Search results for: computational complexity

Authors: E. Gaury, P. Mandausch, O. Picot, A. R. Thomas, L. Veisblat, L. Ralambozanany, C. Delsart

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In Dakar, demographic and spatial growth was accompanied by a 50% increase in household waste between 1988 and 2008 in the city. In addition, a change in the nature of household waste was observed between 1990 and 2007. The share of plastic increased by 15% between 2004 and 2007 in Dakar. Plastics represent the seventh category of household waste, the most produced per year in Senegal. The share of plastic in household and similar waste is 9% in Senegal. Waste management in the city of Dakar is a complex process involving a multitude of formal and informal actors with different perceptions and objectives. The objective of this study was to understand the motivations that could lead to sorting action, as well as the perception of plastic waste sorting within the Dakar population (households and institutions). The problematic of this study was as follows: what may be the factors playing a role in the sorting action? In an attempt to answer this, two approaches have been developed: (1) An exploratory qualitative study by semi-structured interviews with two groups of individuals concerned by the sorting of plastic waste: on the one hand, the experts in charge of waste management and on the other the households-producers of waste plastics. This study served as the basis for formulating the hypotheses and thus for the quantitative analysis. (2) A quantitative study using a questionnaire survey method among households producing plastic waste in order to test the previously formulated hypotheses. The objective was to have quantitative results representative of the population of Dakar in relation to the behavior and the process inherent in the adoption of the plastic waste sorting action. The exploratory study shows that the perception of state responsibility varies between institutions and households. Public institutions perceive this as a shared responsibility because the problem of plastic waste affects many sectors (health, environmental education, etc.). Their involvement is geared more towards raising awareness and educating young people. As state action is limited, the emergence of private companies in this sector seems logical as they are setting up collection networks to develop a recycling activity. The state plays a moral support role in these activities and encourages companies to do more. The study of the understanding of the action of sorting plastic waste by the population of Dakar through a quantitative analysis was able to demonstrate the attitudes and constraints inherent in the adoption of plastic waste sorting.Cognitive attitude, knowledge, and visible consequences have been shown to correlate positively with sorting behavior. Thus, it would seem that the population of Dakar is more sensitive to what they see and what they know to adopt sorting behavior.It has also been shown that the strongest constraints that could slow down sorting behavior were the complexity of the process, too much time and the lack of infrastructure in which to deposit plastic waste.

Keywords: behavior, Dakar, plastic waste, waste management

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

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Authors: Sajjad Hussain, Sabir Khan, Maria Del Pilar Taboada Sotomayor

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This work demonstrates the synthesis of magnetic molecularly imprinted polymers (MMIPs) for determination of a selected pesticide (ametryne) using high performance liquid chromatography (HPLC). Computational simulation can assist the choice of the most suitable monomer for the synthesis of polymers. The (MMIPs) were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using 2-vinylpyradine as functional monomer, ethylene-glycol-dimethacrylate (EGDMA) is a cross-linking agent and 2,2-Azobisisobutyronitrile (AIBN) used as radical initiator. Magnetic non-molecularly imprinted polymer (MNIPs) was also prepared under the same conditions without analyte. The MMIPs were characterized by scanning electron microscopy (SEM), Brunauer, Emmett and Teller (BET) and Fourier transform infrared spectroscopy (FTIR). Pseudo first order and pseudo second order model were applied to study kinetics of adsorption and it was found that adsorption process followed the pseudo first order kinetic model. Adsorption equilibrium data was fitted to Freundlich and Langmuir isotherms and the sorption equilibrium process was well described by Langmuir isotherm mode. The selectivity coefficients (α) of MMIPs for ametryne with respect to atrazine, ciprofloxacin and folic acid were 4.28, 12.32, and 14.53 respectively. The spiked recoveries ranged between 91.33 and 106.80% were obtained. The results showed high affinity and selectivity of MMIPs for pesticide ametryne in the food samples.

Keywords: molecularly imprinted polymer, pesticides, magnetic nanoparticles, adsorption

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Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: Sebastian Kohlstädt, Michael Vynnycky, Stephan Goeke, Jan Jäckel, Andreas Gebauer-Teichmann

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This paper summarizes the progress in the latest computational fluid dynamics research towards the modeling in of lost core viability in high-pressure die casting. High-pressure die casting is a process that is widely employed in the automotive and neighboring industries due to its advantages in casting quality and cost efficiency. The degrees of freedom are however somewhat limited as it has been so far difficult to use lost cores in the process. This is right now changing and the deployment of lost cores is considered a future growth potential for high-pressure die casting companies. The use of this technology itself is difficult though. The strength of the core material, as chiefly salt is used, is limited and experiments have shown that the cores will not hold under all circumstances and process designs. For this purpose, the publicly available CFD library foam-extend (OpenFOAM) is used, and two additional fluid models for incompressible and compressible two-phase flow are implemented as fluid solver models into the FSI library. For this purpose, the volume-of-fluid (VOF) methodology is used. The necessity for the fluid-structure interaction (FSI) approach is shown by a simple CFD model geometry. The model is benchmarked against analytical models and experimental data. Sufficient agreement is found with the analytical models and good agreement with the experimental data. An outlook on future developments concludes the paper.

