Search results for: discrete choice models

Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Paolo Sassi, Jorge Freiria, Gabriel Usera

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In this work, a finite volume fluid flow solver is coupled with a discrete element method module for the simulation of the dynamics of free and elastic bodies in interaction with the fluid and between themselves. The open source fluid flow solver, caffa3d.MBRi, includes the capability to work with nested overlapping grids in order to easily refine the grid in the region where the bodies are moving. To do so, it is necessary to implement a recognition function able to identify the specific mesh block in which the device is moving in. The set of overlapping finer grids might be displaced along with the set of bodies being simulated. The interaction between the bodies and the fluid is computed through a two-way coupling. The velocity field of the fluid is first interpolated to determine the drag force on each object. After solving the objects displacements, subject to the elastic bonding among them, the force is applied back onto the fluid through a Gaussian smoothing considering the cells near the position of each object. The fishnet is represented as lumped masses connected by elastic lines. The internal forces are derived from the elasticity of these lines, and the external forces are due to drag, gravity, buoyancy and the load acting on each element of the system. When solving the ordinary differential equations system, that represents the motion of the elastic and flexible bodies, it was found that the Runge Kutta solver of fourth order is the best tool in terms of performance, but requires a finer grid than the fluid solver to make the system converge, which demands greater computing power. The coupled solver is demonstrated by simulating the interaction between the fluid, an elastic fishnet and a set of free bodies being captured by the net as they are dragged by the fluid. The deformation of the net, as well as the wake produced in the fluid stream are well captured by the method, without requiring the fluid solver mesh to adapt for the evolving geometry. Application of the same strategy to the simulation of elastic structures subject to the action of wind is also possible with the method presented, and one such application is currently under development.

Keywords: computational fluid dynamics, discrete element method, fishnets, nested overlapping grids

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Arcady Ponosov

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Many well-known age-structured population models are derived from the celebrated McKendrick-von Foerster equation (MFE), also called the biological conservation law. A similar technique is suggested for the stochastically perturbed MFE. This technique is shown to produce stochastic versions of the deterministic population models, which appear to be very different from those one can construct by simply appending additive stochasticity to deterministic equations. In particular, it is shown that stochastic Nicholson’s blowflies model should contain both additive and multiplicative stochastic noises. The suggested transformation technique is similar to that used in the deterministic case. The difference is hidden in the formulas for the exact solutions of the simplified boundary value problem for the stochastically perturbed MFE. The analysis is also based on the theory of stochastic delay differential equations.

Keywords: boundary value problems, population models, stochastic delay differential equations, stochastic partial differential equation

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

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Authors: Joseph Sello Kau, Elias Mashayamombe, Brian Washington Madinkana, Cynthia Ngwane

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This paper presents the results for the statistical (stepwise linear regression and multiple regression) analyses, carried out on a number of crops in order to evaluate how the decision for crop choice affect the level of farm income generated by the farmers participating in the High Value Crop production (referred to as the HVC). The goal of the HVC is to encourage farmers cultivate fruit crops. The farmers received planting material from different extension agencies, together with other complementary packages such as fertilizer, garden tools, water tanks etc. During the surveys, it was discovered that a significant number of farmers were cultivating traditional crops even when their plot sizes were small. Traditional crops are competing for resources with high value crops. The results of the analyses show that farmers cultivating fruit crops, maize and potatoes were generating high income than those cultivating spinach and cabbage. High farm income is associated with plot size, access to social grants and gender. Choice for a crop is influenced by the availability of planting material and the market potential for the crop. Extension agencies providing the planting materials stand a good chance of having farmers follow their directives. As a recommendation, for the farmers to cultivate more of the HVCs, the ARC must intensify provision of fruit trees.

