s/GS peptide, a de novo designed three-stranded β-sheet whose structure is folded in vitro and studied by NMR, and the trpzip peptides, a double-stranded β-sheet where a correlation is found between the type of amino acids that constitute the β-turn and the β-propensity.

Keywords: hydrogen bond, polarization effect, protein folding, PSBC

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Authors: Victor Emeli, Akansel Cosgun

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This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).

Keywords: motion planning, path planning, push planning, robot navigation

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Authors: Finbarr Murphy, Wei Xu, Xian Xu

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The embedding of digital technologies in the global economy has attracted increasing attention from economists. With a large and detailed dataset, this study examines the specific case where consumers have a choice between offline and digital channels in the context of insurance purchases. We find that digital channels screen consumers with lower unobserved risk. For the term life, endowment, and disease insurance products, the average risk of the policies purchased through digital channels was 75%, 21%, and 31%, respectively, lower than those purchased offline. As a consequence, the lower unobserved risk leads to weaker information asymmetry and higher profitability of digital channels. We highlight three mechanisms of the risk screening effect: heterogeneous marginal influence of channel features on insurance demand, the channel features directly related to risk control, and the link between the digital divide and risk. We also find that the risk screening effect mainly comes from the extensive margin, i.e., from new consumers. This paper contributes to three connected areas in the insurance context: the heterogeneous economic impacts of digital technology adoption, insurer-side risk selection, and insurance marketing.

Keywords: digital economy, information asymmetry, insurance, mobile application, risk screening

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Authors: Lin Cheng, Zijiang Yang

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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This proposal aims for semantic enrichment between glossaries using the Simple Knowledge Organization System (SKOS) vocabulary to discover synonyms, hyponyms and hyperonyms semiautomatically, in Brazilian Portuguese, generating new semantic relationships based on WordNet. To evaluate the quality of this proposed model, experiments were performed by the use of two sets containing new relations, being one generated automatically and the other manually mapped by the domain expert. The applied evaluation metrics were precision, recall, f-score, and confidence interval. The results obtained demonstrate that the applied method in the field of Oil Production and Extraction (E&P) is effective, which suggests that it can be used to improve the quality of terminological mappings. The procedure, although adding complexity in its elaboration, can be reproduced in others domains.

Keywords: ontology matching, mapping enrichment, semantic web, linked data, SKOS

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Authors: M. A. Zeinelabdeen, A. E. Abasaeed, M. H. Gaily, A. K. Sulieman, M. D. Putra

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The effect of temperature on the production of fructose and bioethanol from date syrup via selective fermentation by S. cerevisiae ATCC 36859 strain was studied. Various temperatures have been tested (27, 30 and 33 ᵒC). The fermentation experiments were conducted in a water shaker bath at the three temperatures under testing and 120 rpm. The results showed that a high fructose yield can be achieved at all temperatures under testing while the optimal is 27 ᵒC with 84% fructose yield. A high ethanol yield can be obtained for all temperatures under testing. However; the maximum biomass concentration and ethanol yield (86.22%) were obtained at 30 ᵒC.

Keywords: dates, ethanol, fructose, fermentation, S. cerevisiae

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Authors: M. Bouhadef, K. Bouzelha-Hammoum, T. Guendouzen-Dabouz, A. Younsi, T. Zitoun

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The aim of this paper is to report the different experimental studies, conducted in the laboratory, dealing with the flow in the presence of an obstacle lying in a rectangular hydraulic channel. Both subcritical and supercritical regimes are considered. Generally, when considering the theoretical problem of the free-surface flow, in a fluid domain of finite depth, due to the presence of an obstacle, we suppose that the water is an inviscid fluid, which means that there is no sheared velocity profile, but constant upstream. In a hydraulic channel, it is impossible to satisfy this condition. Indeed, water is a viscous fluid and its velocity is null at the bottom. The two configurations are presented, i.e. a flow over an obstacle and a towed obstacle in a resting fluid.

