Search results for: approximate dynamic programming

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

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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: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Karel Šebesta, Jiří Žáček, Matuš Salva, Mohammad Housam

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Drivers of agricultural vehicles are exposed to continuous vibration caused by driving over rough terrain. The long-term effects of these vibrations could start with a decreased level of vigilance at work and could reach the level of several health problems. Therefore, eliminating the vibration to maximize the comfort of the driver is essential for better/longer performance. One of the modern damping systems, which can deal with this problem is the Semi-active (S/A) suspension system featuring a Magnetorheological (MR) damper. With this damper, the damping level can be adjusted using varying currents through the coil. Adjustments of the damping force can be carried out continuously based on the evaluated data (position and acceleration of seat) by the control algorithm. The advantage of this system is the wide dynamic range and the high speed of force response time. Compared to other S/A or active systems, the MR damper does not need as much electrical power, and the system is much simpler. This paper aims to prove the effectiveness of this damping system used in the tractor seat. The vibration testing stand was designed and manufactured specifically for this type of research, which is used to simulate vibrations with constant amplitude at variable frequency.

Keywords: magnetorheological damper, semi-active suspension, seat scissor mechanism, sky-hook

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Authors: Wen Ma, Yong Peng, Zhixiang Li

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Security journey is a vital focus on the field of Rail Transportation. Accidents caused by the damage of the high-speed train windshield have occurred many times and have given rise to terrible consequences. Train windshield consists of tempered glass and polyvinyl butyral (PVB) film. In this work, the quasi-static tests and the split Hopkinson pressure bar (SHPB) tests were carried out first to obtain the mechanical properties and constitutive model for the tempered glass and PVB film. These tests results revealed that stress and Young’s modulus of tempered glass were wake-sensitive to strain rate, but stress and Young’s modulus of PVB film were strong-sensitive to strain rate. Then impact experiment of the windshield was carried out to investigate dynamic response and failure characteristics of train windshield. In addition, a finite element model based on the combined finite element method was proposed to investigate fracture and fragmentation responses of train windshield under different-velocity impact. The results can be used for further design and optimization of the windshield for high-speed train application.

Keywords: constitutive model, impact response, mechanism properties, PVB film, tempered glass

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Authors: Garry Gorman, Nigel McKelvey, James Connolly

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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

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Authors: Sujoy Anirudha Das, Albert Thomas

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Building sector is a major consumer of energy globally, and it has corresponding effects to the environment with respect to the carbon emissions. Given the fact that India is expected to add 40-billion square meter of new buildings till 2050, we need frameworks that help in reducing the overall energy consumption in the building sector. Even though several simulation-based frameworks that help in analyzing the building energy consumption are developed globally, in the Indian context, to the best of our knowledge, there is a lack of a comprehensive, yet user-friendly framework to simulate and optimize the effects of various energy influencing factors, specifically for Indian buildings. Therefore, this study is aimed at developing a simulation-based optimization framework to model the energy interactions in different types of Indian buildings by considering the dynamic nature of various energy influencing factors. This comprehensive framework can be used by various building stakeholders to test the energy effects of different factors such as, but not limited to, the various building materials, the orientation, the weather fluctuations, occupancy changes and the type of the building (e.g., office, residential). The results from the case study involving several building types would help us in gaining insights to build new energy-efficient buildings as well as retrofit the existing structures in a more convenient way to consume less energy, exclusively for an Indian scenario.

Keywords: building energy consumption, building energy simulations, energy efficient buildings, optimization framework

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

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In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Magdalena Kuleta

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Ponta de Piedade (37º05 ' N, 08º40 ' W) is an area located in the southern part of the Lagos municipality, which include an abrasive and accumulative type of coastline. It is the one of the main touristic destinations of the city. The dynamic development of the attractiveness of the coast, is related with the expansion of the new tourism infrastructure and urban tourism products. These products are: transportation, sightseeing and entertainment in the form of the boat trips. Each type of excursion refers to the different product. This progress brings also many risks associated primarily with landslides cliffs. Natural conditions affecting the coast, create a huge impact on the evolution of urban tourism management. Based on observation, statistical analysis and survey method, author compare the period of six years from 2012 to 2016 in terms of the number of tourists, number and diversity of attractions, most frequently dialled products and infrastructure changes in the city. Carried methodology is based on data belonging to Turismo Portugal and the tourist company Days of Adventure. Main result, is to indicate the essence of the income from coastal tourism into the city development and how does it influence on the marketing and promoting of urban tourism in Lagos.