Keywords: CFD, fluid-structure interaction, high-pressure die casting, multiphase flow

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Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

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Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of living tissues to mechanical loads is necessary for a wide range of developing fields such as prosthetics design or computerassisted surgical interventions. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically, growth is one of the main sources. Extracting body organ’s shapes from medical imaging does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is gravity since an organ grows under its influence from birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. This paper presents an original computational framework based on gradual growth to determine the residual stresses due to growth. To illustrate the method, we apply it to a finite element model of a healthy human face reconstructed from medical images. The distribution of residual stress in facial tissues is computed, which can overcome the effect of gravity and maintain tissues firmness. Our assumption is that tissue wrinkles caused by aging could be a consequence of decreasing residual stress and thus not counteracting gravity. Taking into account these stresses seems therefore extremely important in maxillofacial surgery. It would indeed help surgeons to estimate tissues changes after surgery.

Keywords: finite element method, growth, residual stress, soft tissue

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Authors: Ilyas Khan. Liliane Pintelon, Harry Martin, Michael Shömig

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The increasing costs of healthcare on one hand, and the rise in aging population and associated chronic disease, on the other hand, are putting increasing burden on the current health care system in many Western countries. For instance, chronic kidney disease (CKD) is a common disease and in Europe, the cost of renal replacement therapy (RRT) is very significant to the total health care cost. However, the recent advancement in healthcare technology, provide the opportunity to treat patients at home in their own comfort. It is evident that home healthcare offers numerous advantages apparently, low costs and high patients’ quality of life. Despite these advantages, the intake of home hemodialysis (HHD) therapy is still low in particular in Germany. Many factors are accounted for the low number of HHD intake. However, this paper is focusing on patients’ safety-related factors of current HHD practices in Germany. The aim of this paper is to analyze the current HHD practices in Germany and to identify risks related factors if any exist. A case study has been conducted in a dialysis center which consists of four dialysis centers in the south of Germany. In total, these dialysis centers have 350 chronic dialysis patients, of which, four patients are on HHD. The centers have 126 staff which includes six nephrologists and 120 other staff i.e. nurses and administration. The results of the study revealed several risk-related factors. Most importantly, these centers do not offer allied health services at the pre-dialysis stage, the HHD training did not have an established curriculum; however, they have just recently developed the first version. Only a soft copy of the machine manual is offered to patients. Surprisingly, the management was not aware of any standard available for home assessment and installation. The home assessment is done by a third party (i.e. the machines and equipment provider) and they may not consider the hygienic quality of the patient’s home. The type of machine provided to patients at home is similar to the one in the center. The model may not be suitable at home because of its size and complexity. Even though portable hemodialysis machines, which are specially designed for home use, are available in the market such as the NxStage series. Besides the type of machine, no assistance is offered for space management at home in particular for placing the machine. Moreover, the centers do not offer remote assistance to patients and their carer at home. However, telephonic assistance is available. Furthermore, no alternative is offered if a carer is not available. In addition, the centers are lacking medical staff including nephrologists and renal nurses.

Keywords: home hemodialysis, home hemodialysis practices, patients’ related risks in the current home hemodialysis practices, patient safety in home hemodialysis

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Authors: Paola Molteni, Luigi d’Alonzo