Keywords: experiments, free-surface flow, hydraulic channel, subcritical regime, supercritical flow

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Authors: Yuqing Sun

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Chinese has been regarded as one of the most difficult languages in learning due to its complex spelling structure, difficult pronunciation, as well as its varying forms. Since vocabulary acquisition is the basic process to acquire a language, to express yourself, to compose a sentence, and to conduct a communication, so learning the vocabulary is of great importance. However, the vocabulary contains pronunciation, spelling, recognition and application which may seem as a huge work. This may pose a question for the language teachers (language teachers in China who teach Chinese to the foreign students): How to teach them in an effective way? Traditionally, teachers have no choice but teach it all by themselves, then with the development of technology, they can use computer as a tool to help them (Computer Assisted Language Learning or CALL). Now, they move into the Mobile Assisted Language Learning (MALL) method to guide their teaching, upon which the appraisal is convincing. It diversifies the learning material and the way of output, which can activate learners’ curiosity and accelerate their understanding. This paper will focus on actual case studies occurring in the universities in China of teaching the foreign students to learn Chinese, and the analysis of the utilization of WeChat channel as an example of MALL model to explore the active role of MALL to enhance the effectiveness of Chinese vocabulary acquisition.

Keywords: Chinese, vocabulary acquisition, MALL, case

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Authors: Samir K. Safi

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The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.

Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility

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Authors: Umberto Platini

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This paper analyses the role of government fragmentation as predictor of the use of emergency decrees in parliamentary democracies. In particular, it focuses on the relationship between ideological divisiveness within cabinets and the choice by executives to issue emergency decrees rather initiating ordinary legislative procedures. A Bayesian multilevel analysis conducted on the population of government-initiated legislation in Italy between 1996 and 2018 finds significant evidence that those legislative proposals which are further away from the ideological centre of gravity of the executive are around three times more likely to be issued as emergency decrees. Likewise, legislative projects regulating more contentious policy areas are significantly more likely to be issued by decree. However, for more contentious issues the importance of ideological distance as a predictor diminishes. This evidence suggests that cabinets prefer decrees to ordinary legislative procedures when they expect that the bargaining environment in Parliament is more hostile. These results persist regardless of the fluctuations of the political-economic cycle. Their robustness is also tested against a battery of controls and against fixed effects both at the government level and at the legislature level.

Keywords: Bayesian multilevel logit models, executive action, executive decrees, ideology, legislative studies, polarization

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Authors: Sarah Alamolhoda, Kevin J. Smith, Xiaotao Bi, Naoko Ellis

Abstract:

For millennials, biomass has been the most important source of fuel used to produce energy. Energy derived from biomass is renewable by re-growth of biomass. Various technologies are used to convert biomass to potential renewable products including combustion, gasification, pyrolysis and fermentation. Gasification is the incomplete combustion of biomass in a controlled environment that results in valuable products such as syngas, biooil and biochar. Syngas is a combustible gas consisting of hydrogen (H₂), carbon monoxide (CO), carbon dioxide (CO₂), and traces of methane (CH₄) and nitrogen (N₂). Cleaned syngas can be used as a turbine fuel to generate electricity, raw material for hydrogen and synthetic natural gas production, or as the anode gas of solid oxide fuel cells. In this work, syngas as a product of woody biomass gasification in British Columbia, Canada, was introduced to two consecutive fixed bed reactors to perform a catalytic water gas shift reaction followed by a catalytic methanation reaction. The water gas shift reaction is a well-established industrial process and used to increase the hydrogen content of the syngas before the methanation process. Catalysts were used in the process since both reactions are reversible exothermic, and thermodynamically preferred at lower temperatures while kinetically favored at elevated temperatures. The water gas shift reactor and the methanation reactor were packed with Cu-based catalyst and Ni-based catalyst, respectively. Simulated syngas with different percentages of CO, H₂, CH₄, and CO₂ were fed to the reactors to investigate the effect of operating conditions in the unit. The water gas shift reaction experiments were done in the temperature of 150 ˚C to 200 ˚C, and the pressure of 550 kPa to 830 kPa. Similarly, methanation experiments were run in the temperature of 300 ˚C to 400 ˚C, and the pressure of 2340 kPa to 3450 kPa. The Methanation reaction reached 98% of CO conversion at 340 ˚C and 3450 kPa, in which more than half of CO was converted to CH₄. Increasing the reaction temperature caused reduction in the CO conversion and increase in the CH₄ selectivity. The process was designed to be renewable and release low greenhouse gas emissions. Syngas is a clean burning fuel, however by going through water gas shift reaction, toxic CO was removed, and hydrogen as a green fuel was produced. Moreover, in the methanation process, the syngas energy was transformed to a fuel with higher energy density (per volume) leading to reduction in the amount of required fuel that flows through the equipment and improvement in the process efficiency. Natural gas is about 3.5 times more efficient (energy/ volume) than hydrogen and easier to store and transport. When modification of existing infrastructure is not practical, the partial conversion of renewable hydrogen to natural gas (with up to 15% hydrogen content), the efficiency would be preserved while greenhouse gas emission footprint is eliminated.