Keywords: geomorphology of the coast in Lagos, market and promotion, quality of tourism service, urban tourism products

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Babak Safaei, A. M. Fattahi

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In the present study we have investigated axial buckling characteristics of nanocomposite beams reinforced by single-walled carbon nanotubes (SWCNTs). Various types of beam theories including Euler-Bernoulli beam theory, Timoshenko beam theory and Reddy beam theory were used to analyze the buckling behavior of carbon nanotube-reinforced composite beams. Generalized differential quadrature (GDQ) method was utilized to discretize the governing differential equations along with four commonly used boundary conditions. The material properties of the nanocomposite beams were obtained using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites which were embedded by amorphous polyethylene matrix. Then the results obtained directly from MD simulations were matched with those calculated by the mixture rule to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results were presented to indicate the influences of nanotube volume fractions and end supports on the critical axial buckling loads of nanocomposite beams relevant to long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, axial buckling, generalized differential quadrature (GDQ)

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Authors: Staņislavs Gendelis, Andris Jakovičs, Jānis Ratnieks, Aigars Laizāns, Dāvids Vardanjans

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Dehumidification of biogas at the biomass plants is very important to provide the energy efficient burning of biomethane at the outlet. A few methods are widely used to reduce the water content in biogas, e.g. chiller/heat exchanger based cooling, usage of different adsorbents like PSA, or the combination of such approaches. A quite different method of biogas dehumidification is offered and analyzed in this paper. The main idea is to direct the flow of biogas from the plant around it downwards; thus, creating additional insulation layer. As the temperature in gas shell layer around the plant will decrease from ~ 38°C to 20°C in the summer or even to 0°C in the winter, condensation of water vapor occurs. The water from the bottom of the gas shell can be collected and drain away. In addition, another upward shell layer is created after the condensate drainage place on the outer side to further reducing heat losses. Thus, counterflow biogas heat exchanger is created around the biogas plant. This research work deals with the numerical modelling of biogas flow, taking into account heat exchange and condensation on cold surfaces. Different kinds of boundary conditions (air and ground temperatures in summer/winter) and various physical properties of constructions (insulation between layers, wall thickness) are included in the model to make it more general and useful for different biogas flow conditions. The complexity of this problem is fact, that the temperatures in both channels are conjugated in case of low thermal resistance between layers. MATLAB programming language is used for multiphysical model development, numerical calculations and result visualization. Experimental installation of a biogas plant’s vertical wall with an additional 2 layers of polycarbonate sheets with the controlled gas flow was set up to verify the modelling results. Gas flow at inlet/outlet, temperatures between the layers and humidity were controlled and measured during a number of experiments. Good correlation with modelling results for vertical wall section allows using of developed numerical model for an estimation of parameters for the whole biogas dehumidification system. Numerical modelling of biogas counterflow heat exchanger system placed on the plant’s wall for various cases allows optimizing of thickness for gas layers and insulation layer to ensure necessary dehumidification of the gas under different climatic conditions. Modelling of system’s defined configuration with known conditions helps to predict the temperature and humidity content of the biogas at the outlet.

Keywords: biogas dehumidification, numerical modelling, condensation, biogas plant experimental model

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Salim Khan

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The attainment of the carbon neutrality objective and Sustainable Development Goal 13 (SDG-13) target, which pertains to climate actions, received widespread attention in developing and emerging nations. Given the increasing pace of urbanization, technological advancements, and rapid growth, it is imperative to examine the linear and nonlinear effects of urbanization and economic growth and the linear impact of information and communication technology (ICT) on carbon emissions (CO2e). This study employs the Dynamic System GMM (DSGMM) and Panel Quantile Regression (PQR) methodologies to investigate the causal relationship between urbanization, ICT, economic growth, and their interplay on CO2e in 39 BRI countries from 2001 to 2020. The study's findings indicate that the impact of urbanization on CO2e exhibits linear and nonlinear patterns. The specific nonlinear impact of urbanization leads to a decrease in CO2e, hence facilitating the achievement of carbon neutrality and contributing to SDG-13. The study highlights the importance of ICT in achieving SDG-13 by reducing CO2e, emphasizing the need for informatization. Simultaneously, the findings support the Environmental Kuznets Curve (EKC) hypothesis and support the pollution haven theory. Finally, based on empirical findings, significant policy implications are suggested for achieving SGD 13 and carbon neutrality.