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Background: Sensory issues are now considered one of the key aspects in defining and diagnosing autism, changing the perspectives on behavioural analysis and intervention in mainstream educational services. However, Italian teachers’ training is yet not specific on the topic of autism and its sensory-related effects and this research investigates the teacher’s capability in understanding the student’s needs and his/her challenging behaviours considering sensory perceptions. Objectives: The research aims to analyse mainstream schools teachers’ awareness on students’ sensory perceptions and how this affects classroom inclusion and learning process. The research questions are: i) Are teachers able to identify student’s sensory issues?; ii) Are trained teachers more able to identify sensory problems then untrained ones?; iii) What is the impact of sensory issues on inclusion in mainstream classrooms?; iv) What should teachers know about autistic sensory dimensions? Methods: This research was designed as a pilot study that involves a multi-methods approach, including action and collaborative research methodology. The designed research allows the researcher to catch the complexity of a province school district (from kindergarten to high school) through a deep detailed analysis of selected aspects. The researcher explored the questions described above through 133 questionnaires and 6 focus groups. The qualitative and quantitative data collected during the research were analysed using the Interpretative Phenomenological Analysis (IPA). Results: Mainstream schools teachers are not able to confidently recognise sensory issues of children included in the classroom. The research underlines: how professionals with no specific training on autism are not able to recognise sensory problems in students on the spectrum; how hearing and sight issues have higher impact on classroom inclusion and student’s learning process; how a lack of understanding is often followed by misinterpretations of the impact of sensory issues and challenging behaviours. Conclusions: As this research has shown, promoting and enhancing the importance of understanding sensory issues related to autism is fundamental to enable mainstream schools teachers to define educational and life-long plans able to properly answer the student’s needs and support his/her real inclusion in the classroom. This study is a good example of how the educational research can meet and help the daily practice in working with people on the autism spectrum and support the training design for mainstream school teachers: the emerging need of designed preparation on sensory issues is fundamental to be considered when planning school district in-service training programmes, specifically declined for inclusive services.

Keywords: autism spectrum condition, scholastic inclusion, sensory overload, teacher's training

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Christofas Stergianos, Jason Atkin, Herve Morvan

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As air traffic increases, more airports are interested in utilizing optimization methods. Many processes happen in parallel at an airport, and complex models are needed in order to have a reliable solution that can be implemented for ground movement operations. The ground movement for aircraft in an airport, allocating a path to each aircraft to follow in order to reach their destination (e.g. runway or gate), is one process that could be optimized. The Quickest Path Problem with Time Windows (QPPTW) algorithm has been developed to provide a conflict-free routing of vehicles and has been applied to routing aircraft around an airport. It was subsequently modified to increase the accuracy for airport applications. These modifications take into consideration specific characteristics of the problem, such as: the pushback process, which considers the extra time that is needed for pushing back an aircraft and turning its engines on; stand holding where any waiting should be allocated to the stand; and runway sequencing, where the sequence of the aircraft that take off is optimized and has to be respected. QPPTW involves searching for the quickest path by expanding the search in all directions, similarly to Dijkstra’s algorithm. Finding a way to direct the expansion can potentially assist the search and achieve a better performance. We have further modified the QPPTW algorithm to use a heuristic approach in order to guide the search. This new algorithm is based on the A-star search method but estimates the remaining time (instead of distance) in order to assess how far the target is. It is important to consider the remaining time that it is needed to reach the target, so that delays that are caused by other aircraft can be part of the optimization method. All of the other characteristics are still considered and time windows are still used in order to route multiple aircraft rather than a single aircraft. In this way the quickest path is found for each aircraft while taking into account the movements of the previously routed aircraft. After running experiments using a week of real aircraft data from Zurich Airport, the new algorithm (A-star QPPTW) was found to route aircraft much more quickly, being especially fast in routing the departing aircraft where pushback delays are significant. On average A-star QPPTW could route a full day (755 to 837 aircraft movements) 56% faster than the original algorithm. In total the routing of a full week of aircraft took only 12 seconds with the new algorithm, 15 seconds faster than the original algorithm. For real time application, the algorithm needs to be very fast, and this speed increase will allow us to add additional features and complexity, allowing further integration with other processes in airports and leading to more optimized and environmentally friendly airports.

Keywords: a-star search, airport operations, ground movement optimization, routing and scheduling

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Authors: Mohamed Razi Nalim, Shahrzad Ghadiri

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With current concerns regarding global warming, demand for a society with greater environmental awareness significantly increases. With gradual development in hybrid and electric vehicles and the availability of renewable energy resources, increasing efficiency in fossil fuel and combustion engines seems a faster solution toward sustainability and reducing greenhouse gas emissions. This paper aims to provide a comprehensive review of recent progress in wave rotor combustor, one of the combustion concepts with considerable potential to improve power output and emission standards. A wave rotor is an oscillatory flow device that uses the unsteady gas dynamic concept to transfer energy by generating pressure waves. From a thermodynamic point of view, unlike conventional positive-displacement piston engines which follow the Brayton cycle, wave rotors offer higher cycle efficiency due to pressure gain during the combustion process based on the Humphrey cycle. First, the paper covers all recent and ongoing computational and experimental studies around the world with a quick look at the milestones in the history of wave rotor development. Second, the main similarity and differences in the ignition system of the wave rotor with piston engines are considered. Also, the comparison is made with another pressure gain device, rotating detonation engines. Next, the main challenges and research needs for wave rotor combustor commercialization are discussed.