Keywords: farm income, nature of extension services, type of crops cultivated, fruit crops, cabbage, maize, potato and spinach

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Authors: Rebecca Hafner, Daniel Read, David Elmes

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The persuasive potential of normative and feedback (financial vs. environmental) information in ‘nudging’ people towards making environmentally sound decisions was explored in a hypothetical choice experiment. The research was specifically focused on determining how subtle variations in the decision frame could be used to increase the selection of energy efficient vs. standard technologies, using the context of home heating choice. Participants were given a choice of a standard heating system (a gas boiler) and a relatively more-energy efficient option (a heat pump). The experiment had a 2 (normative vs. no normative information) by 3 feedback type (financial, environmental, none) design. The last group constituted the control. Half of the participants were given normative information about what the majority of others in their neighbourhood had opted to do when faced with the same choice set, prior to making their decision. The other half received no such information. Varying feedback frames were incorporated by providing participants with information on either financial or environmental savings that could be achieved by choosing the heat pump. No such information was provided in the control group. A significant interaction was found between normative information and feedback frame type. Specifically, the impact of feedback frames was found to be reduced when normative information was provided; illustrating the overriding influence of normative information on option preference. Participants were significantly more likely to select the heat pump if they were vs. were not given normative information. Yet when no normative information was provided, the persuasive influence of the financial frame was increased – highlighting this as an effective means of encouraging uptake of new technologies in this instance. Conversely, the environmental frame was not found to differ significantly from the control. Marginal carryover effects were also found for stated future real-life decision-making behaviour, with participants who were versus were not given normative information being marginally more likely to state they would consider installing a heat pump when they next need to replace their heating system in real life. We conclude that normative and financial feedback framing techniques are highly effective in increasing uptake of new, energy efficient heating technologies involving significant upfront financial outlay. The implications for researchers looking to promote ‘green’ choice in the context of new technology adoption are discussed.

Keywords: energy-efficient technology adoption, environmental decision making, financial vs. environmental feedback framing techniques, social norms

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Authors: Prasad Pokkunuri

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Visco-elastic materials combine the stress response properties of both solids and fluids and have found use in a variety of damping applications – both vibrational and acoustic. Defense and automotive applications, in particular, are subject to high impact and shock loading – for example: aircraft landing gear, firearms, and shock absorbers. Field responsive fluids – a class of smart materials – are the preferred choice of energy absorbents because of their controllability. These fluids’ stress response can be controlled by the application of a magnetic or electric field, in a closed loop. Their rheological properties – elasticity, plasticity, and viscosity – can be varied all the way from that of a liquid such as water to a hard solid. This work presents a simplified model to study the impulse response behavior of such fluids for use in recoil damping systems. The well-known Burger’s equation, in conjunction with various visco-elastic constitutive models, is used to represent fluid behavior. The Kelvin-Voigt, Upper Convected Maxwell (UCM), and Oldroyd-B constitutive models are implemented in this study. Using these models in a one-dimensional framework eliminates additional complexities due to geometry, pressure, body forces, and other source terms. Using a finite difference formulation to numerically solve the governing equation(s), the response to an initial impulse is studied. The disturbance is confined within the problem domain with no-inflow, no-outflow boundary conditions, and its decay characteristics studied. Visco-elastic fluids typically involve a time-dependent stress relaxation which gives rise to interesting behavior when subjected to an impulsive load. For particular values of viscous damping and elastic modulus, the fluid settles into a stable oscillatory state, absorbing and releasing energy without much decay. The simplified formulation enables a comprehensive study of different modes of system response, by varying relevant parameters. Using the insights gained from this study, extension to a more detailed multi-dimensional model is considered.

Keywords: Burgers Equation, Impulse Response, Recoil Damping Systems, Visco-elastic Fluids

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Authors: P. L. D. N. M. de Silva, S. G. Edirisinghe, R. Weerasuriya

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High peak-to-average power ratio (PAPR) is a concern of orthogonal frequency division multiplexing (OFDM) based visible light communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. Previous research has been conducted to study the impact of these techniques separately. However, to the best of the knowledge of the authors, no study has been done so far to identify the improvement which can be harnessed by hybridizing these two techniques for VLC systems. Therefore, this is a novel study area under this research. In addition, channel coding techniques such as Polar codes and Turbo codes have been tested in the VLC domain. However, other efficient techniques such as Hamming coding and Convolutional coding have not been studied too. Therefore, the authors present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems using Matlab simulations.