Keywords: urbanization, ICT, CO2 emission, EKC, pollution haven, BRI

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Authors: Layal Mansour

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This paper breaks down Egypt’s financial crisis by constructing a customized financial stress index by including the vulnerable economic indicator “dollarization” as a vulnerable indicator in the credit and exchange sector. The Financial Stress Index for Egypt (FSIE) includes informative vulnerable indicators of the main financial sectors: the banking sector, the equities market, and the foreign exchange market. It is calculated on a monthly basis from 2010 to December 2022, so to report the two recent world’s most devastating financial crises: Covid 19 crisis and Ukraine-Russia War, in addition to the local 2016 and 2022 financial crises. We proceed first by a graphical analysis then by empirical analysis in running under Vector Autoregression (VAR) Model, dynamic causality tests between foreign reserves, dollarization rate, and FSIE. The graphical analysis shows that unexpectedly, Egypt’s economy seems to be immune to internal economic/political instabilities, however it is highly exposed to the foreign and exchange market. Empirical analysis confirms the graphical observations and proves that dollarization, or more precisely debt in foreign currency seems to be the main trigger of Egypt’s current financial crisis.

Keywords: egypt, financial crisis, financial stress index, dollarization, VAR model, causality tests

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Authors: M. Orefice, V. Di Vito

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This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: ADS-B Based Application, Collision Avoidance, RPAS, Spiral Geometry.

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Authors: Adeyemi Kamil Hamzah

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The contiguity of nations in international system suggests that world is a composite of socio-economic unit with people exploring and exploiting the potentials in the world via migrations. Thus, cross border migration has made positive contributions to social and economic development of individuals and nations by increasing the household incomes of the host countries. However, the cross border migrations in West Africa are becoming part of a dynamic and unstable world migration system. This is due to the nature and consequences of trans-border crimes in West Africa, with both short and long term effects on the socio-economic viability of developing countries like West African States. The paper identified that migration influenced cross-border crimes as well as the high spate of insurgencies in the sub-region. Furthermore, the consequential effect of a global village has imbalanced population flows, making some countries host and parasites to others. Also, stern and deft cross-border rules and regulations, as well as territorial security and protections, ameliorate cross border crimes and migration in West African sub-regions. Therefore, the study concluded that cross border migration is the linchpin of all kinds of criminal activities which affect the security of states in the sub-region.

Keywords: cross-border migration, border crimes, security, West Africa, development, globalisation

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Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: social platforms, buyer behavior, consumer behavior, digital era

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Authors: Odd Ivar Haugen

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Society increasingly relies on complex systems whose behaviour is determined, not by the properties of each part, but by the interaction between them. The behaviour of such systems is emergent. Modelling emergent system behaviour requires a systems approach that incorporates the necessary concepts that are capable of determining such behaviour. The CESM metamodel is a model of system models. A set of system models needs to address the elements of CESM at different levels of abstraction to be able to model the behaviour of a complex system. Modern ships contain numerous sophisticated equipment, often accompanied by a local safety system to protect its integrity. These control systems are then connected into a larger integrated system in order to achieve the ship’s objective or mission. The integrated system becomes what is commonly known as a system of systems, which can be termed a complex system. Examples of such complex systems are the dynamic positioning system and the power management system. Three ship accidents are provided as examples of how system complexity may contribute to accidents. Then, the three accidents are discussed in terms of how the Multi-Level/Multi-Model Safety Analysis might catch scenarios such as those leading to the accidents described.

Keywords: emergent properties, CESM metamodel, multi-level/multi-model safety analysis, safety, system complexity, system models, systems thinking

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Authors: Okwan Frank

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Maternal health outcome is one of the major population development challenges in Sub-Saharan Africa. The region has the highest maternal mortality ratio, despite the progressive economic growth in the region during the global economic crisis. It has been hypothesized that increase in economic growth will reduce the level of maternal mortality. The purpose of this study is to investigate the existence of the negative relationship between health outcome proxy by maternal mortality ratio and economic growth in Sub-Saharan Africa. The study used the Pooled Mean Group estimator of ARDL Autoregressive Distributed Lag (ARDL) and the Kao test for cointegration to examine the short-run and long-run relationship between maternal mortality and economic growth. The results of the cointegration test showed the existence of a long-run relationship between the variables considered for the study. The long-run result of the Pooled Mean group estimates confirmed the hypothesis of an inverse relationship between maternal health outcome proxy by maternal mortality ratio and economic growth proxy by Gross Domestic Product (GDP) per capita. Thus increasing economic growth by investing in the health care systems to reduce pregnancy and childbirth complications will help reduce maternal mortality in the sub-region.