Keywords: wave rotor combustor, unsteady gas dynamic, pre-chamber jet ignition, pressure gain combustion, constant-volume combustion

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Syed Muhammad Awais Tahir, Syed Hossein Raza Hamdani

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In the last two years, there has been a substantial increase in the rate of satellite launches. To keep up with the technology, it is imperative that the launch cost must be made affordable, especially in developing and underdeveloped countries. Launch cost is directly affected by the launch vehicle’s aerodynamic performance. Pegasus-XL SLV (Satellite Launch Vehicle) has been serving as a commercial SLV for the last 26 years, commencing its commercial flight operation from the six operational sites all around the US and Europe, and the Marshal Islands. Aerodynamic heating and drag contribute largely to Pegasus’s flight performance. The objective of this study is to reduce the aerodynamic heating and drag on Pegasus’s body significantly for supersonic and hypersonic flight regimes. Aerodynamic data for Pegasus’s first flight has been validated through CFD (Computational Fluid Dynamics), and then drag and aerodynamic heating is reduced by using a combination of a forward-facing cylindrical spike and a conical aero-disk at the actual operational flight conditions. CFD analysis using ANSYS fluent will be carried out for Mach no. ranges from 0.83 to 7.8, and AoA (Angle of Attack) ranges from -4 to +24 degrees for both simple and spiked-configuration, and then the comparison will be drawn using a variety of graphs and contours. Expected drag reduction for supersonic flight is to be around 15% to 25%, and for hypersonic flight is to be around 30% to 50%, especially for AoA < 15⁰. A 5% to 10% reduction in aerodynamic heating is expected to be achieved for hypersonic regions. In conclusion, the aerodynamic performance of air-launched Pegasus-XL SLV can be further enhanced, leading to its optimal fuel usage to achieve a more economical orbital flight.

Keywords: aerodynamics, pegasus-XL, drag reduction, aerodynamic heating, satellite launch vehicle, SLV, spike, aero-disk

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Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: Tran Ich Thinh, Nguyen Manh Cuong

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Free vibrations of partial fluid-filled composite truncated conical shells are investigated using the Dynamic Stiffness Method (DSM) or Continuous Element Method (CEM) based on the First Order Shear Deformation Theory (FSDT) and non-viscous incompressible fluid equations. Numerical examples are given for analyzing natural frequencies and harmonic responses of clamped-free conical shells partially and completely filled with fluid. To compare with the theoretical results, detailed experimental results have been obtained on the free vibration of a clamped-free conical shells partially filled with water by using a multi-vibration measuring machine (DEWEBOOK-DASYLab 5.61.10). Three glass fiber/polyester composite truncated cones with the radius of the larger end 285 mm, thickness 2 mm, and the cone lengths along the generators are 285 mm, 427.5 mm and 570 mm with the semi-vertex angles 27, 14 and 9 degrees respectively were used, and the filling ratio of the contained water was 0, 0.25, 0.50, 0.75 and 1.0. The results calculated by proposed computational model for studied composite conical shells are in good agreement with experiments. Obtained results indicate that the fluid filling can reduce significantly the natural frequencies of composite conical shells. Parametric studies including circumferential wave number, fluid depth and cone angles are carried out.

Keywords: dynamic stiffness method, experimental study, free vibration, fluid-shell interaction, glass fiber/polyester composite conical shell

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Authors: S. K. Fasogbon, O. E. Oguegbu

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Pasteurization is one of the most important steps in the preservation of beer products, which improves its shelf life by inactivating almost all the spoilage organisms present in it. However, there is no gain saying the fact that it is always difficult to determine the slowest heating zone, the temperature profile and pasteurization units inside bottled beer during pasteurization, hence there had been significant experimental and ANSYS fluent approaches on the problem. This work now developed Computational fluid dynamics model using COMSOL Multiphysics. The model was simulated to determine the slowest heating zone, temperature profile and pasteurization units inside the bottled beer during the pasteurization process. The results of the simulation were compared with the existing data in the literature. The results showed that, the location and size of the slowest heating zone is dependent on the time-temperature combination of each zone. The results also showed that the temperature profile of the bottled beer was found to be affected by the natural convection resulting from variation in density during pasteurization process and that the pasteurization unit increases with time subject to the temperature reached by the beer. Although the results of this work agreed with literatures in the aspects of slowest heating zone and temperature profiles, the results of pasteurization unit however did not agree. It was suspected that this must have been greatly affected by the bottle geometry, specific heat capacity and density of the beer in question. The work concludes that for effective pasteurization to be achieved, there is a need to optimize the spray water temperature and the time spent by the bottled product in each of the pasteurization zones.