Keywords: convolutional coding, discrete Fourier transform spread orthogonal frequency division multiplexing, hamming coding, peak-to-average power ratio, visible light communications

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Authors: Adel Pasztor

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International doctoral mobility is a largely under-researched component of academic mobility and migration. This is in stark contrast to the case of student mobility where much research has been undertaken on Erasmus students; or the growing research on academic staff mobility which can be viewed as a key part of highly skilled migration. The aim of this paper is to remedy the situation by specifically focusing on international doctoral students studying at elite higher education institutions in the United Kingdom. In doing so, in-depth qualitative interviews with doctoral students and recent graduates were carried out in order to identify the signifiers of an internationally mobile doctoral student and unpack the decision-making processes leading onto the choice of higher education institution abroad. Overall, a diverse range of degree subjects from within the humanities and the social sciences were covered with a relatively large spread of nationalities which include the following countries: Italy, Germany, Hungary, Latvia, Bulgaria, Turkey, Lebanon, Israel, Australia, USA, China, and Chile. The interview questions were designed to probe the motivations, choices, educational trajectories and career plans of international doctoral students relative to their social class background, gender, nationality or funding. It was clear from the interviews that there were two main types of international doctoral students: those who ‘did not think anything else was ever a serious possibility’, contrasted with the other, more opportune type, to whom ‘it happened to be a PhD’. There were marked differences between the two types since initial access to university, mainly because educational decisions such as the doctorate do not happen in a vacuum, rather are built on the individual’s higher education aspirations and previous educational choices. The results were in line with existing literature suggesting that those with higher educated parents and from schools strongly supporting the choice process fared better as they were able to make well informed, well thought through as well as strategic decisions for their future involving the very best universities within the national boundaries. Being ‘at the right place’ often meant access to prestigious doctoral scholarships thus, the route of the PhD has been chosen even if it did not necessarily enhance career opportunities. At the same time, the initial higher education choices of those with limited capital were played out locally, although they did aim for the best universities within their geographically constrained landscape of choice. Here, the majority of students referred to some ‘turning points’ in their lives which lead them towards considering international doctoral opportunities but essentially their proactive, do-it-yourself attitude was behind the life-changing educational opportunities.

Keywords: choice, doctoral students, international mobility, PhD, UK

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Authors: Emily J. Morey, Kevin Galvin, Thomas Riley, R. Eddie Wilson

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The key challenges faced by integrating autonomous rail operations into the existing mainline railway environment have been identified through the understanding and framing of the problem space and stakeholder analysis. This was achieved through the completion of the first four steps of Soft Systems Methodology, where the problem space has been expressed via conceptual models. Having identified these challenges, we investigated one of them, namely capacity, via the use of models and simulation. This paper examines the approach used to move from the conceptual models to a simulation which can determine whether the integration of autonomous trains can plausibly increase capacity. Within this approach, we developed an architecture and converted logical models into physical resource models and associated design features which were used to build a simulator. From this simulator, we are able to analyse mixtures of legacy-autonomous operations and produce fundamental diagrams and trajectory plots to describe the dynamic behaviour of mixed mainline railway operations.

Keywords: autonomy, executable architecture, modelling and simulation, railway capacity

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Authors: Mohd Adib Abd Muin

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Social entrepreneurship has become a new phenomenon in a country in order to reduce social problems and eradicate poverty communities. However, the study based on Islamic social entrepreneurship from the social entrepreneurial activity is still new especially in the Islamic perspective. In addition, this research found that is lacking of model on social entrepreneurship that focus on Islamic perspective. Therefore, the objective of this paper is to identify the issues and research gap based on Islamic perspective from existing models and to develop a concept of Islamic social entrepreneurship according to Islamic perspective and Maqasid Shari’ah. The research method used in this study is literature review and comparative analysis from 11 existing models of social entrepreneurship. The research finding shows that 11 existing models on social entrepreneurship has been analyzed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: component, social entrepreneurship, Islamic perspective, research gap