Keywords: economic growth, maternal mortality, pool mean group, Sub-Saharan Africa

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Authors: Moshe Leiba, Doron Zohar

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Computer Science (CS) and programming is still considered a boy’s club and is a male-dominated profession. This is also the case in high schools and higher education. In Israel, not different from the rest of the world, there are less than 35% of female students in CS studies that take the matriculation exams. The Israeli matriculation exams are written in a masculine form language. Gender-fair language (GFL) aims at reducing gender stereotyping and discrimination. There are several strategies that can be employed to make languages gender-fair and to treat women and men symmetrically (especially in languages with grammatical gender, among them neutralization and using the plural form. This research aims at exploring computer science teachers’ beliefs regarding the use of gender-fair language in exams. An exploratory quantitative research methodology was employed to collect the data. A questionnaire was administered to 353 computer science teachers. 58% female and 42% male. 86% are teaching for at least 3 years, with 59% of them have a teaching experience of 7 years. 71% of the teachers teach in high school, and 82% of them are preparing students for the matriculation exam in computer science. The questionnaire contained 2 matriculation exam questions from previous years and open-ended questions. Teachers were asked which form they think is more suited: (a) the existing form (mescaline), (b) using both gender full forms (e.g., he/she), (c) using both gender short forms, (d) plural form, (e) natural form, and (f) female form. 84% of the teachers recognized the need to change the existing mescaline form in the matriculation exams. About 50% of them thought that using the plural form was the best-suited option. When examining the teachers who are pro-change and those who are against, no gender differences or teaching experience were found. The teachers who are pro gender-fair language justified it as making it more personal and motivating for the female students. Those who thought that the mescaline form should remain argued that the female students do not complain and the change in form will not influence or affect the female students to choose to study computer science. Some even argued that the change will not affect the students but can only improve their sense of identity or feeling toward the profession (which seems like a misconception). This research suggests that the teachers are pro-change and believe that re-formulating the matriculation exams is the right step towards encouraging more female students to choose to study computer science as their major study track and to bridge the gap for gender equality. This should indicate a bottom-up approach, as not long after this research was conducted, the Israeli ministry of education decided to change the matriculation exams to gender-fair language using the plural form. In the coming years, with the transition to web-based examination, it is suggested to use personalization and adjust the language form in accordance with the student's gender.

Keywords: compter science, gender-fair language, teachers, national exams

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Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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Authors: Faride Crespo Razeg, Beatriz Eugenia Rivera Pedroza

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While Colombian’s society has changed, the way that Colombian’s civil society participates has changed too. Thus, the social movements as a form of participation should be research to understand as the society structure as the groups’ interactions. In fact, in the last decades, the social movements in Colombia have been transformed in three categories: actors, spaces, and demands. For this reason, it is important to know from what perspectives have been researched this topic, allowing to recognize an epistemological and ontological reflections of it. The goal of this research has been characterizing the social movements of Cali – Colombia between 2002 and 2016. Cali is the southwest largest Colombian city; for this reason, it could be considered as a representative data for the social dynamic of the region. Qualitative methods as documental analysis have been used, in order to know the way that the research on social movements has been done. Thus taking into account this methodological technique, it has been found the goals that are present in most of the studies, which represents what are the main concerns around this topic. Besides, the methodology more used, to understand the way that the data was collected, its problems and its advantages. Finally, the ontological and epistemological reflections are important to understand which have been the theory and conceptual approach of the studies and how its have been contextualized to Cali, taking into account its own history.