Keywords: renewable natural gas, methane, hydrogen, gasification, syngas, catalysis, fuel

Procedia PDF Downloads 118

Authors: Victor Mantilla, Romeu Vicente, António Figueiredo, Victor Ferreira, Sandra Sorte

Abstract:

Integrating dynamic facades into contemporary building design is shaping a new era of energy efficiency and user comfort. These innovative facades, often constructed using lightweight construction systems and materials, offer an opportunity to have a responsive and adaptive nature to the dynamic behavior of the outdoor climate. Therefore, in regions characterized by high fluctuations in daily temperatures, the ability to adapt to environmental changes is of paramount importance and a challenge. This paper presents a thorough review of the state of the art on double-skin facades (DSF), focusing on lightweight solutions for the external envelope. Dynamic facades featuring elements like movable shading devices, phase change materials, and advanced control systems have revolutionized the built environment. They offer a promising path for reducing energy consumption while enhancing occupant well-being. Lightweight construction systems are increasingly becoming the choice for the constitution of these facade solutions, offering benefits such as reduced structural loads and reduced construction waste, improving overall sustainability. However, the performance of dynamic facades based on low thermal inertia solutions in climatic contexts with high thermal amplitude is still in need of research since their ability to adapt is traduced in variability/manipulation of the thermal transmittance coefficient (U-value). Emerging technologies can enable such a dynamic thermal behavior through innovative materials, changes in geometry and control to optimize the facade performance. These innovations will allow a facade system to respond to shifting outdoor temperature, relative humidity, wind, and solar radiation conditions, ensuring that energy efficiency and occupant comfort are both met/coupled. This review addresses the potential configuration of double-skin facades, particularly concerning their responsiveness to seasonal variations in temperature, with a specific focus on addressing the challenges posed by winter and summer conditions. Notably, the design of a dynamic facade is significantly shaped by several pivotal factors, including the choice of materials, geometric considerations, and the implementation of effective monitoring systems. Within the realm of double skin facades, various configurations are explored, encompassing exhaust air, supply air, and thermal buffering mechanisms. According to the review places a specific emphasis on the thermal dynamics at play, closely examining the impact of factors such as the color of the facade, the slat angle's dimensions, and the positioning and type of shading devices employed in these innovative architectural structures.This paper will synthesize the current research trends in this field, with the presentation of case studies and technological innovations with a comprehensive understanding of the cutting-edge solutions propelling the evolution of building envelopes in the face of climate change, namely focusing on double-skin lightweight solutions to create sustainable, adaptable, and responsive building envelopes. As indicated in the review, flexible and lightweight systems have broad applicability across all building sectors, and there is a growing recognition that retrofitting existing buildings may emerge as the predominant approach.

Keywords: adaptive, control systems, dynamic facades, energy efficiency, responsive, thermal comfort, thermal transmittance

Procedia PDF Downloads 80

Authors: Panupat Chaiworn, Soraya lama

Abstract:

We study the motion of particles in cylinders which are subjected to a sinusoidal vertical vibration. We measure the rising time of a large intruder from the bottom of the container to free surface of the bed particles and find that the rising time as a function of intruder density increases to a maximum and then decreases monotonically. The result is qualitatively accord to the previous findings in experiments using relative humidity of the bed particles and found speed convection of the bed particles containers it moving slowly, and the rising time of the intruder where a minimal instead of maximal rising time in the small density region was found. Our experimental results suggest that the topology of the container plays an important role in the Brazil nut effect.

Keywords: granular particles, Brazil nut effect, cylinder container, vertical vibration, convection

Procedia PDF Downloads 528