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Authors: Salahaeddine Sbai

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Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

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Authors: Samuel Opeyemi Williams, Razali Bin Adul Hamid, M. S. Misnan, Taki Eddine Seghier, D. I. Ajayi

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Construction sites are characterized with occupational risks. Review of literature on construction accidents reveals that a lot of theories have been propounded over the years by different theorists, coupled with multifarious models developed by different proponents at different times. Accidents are unplanned events that are prominent in construction sites, involving materials, objects and people with attendant damages, loses and injuries. Models were developed to investigate the causations of accident with the aim of preventing its occurrence. Though, some of these theories were criticized, most especially, the Heinrich Domino theory, being mostly faulted for placing much blame on operatives rather than the management. The purpose of this paper is to unravel the significant construction accident causation theories and models for the benefit of understanding of the theories, and consequently enabling construction stakeholders identify the possible potential hazards on construction sites, as all stakeholders have significant roles to play in preventing accident. Accidents are preventable; hence, understanding the risk factors of accident and the causation theories paves way for its prevention. However, findings reveal that still some gaps missing in the existing models, while it is recommended that further research can be made in order to develop more models in order to maintain zero accident on construction sites.

Keywords: domino theory, construction site, site safety, accident causation model

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Authors: M. Wigwe, J. G Akpa, E. N Wami

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Mathematical models of the absorber of a glycol dehydration facility was developed using the principles of conservation of mass and energy. Models which predict variation of the water content of gas in mole fraction, variation of gas and liquid temperatures across the parking height were developed. These models contain contributions from bulk and diffusion flows. The effect of diffusion on the process occurring in the absorber was studied in this work. The models were validated using the initial conditions in the plant data from Company W TEG unit in Nigeria. The results obtained showed that the effect of diffusion was noticed between z=0 and z=0.004 m. A deviation from plant data of 0% was observed for the gas water content at a residence time of 20 seconds, at z=0.004 m. Similarly, deviations of 1.584% and 2.844% were observed for the gas and TEG temperatures.

Keywords: separations, absorption, simulation, dehydration, water content, triethylene glycol

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Authors: Boussoualim Nacira, Aklouf Youcef

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Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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Authors: Sally A. Brown

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Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

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Authors: Katalin Kovacs

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In most forms of violence the perpetrators intend to hide their identities. Terrorism is different. Terrorist groups often take responsibility for their attacks, and consequently they reveal their identities. This unique characteristic of terrorism has been largely overlooked, and scholars are still puzzled as to why terrorist groups claim responsibility for their attacks. Certainly, the claim of responsibility is worth analysing. It would help to have a clearer picture of what terrorist groups try to achieve and how, but also to develop an understanding of the strategic planning of terrorist attacks and the message the terrorists intend to deliver. The research aims to answer the question why terrorist groups choose to claim responsibility for some of their attacks and not for others. In order to do so the claim of responsibility is considered to be a tactical choice, based on the assumption that terrorists weigh the costs and benefits of claiming responsibility. The main argument is that terrorist groups do not claim responsibility in cases when there is no tactical advantage gained from claiming responsibility. The idea that the claim of responsibility has tactical value offers the opportunity to test these assertions using a large scale empirical analysis. The claim of responsibility as a tactical choice depends on other tactical choices, such as the choice of target, the internationality of the attack, the number of victims and whether the group occupies territory or operates as an underground group. The structure of the terrorist groups and the level of decision making also affects the claim of responsibility. Terrorists on the lower level are less disciplined than the leaders. This means that the terrorists on lower levels pay less attention to the strategic objectives and engage easier in indiscriminate violence, and consequently they would less like to claim responsibility. Therefore, the research argues that terrorists, who are on a highest level of decision making would claim responsibility for the attacks as those are who takes into account the strategic objectives. As most studies on terrorism fail to provide definitions; therefore the researches are fragmented and incomparable. Separate, isolated researches do not support comprehensive thinking. It is also very important to note that there are only a few researches using quantitative methods. The aim of the research is to develop a new and comprehensive overview of the claim of responsibility based on strong quantitative evidence. By using well-established definitions and operationalisation the current research focuses on a broad range of attributes that can have tactical values in order to determine circumstances when terrorists are more likely to claim responsibility.