Keywords: modeling, heat transfer, temperature profile, pasteurization process, bottled beer

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Authors: Kawsar Ahmed, Hong Wang

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The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy.

Keywords: causal mediation analysis, directed acyclic graphs, tobacco price policy, sensitivity analysis, pathway estimation

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Authors: Yaara Oppenheimer-Shaanan, Nimrod Nachmias, Marina Campos Rocha, Neta Schlezinger, Noam Dotan, Asaf Levy

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Fusarium oxysporum, a fungus that attacks a broad range of plants and can cause infections in humans, operates across different kingdoms. This pathogen encounters varied conditions, such as temperature, pH, and nutrient availability, in plant and human hosts. The Fusarium oxysporum species complex, pervasive in soils globally, can affect numerous plants, including key crops like tomatoes and bananas. Controlling Fusarium infections can involve biocontrol agents that hinder the growth of harmful strains. Our research developed a computational method to identify toxin domains within a vast number of microbial genomes, leading to the discovery of nine distinct toxins capable of killing bacteria and fungi, including Fusarium. These toxins appear to function as enzymes, causing significant damage to cellular structures, membranes and DNA. We explored biological control using bacteria that produce polymorphic toxins, finding that certain bacteria, non-pathogenic to plants, offer a safe biological alternative for Fusarium management, as they did not harm macrophage cells or C. elegans. Additionally, we elucidated the 3D structures of two toxins with their protective immunity proteins, revealing their function as unique DNases. These potent toxins are likely instrumental in microbial competition within plant ecosystems and could serve as biocontrol agents to mitigate Fusarium wilt and related diseases.

Keywords: microbial toxins, antifungal, Fusarium oxysporum, bacterial-fungal intreactions

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Authors: Rui Brito

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This contribution regards a literature review of inventory management that is a relevant topic for the firms, due to its important use of capital with implications in firm’s profitability within the complexity of a more competitive and globalized world. Firms look for small inventories in order to reduce holding costs, namely opportunity cost, warehousing and handling costs, deterioration and being out of style, but larger inventories are required by some reasons, such as customer service, ordering cost, transportation cost, supplier’s payment to reduce unit costs or to take advantage of price increase in the near future, and equipment setup cost. Thus, management shall address a trade-off between small inventories and larger inventories. This literature review concerns three types of inventory (spare parts, safety stock, and vendor) whose management usually is beyond the scope of logistics. The applied methodology consisted of an online search of databases regarding scientific documents in English, namely Elsevier, Springer, Emerald, Wiley, and Taylor & Francis, but excluding books except if edited, using search engines, such as Google Scholar and B-on. The search was based on three keywords/strings (themes) which had to be included just as in the article title, suggesting themes were very relevant to the researchers. The whole search period was between 2009 and 2018 with the aim of collecting between twenty and forty studies considered relevant within each of the key words/strings specified. Documents were sorted by relevance and to prevent the exclusion of the more recent articles, based on lower quantity of citations partially due to less time to be cited in new research articles, the search period was divided into two sub-periods (2009-2015 and 2016-2018). The number of surveyed articles by theme showed a variation from 40 to 200 and the number of citations of those articles showed a wider variation from 3 to 216. Selected articles from the three themes were analyzed and the first seven of the first sub-period and the first three of the second sub-period with more citations were read in full to make a synopsis of each article. Overall, the findings show that the majority of article types were models, namely mathematical, although with different sub-types for each theme. Almost all articles suggest further studies, with some mentioning it for their own author(s), which widen the diversity of the previous research. Identified research gaps concern the use of surveys to know which are the models more used by firms, the reasons for not using the models with more performance and accuracy, and which are the satisfaction levels with the outcomes of the inventories management and its effect on the improvement of the firm’s overall performance. The review ends with the limitations and contributions of the study.