Keywords: social movements, civil society, forms of participation, collective actions

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Authors: Ali Kadivar, Kaveh Niayesh

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MVDC markets for green power generations, Navy, subsea oil and gas electrification, and transportation electrification are extending rapidly. The lack of fast and powerful DC circuit breakers (CB) is the most significant barrier to realizing the medium voltage DC (MVDC) networks. A concept of hybrid circuit breakers (HCBs) benefiting from ultrafast disconnectors (UFD) is proposed. A set of mechanical switches substitute the power electronic commutation switches to reduce the losses during normal operation in HCB. The success of current commutation in such breakers relies on the behaviour of elongated, wall constricted arcs during the opening across the contacts inside the UFD. The arc voltage dependencies on the contact speed of UFDs is discussed through multiphysics simulations contact opening speeds of 10, 20 and 40 m/s. The arc voltage at a given current increases exponentially with the contact opening velocity. An empirical equation for the dynamic arc characteristics is presented for the tested UFD, and the experimentally verfied characteristics for voltage-current are utilized for the current commutation simulation prior to apply on a 14 kV experimental setup. Different failures scenarios due to the current commutation are investigated

Keywords: MVDC breakers, DC circuit breaker, fast operating breaker, ultra-fast elongated arc

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Authors: Pascal Alberti, Mustapha Mouloua

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In today’s global market economy, various companies are often confronted with the dynamic and complex nature of current competitive markets. The dynamics of these markets are becoming more and more fluid, often requiring companies to provide competitive, definite advantages, and technological responses within increasingly shorte time frames. To meet these demands, companies must rely on the cognitive abilities of actors of creativity to provide tangible answers to the current contextual problems. Thus, it is important to provide a variety of instruments and design tools to support this particular stage of innovation, and to meet their demand expectations. For a number of years now, we have been extensively conducting experiments on the use of mind maps in the context of innovative projects with collaborative research teams from various nationalities. Our research findings reported a significant difference between a “Word” Mind Map and “Photographic” Mind Map, a correlation between the different uses of iconic tools and certain types of innovation, and a relationship between the different cognitive logics. In this paper, we will present our new results related to the effect of symmetrical presentation of a Photographic Mind Map" on the production of design solutions. Finally, we will conclude by highlighting the importance of our experimental method, and discussing both the theoretical and practical implications of our research.

Keywords: creativity, innovation, management, mind mapping, design product

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Dae-gun Kim, Hyun-joo Kang

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Purpose: The purpose of this study was to investigate the effects of aging on center of pressure, gait angle and gait time. Methods: 29 healthy female college students(FCS) and 28 elderly women (EW) were recruited to participate in this study. A gait analysis system( Gaitview, Korea) was used to collect the center of pressure in static state and gait angle with gait time in dynamic state. Results: Results of the center of pressure do not have significant differences between two groups. In the gait angle test, the FCS showed 1.56±5.2° on their left while the EW showed 9.76±6.54° on their left. In their right, the FCS showed 2.85±6.47° and the EW showed 10.27±6.97°. In the gait angle test, there was a significant difference in the gait time between the female college students and elderly women. A significant difference was evident in the gait time. The FCS on the left was 0.87±0.1sec while the EW’s was 1.28±0.44sec. The FCS on the right was 0.86±0.09sec and the EW was 1.1±0.21sec. The results of this study revealed that the elderly participants aging musculoskeletal system and subsequent changes in their posture altered gait angle and gait time. Therefore, this widening is due to their need to leave their feet on the ground longer for stability slowing their movement. Conclusions: In conclusion, it is advisable to develop an exercise program for the elderly focusing on stability the prevention of falls.

Keywords: center of pressure, gait angle, gait time, elderly women

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Authors: Lisa J. Piergallini

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This project uses panel regression analyses to investigate the relationships between geography, institutions, and economic development, as guided by the theories of the 18^th century French philosopher Montesquieu. Contemporary scholars of political economy perpetually misinterpret Montesquieu’s theories on climate, and in doing so they miss what could be the key to resolving the geography vs. institutions debate. There is a conspicuous gap in this literature, in that it does not consider whether geography and institutors might have an interactive, dynamic effect on economic development. This project seeks to bridge that gap. Data are used for all available countries over the years 1980-2013. Two interaction terms between geographic and institutional variables are employed within the empirical analyses, and these offer a unique contribution to the ongoing geography vs. institutions debate within the political economy literature. This study finds that there is indeed an interactive effect between geography and institutions, and that this interaction has a statistically significant effect on economic development. Democracy (as measured by Polity score) and rule of law and property rights (as measured by the Fraser index) have positive effects on economic development (as measured by GDP per capita), yet the magnitude of these effects are stronger in contexts where a low percent of the national population lives in the geographical tropics. This has implications for promoting economic development, and it highlights the importance of understanding geographical context.

Keywords: Montesquieu, institutions, geography, economic development, political philosophy, political economy

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Authors: Priya Kedia, Kiranmoy Das

Abstract:

There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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