Keywords: claim of responsibility, leadership, tactical choice, terrorist group

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Authors: Oulad Naoui Noureddine, Cherif ELAmine, Djehiche Abdelkader

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Water resources management includes several disciplines; the modeling of rainfall-runoff relationship is the most important discipline to prevent natural risks. There are several models to study rainfall-runoff relationship in watersheds. However, the majority of these models are not applicable in all basins of the world.  In this study, a new stochastic method called The Only Corresponding Competitor method (OCC) was used for the hydrological modeling of M’ZAB   Watershed (South East of Algeria) to adapt a few empirical models for any hydrological regime.  The results obtained allow to authorize a certain number of visions, in which it would be interesting to experiment with hydrological models that improve collectively or separately the data of a catchment by the OCC method.

Keywords: modelling, optimization, rainfall-runoff relationship, empirical model, OCC

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Authors: Candida Petrogalli, Giovanni Incerti, Luigi Solazzi

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This paper describes three lumped parameters models for the study of the dynamic behaviour of a boom crane. The models proposed here allow evaluating the fluctuations of the load arising from the rope and structure elasticity and from the type of the motion command imposed by the winch. A calculation software was developed in order to determine the actual acceleration of the lifted mass and the dynamic overload during the lifting phase. Some application examples are presented, with the aim of showing the correlation between the magnitude of the stress and the type of the employed motion command.

Keywords: crane, dynamic model, overloading condition, vibration

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Lucie Cote, Sonia McFadden

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Mental health problems in the workplace are currently one of the main causes of absences. Research work has highlighted the importance of a collaborative process involving the stakeholders in the return-to-work process and has established the best management practices to ensure a successful return-to-work. However, very few studies have specifically explored the combination of various management models and determined whether they could satisfy the needs of the stakeholders. The objective of this study is to analyze two models for managing the return to work: the ‘medical-administrative’ and the ‘support of the worker’ in order to understand the actions and actors involved in these models. The study also aims to explore whether these models meet the needs of the actors involved in the management of the return to work. A qualitative case study was conducted in a Canadian federal organization. An abundant internal documentation and semi-directed interviews with six managers, six workers and four human resources professionals involved in the management of records of employees returning to work after a mental health problem resulted in a complete picture of the return to work management practices used in this organization. The triangulation of this data facilitated the examination of the benefits and limitations of each approach. The results suggest that the actions of management for employee return to work from both models of management ‘support of the worker’ and ‘medical-administrative’ are compatible and can meet the needs of the actors involved in the return to work. More research is needed to develop a structured model integrating best practices of the two approaches to ensure the success of the return to work.

Keywords: return to work, mental health, management models, organizations

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Authors: Anton James

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This study explored the contribution of parenting styles in the Maternal Perception of Compliance Model (MPCM). This model explores maternal expectations to illustrate the formation of maternal perception of severity of noncompliance in adolescent children. The methodology consisted of three stages: In the first stage, a focus group was held, and the data was analysed to fine-tune the interview schedule. In the second stage, a single interview was held, and the interview schedule was further modified. The third and the final stage consisted of interviewing six mothers who had adolescent children. They were chosen with ‘maximum variation’ approach to represent three tiered socioeconomic statuses, and Asian, white and black ethnicities. The data was thematically analysed in a hybrid fashion: inductive coding and deductive assignment of codes into discrete parenting styles. The study found: a) parenting styles are not always discrete and sometimes it can be mixed. b) The parenting styles are influenced by culture, socioeconomic status, transgenerational knowledge, academic knowledge, observational knowledge, self-reflective knowledge, and parental anxiety. c) The parenting style functioned a mediating mechanism where it attempted to converge discrepancies between parental expectations of compliance with maternal perception of severity of noncompliance. The findings of parenting styles were discussed in relation to MPCM.