Keywords: inventory management, safety stock, spare parts inventory, vendor managed inventory

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Authors: Mohammad Bagher Anvari, Arman Shojaei

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Incremental launching, a widely adopted bridge erection technique, offers numerous advantages for bridge designers. However, accurately simulating and modeling the dynamic behavior of the bridge during each step of the launching process proves to be tedious and time-consuming. The perpetual variation of internal forces within the deck during construction stages adds complexity, exacerbated further by considerations of other load cases, such as support settlements and temperature effects. As a result, there is an urgent need for a reliable, simple, economical, and fast algorithmic solution to model bridge construction stages effectively. This paper presents a novel Finite Element (FE) model that focuses on studying the static behavior of bridges during the launching process. Additionally, a simple method is introduced to normalize all quantities in the problem. The new FE model overcomes the limitations of previous models, enabling the simulation of all stages of launching, which conventional models fail to achieve due to underlying assumptions. By leveraging the results obtained from the new FE model, this study proposes solutions to improve the accuracy of conventional models, particularly for the initial stages of bridge construction that have been neglected in previous research. The research highlights the critical role played by the first span of the bridge during the initial stages, a factor often overlooked in existing studies. Furthermore, a new and simplified model termed the "semi-infinite beam" model, is developed to address this oversight. By utilizing this model alongside a simple optimization approach, optimal values for launching nose specifications are derived. The practical applications of this study extend to optimizing the nose-deck system of incrementally launched bridges, providing valuable insights for practical usage. In conclusion, this paper introduces a comprehensive Finite Element model for studying the static behavior of bridges during incremental launching. The proposed model addresses limitations found in previous approaches and offers practical solutions to enhance accuracy. The study emphasizes the importance of considering the initial stages and introduces the "semi-infinite beam" model. Through the developed model and optimization approach, optimal specifications for launching nose configurations are determined. This research holds significant practical implications and contributes to the optimization of incrementally launched bridges, benefiting both the construction industry and bridge designers.

Keywords: incremental launching, bridge construction, finite element model, optimization

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Authors: Linlong Mu, Maosong Huang

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Considering excavations in urban areas, the soil deformation induced by the excavations usually causes damage to the surrounding structures. Displacement control becomes a critical indicator of foundation design in order to protect the surrounding structures. Evaluation, the damage potential of the surrounding structures induced by the excavations, usually depends on the finite element method (FEM) because of the complexity of the excavation and the variety of the surrounding structures. Besides, evaluation the influence of the excavation on surrounding structures is a three-dimensional problem. And it is now well recognized that small strain behaviour of the soil influences the responses of the excavation significantly. Three-dimensional FEM considering small strain behaviour of the soil is a very complex method, which is hard for engineers to use. Thus, it is important to obtain a simplified method for engineers to predict the influence of the excavations on the surrounding structures. Based on large-scale finite element calculation with small-strain based soil model coupling with inverse analysis, an empirical method is proposed to calculate the three-dimensional soil movement induced by braced excavation. The empirical method is able to capture the small-strain behaviour of the soil. And it is suitable to be used in layered soil. Then the free-field soil movement is applied to the pile to calculate the responses of the pile in both vertical and horizontal directions. The asymmetric solutions for problems in layered elastic half-space are employed to solve the interactions between soil points. Both vertical and horizontal pile responses are solved through finite difference method based on elastic theory. Interactions among the nodes along a single pile, pile-pile interactions, pile-soil-pile interaction action and soil-soil interactions are counted to improve the calculation accuracy of the method. For passive piles, the shadow effects are also calculated in the method. Finally, the restrictions of the raft on the piles and the soils are summarized as: (1) the summations of the internal forces between the elements of the raft and the elements of the foundation, including piles and soil surface elements, is equal to 0; (2) the deformations of pile heads or of the soil surface elements are the same as the deformations of the corresponding elements of the raft. Validations are carried out by comparing the results from the proposed method with the results from the model tests, FEM and other existing literatures. From the comparisons, it can be seen that the results from the proposed method fit with the results from other methods very well. The method proposed herein is suitable to predict the responses of the pile-raft foundation induced by braced excavation in layered soil in both vertical and horizontal directions when the deformation is small. However, more data is needed to verify the method before it can be used in practice.

Keywords: excavation, pile-raft foundation, passive piles, deformation control, soil movement

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Authors: Luis Enrique Escalante Ochoa

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This paper attempts to assess the impacts of Climate change (CC) on inequalities in the labour market. CC will have the most serious effects on some vulnerable economic sectors, such as agriculture, livestock or tourism, but also on the most vulnerable population groups. The objective of this research is to evaluate the impact of CC on the labour market and particularly on Mexican women. Influential documents such as the synthesis reports produced by the Intergovernmental Panel on Climate Change (IPCC) in 2007 and 2014 revived a global effort to counteract the effects of CC, called for an analysis of the impacts on vulnerable socio-economic groups and on economic activities, and for the development of decision-making tools to enable policy and other decisions based on the complexity of the world in relation to climate change, taking into account socio-economic attributes. We follow up this suggestion and determine the impact of CC on vulnerable populations in the Mexican labour market, taking into account two attributes (gender and level of qualification of workers). Most studies have focused on the effects of CC on the agricultural sector, as it is considered a highly vulnerable economic sector to the effects of climate variability. This research seeks to contribute to the existing literature taking into account, in addition to the agricultural sector, other sectors such as tourism, water availability, and energy that are of vital importance to the Mexican economy. Likewise, the effects of climate change will be extended to the labour market and specifically to women who in some cases have been left out. The studies are sceptical about the impact of CC on the female labour market because of the perverse effects on women's domestic work, which are too often omitted from analyses. This work will contribute to the literature by integrating domestic work, which in the case of Mexico is much higher among women than among men (80.9% vs. 19.1%), according to the 2009 time use survey. This study is relevant since it will allow us to analyse impacts of climate change not only in the labour market of the formal economy, but also in the non-market sphere. Likewise, we consider that including the gender dimension is valid for the Mexican economy as it is a country with high degrees of gender inequality in the labour market. In the OECD economic study for Mexico (2017), the low labour participation of Mexican women is highlighted. Although participation has increased substantially in recent years (from 36% in 1990 to 47% in 2017), it remains low compared to the OECD average where women participate around 70% of the labour market. According to Mexico's 2009 time use survey, domestic work represents about 13% of the total time available. Understanding the interdependence between the market and non-market spheres, and the gender division of labour within them is the necessary premise for any economic analysis aimed at promoting gender equality and inclusive growth.

Keywords: climate change, labour market, domestic work, rural sector

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Authors: Vânia Costa, Nuno De Sá Teixeira, Ana C. Santos, Eduardo Santos

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Financial literacy and numeracy have been regarded as paramount for rational household decision making in the increasing complexity of financial markets. However, financial decisions are often made under sub-optimal circumstances, including cognitive overload. The present study aims to clarify how financial literacy and numeracy, taken as relevant expert knowledge for financial decision-making, modulate possible effects of cognitive load. Participants were required to perform a choice between a sure loss or a gambling pertaining a financial investment, either with or without a competing memory task. Two experiments were conducted varying only the content of the competing task. In the first, the financial choice task was made while maintaining on working memory a list of five random letters. In the second, cognitive load was based upon the retention of six random digits. In both experiments, one of the items in the list had to be recalled given its serial position. Outcomes of the first experiment revealed no significant main effect or interactions involving cognitive load manipulation and numeracy and financial literacy skills, strongly suggesting that retaining a list of random letters did not interfere with the cognitive abilities required for financial decision making. Conversely, and in the second experiment, a significant interaction between the competing mnesic task and level of financial literacy (but not numeracy) was found for the frequency of choice of a gambling option. Overall, and in the control condition, both participants with high financial literacy and high numeracy were more prone to choose the gambling option. However, and when under cognitive load, participants with high financial literacy were as likely as their illiterate counterparts to choose the gambling option. This outcome is interpreted as evidence that financial literacy prevents intuitive risk-aversion reasoning only under highly favourable conditions, as is the case when no other task is competing for cognitive resources. In contrast, participants with higher levels of numeracy were consistently more prone to choose the gambling option in both experimental conditions. These results are discussed in the light of the opposition between classical dual-process theories and fuzzy-trace theories for intuitive decision making, suggesting that while some instances of expertise (as numeracy) are prone to support easily accessible gist representations, other expert skills (as financial literacy) depend upon deliberative processes. It is furthermore suggested that this dissociation between types of expert knowledge might depend on the degree to which they are generalizable across disparate settings. Finally, applied implications of the present study are discussed with a focus on how it informs financial regulators and the importance and limits of promoting financial literacy and general numeracy.