Keywords: compliance, expectation, parenting styles, perception

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

Abstract:

Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.

Keywords: speed, Kriging, arterial, traffic volume

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Authors: Ussawit Srisakrapikoop, Art-Ong Pradatsundarasar, Duangkhae Sitthicharoenchai

Abstract:

Monomorium destructor or Singapore ant is one of the common household pests. It causes nuisance and damage to household. Due to the fact that there are many queens in one colony (polygyny), so this ant can quickly increase its population in a short time in the urban environment. This study has been conducted at Faculty of Science, Chulalongkorn University in the field condition. Ant food preference was conducted for 3 replicates per month by using six food choices including 20% sucrose solution, 20% sucrose agar, pork liver, smashed pork liver, pork fat and lard. The number of ants of each bait choice was counted and the orders of ant accessing baits were also recorded. The results showed that the 20% sucrose agar was the most attractive significantly following by pork liver and pork fat. The ants also most accessed to the pork liver bait choice in the first place. It can be suggested that the ant control by baiting should consist of mixture of carbohydrate, protein and lipid in solid form with suitable ratios.

Keywords: baits, food preference, monomorium destructor, Singapore ant

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

Abstract:

As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: H. Majour, L. Djabri

Abstract:

Many methods in the groundwater vulnerability have been developed in the world (methods like PRAST, DRIST, APRON/ARAA, PRASTCHIM, GOD). In this study, our choice dealt with two recent complementary methods using category mapping of index with weighting criteria (Point County Systems Model MSCP) namely the standard DRASTIC method and SI (Susceptibility Index). At present, these two methods are the most used for the mapping of the intrinsic vulnerability of groundwater. Two classes of groundwater vulnerability in the Biskra sandy aquifer were identified by the DRASTIC method (average and high) and the SI method (very high and high). Integrated analysis has revealed that the high class is predominant for the DRASTIC method whereas for that of SI the preponderance is for the very high class. Furthermore, we notice that the method SI estimates better the vulnerability for the pollution in nitrates, with a rate of 85 % between the concentrations in nitrates of groundwater and the various established classes of vulnerability, against 75 % for the DRASTIC method. By including the land use parameter, the SI method produced more realistic results.

Keywords: DRASTIC, SI, GIS, Biskra sandy aquifer, Algeria

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Authors: Sara Atibi, Azzeddine Atibi, Salim Ahmed, Khadija El Kababi

Abstract:

The concept of chemical bonding is fundamental in chemistry education, ubiquitous in school curricula, and essential to numerous topics in the field. Mastery of this concept enables students to predict and explain the physical and chemical properties of substances. However, chemical bonding is often regarded as one of the most complex concepts for secondary and higher education students to comprehend, due to the underlying complex theory and the use of abstract models. Teachers also encounter significant challenges in conveying this concept effectively. This study aims to identify the difficulties and alternative conceptions faced by Moroccan secondary school students in learning about chemical bonding, as well as the pedagogical strategies employed by teachers to overcome these obstacles. A survey was conducted involving 150 Moroccan secondary school physical science teachers, using a structured questionnaire comprising closed, open-ended, and multiple-choice questions. The results reveal frequent student misconceptions, such as the octet rule, molecular geometry, and molecular polarity. Contributing factors to these misconceptions include the abstract nature of the concepts, the use of models, and teachers' difficulties in explaining certain aspects of chemical bonding. The study proposes improvements for teaching chemical bonding, such as integrating information and communication technologies (ICT), diversifying pedagogical tools, and considering students' pre-existing conceptions. These recommendations aim to assist teachers, curriculum developers, and textbook authors in making chemistry more accessible and in addressing students' misconceptions.

Keywords: chemical bonding, alternative conceptions, chemistry education, pedagogical strategies

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