Keywords: decision making, cognitive load, financial literacy, numeracy

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Quoc Hung Le Pham

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In the field of language study, classifier is an interesting research feature. In the world’s languages, some languages have classifier system, some do not. Mandarin Chinese and Vietnamese languages are a rich classifier system, however, because of the language system, the cognitive, cultural differences, so that the syntactic structure of classifier of them also dissimilar. When using Mandarin Chinese classifiers must collocate with nouns or verbs, in the lexical category it is not like nouns or verbs, belong to the open class. But some scholars believe that Mandarin Chinese measure words are similar to English and other Indo European languages. The word hanging on the structure and word formation (suffix), is a closed class. Compared to other languages, such as Chinese, Vietnamese, Thai and other Asian languages are still belonging to the classifier language’s second type, this type of language is classifier, it is in the majority of quantity must exist, and following deictic, anaphoric or quantity appearing together, not separation between its modified noun, also known as numeral classifier language. Main syntactic structure of Chinese classifiers are as follows: ‘quantity+measure+noun’, ‘pronoun+measure+noun’, ‘pronoun+quantity+measure+noun’, ‘prefix+quantity+measure +noun’, ‘quantity +adjective + measure +noun’, ‘ quantity (above 10 whole number), + duo (多)measure +noun’, ‘ quantity (around 10) + measure + duo (多) +noun’. Main syntactic structure of Vietnamese classifiers are: ‘quantity+measure+noun’, ‘ measure+noun+pronoun’, ‘quantity+measure+noun+pronoun’, ‘measure+noun+prefix+ quantity’, ‘quantity+measure+noun+adjective', ‘duo (多) +quanlity+measure+noun’, ‘quantity+measure+adjective+pronoun (quantity word could not be 1)’, ‘measure+adjective+pronoun’, ‘measure+pronoun’. In daily life, classifiers are commonly used, if Chinese learners failed to standardize this using catergory, because the negative impact might occur on their verbal communication. The richness of the Chinese classifier system contributes to the complexity in the study of the system by foreign learners, especially in the inter language of Vietnamese learners. As above mentioned, Vietnamese language also has a rich system of classifiers, however, the basic structure order of two languages are similar but both still have differences. These similarities and dissimilarities between Chinese and Vietnamese classifier systems contribute significantly to the common errors made by Vietnamese students while they acquire Chinese, which are distinct from the errors made by students from the other language background. This article from a comparative perspective of language, has an orientation towards Chinese and Vietnamese languages commonly used in classifiers semantics and structural form two aspects. This comparative study aims to identity Vietnamese students while learning Chinese classifiers may face some negative transference of mother language, beside that through the analysis of the classifiers questionnaire, find out the causes and patterns of the errors they made. As the preliminary analysis shows, Vietnamese students while learning Chinese classifiers made some errors such as: overuse classifier ‘ge’(个); misuse the other classifiers ‘*yi zhang ri ji’(yi pian ri ji), ‘*yi zuo fang zi’(yi jian fang zi), ‘*si zhang jin pai’(si mei jin pai); homonym words ‘dui, shuang, fu, tao’ (对、双、副、套), ‘ke, li’ (颗、粒).

Keywords: acquisition, classifiers, negative transfer, Vietnamse learners

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Authors: Emmanuel Ogala

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Cloud computing has been envisioned as the next-generation architecture of Information Technology (IT) enterprise. In contrast to traditional solutions where IT services are under physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. This is due to the fact that the systems are opened to the whole world and as people tries to have access into the system, many people also are there trying day-in day-out on having unauthorized access into the system. This research contributes to the improvement of cloud computing security for better operation. The work is motivated by two problems: first, the observed easy access to cloud computing resources and complexity of attacks to vital cloud computing data system NIC requires that dynamic security mechanism evolves to stay capable of preventing illegitimate access. Second; lack of good methodology for performance test and evaluation of biometric security algorithms for securing records in cloud computing environment. The aim of this research was to evaluate the performance of an integrated security system (ISS) for securing exams records in cloud computing environment. In this research, we designed and implemented an ISS consisting of three security mechanisms of biometric (fingerprint), auto-PIN and password into one stream of access control and used for securing examination records in Kogi State University, Anyigba. Conclusively, the system we built has been able to overcome guessing abilities of hackers who guesses people password or pin. We are certain about this because the added security system (fingerprint) needs the presence of the user of the software before a login access can be granted. This is based on the placement of his finger on the fingerprint biometrics scanner for capturing and verification purpose for user’s authenticity confirmation. The study adopted the conceptual of quantitative design. Object oriented and design methodology was adopted. In the analysis and design, PHP, HTML5, CSS, Visual Studio Java Script, and web 2.0 technologies were used to implement the model of ISS for cloud computing environment. Note; PHP, HTML5, CSS were used in conjunction with visual Studio front end engine design tools and MySQL + Access 7.0 were used for the backend engine and Java Script was used for object arrangement and also validation of user input for security check. Finally, the performance of the developed framework was evaluated by comparing with two other existing security systems (Auto-PIN and password) within the school and the results showed that the developed approach (fingerprint) allows overcoming the two main weaknesses of the existing systems and will work perfectly well if fully implemented.

Keywords: performance evaluation, fingerprint, auto-pin, password-based, security systems, cloud computing environment

Procedia PDF Downloads 114