Search results for: conditional proportional reversed hazard rate model

Authors: Imran Badshah

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Pedestrian service time reflects the performance of the facility, and it’s a key parameter to analyze the capability of facilities provided to serve pedestrians. The level of service of pedestrians (LOS) mainly depends on pedestrian time and safety. The pedestrian time utilized by taking a service is mainly influenced by the number of available services and the time utilized by each pedestrian in receiving a service; that is called a delay time. In this paper, we analyzed the simulated pedestrian service time with different delay times. A simulation is performed in AnyLogic by developing a model that reflects the real scenario of pedestrian services such as ticket machine gates at rail stations, airports, shopping malls, and cinema halls. The simulated pedestrian time is determined for various delay values. The simulated result shows how pedestrian time changes with the delay pattern. The histogram and time plot graph of a model gives the mean, maximum and minimum values of the pedestrian time. This study helps us to check the behavior of pedestrian time at various services such as subway stations, airports, shopping malls, and cinema halls.

Keywords: agent-based simulation, anylogic model, pedestrian behavior, time delay

Procedia PDF Downloads 216

Authors: J. Harrison Kurunathan, R. Jayaparvathy

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"Assistive Robotics" is the field that deals with the study of robots that helps in human motion and also empowers human abilities by interfacing the robotic systems to be manipulated by human motion. The proposed model is a robotic arm that works as a haptic interface on the basis on accelerometers and DC motors that will function with respect to the movement of the human muscle. The proposed model would effectively work as a haptic interface that would reduce human effort in the field of defense and rescue. This can be used in very critical conditions like fire accidents to avoid causalities.

Keywords: accelerometers, haptic interface, servo motors, signal processing

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Authors: Vojtěch Svěrák

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Climate change ethics have recently shifted away from individualistic paradigms towards concepts of shared or collective responsibility. Despite this evolving trend, a noticeable gap remains: a lack of research exclusively addressing the moral responsibility of specific unorganized social groups. The primary objective of the article is to fill this gap. The article employs the structuralist methodological approach proposed by some feminist philosophers, utilizing structural analysis to explain the existence of social groups. The argument is made for the integration of this framework with the so-called forward-looking Social Connection Model (SCM) of responsibility, which ascribes responsibilities to individuals based on their participation in social structures. The article offers an extension of this model to justify the responsibility of unorganized social groups. The major finding of the study is that although members of unorganized groups are loosely connected, collectively they instantiate specific external social structures, share social positioning, and the notion of responsibility could be based on that. Specifically, if the structure produces harm or perpetuates injustices, and the group both benefits from and possesses the capacity to significantly influence the structure, a greater degree of responsibility should be attributed to the group as a whole. This thesis is applied and justified within the context of climate change, based on the asymmetrical positioning of different social groups. Climate change creates a triple inequality: in contribution, vulnerability, and mitigation. The study posits that different degrees of group responsibility could be drawn from these inequalities. Two social groups serve as a case study for the article: first, the Pakistan lower class, consisting of people living below the national poverty line, with a low greenhouse gas emissions rate, severe climate change-related vulnerability due to the lack of adaptation measures, and with very limited options to participate in the mitigation of climate change. Second, the so-called polluter elite, defined by members' investments in polluting companies and high-carbon lifestyles, thus with an interest in the continuation of structures leading to climate change. The first identified group cannot be held responsible for climate change, but their group interest lies in structural change and should be collectively maintained. On the other hand, the responsibility of the second identified group is significant and can be fulfilled by a justified demand for some political changes. The proposed approach of group responsibility is suggested to help navigate climate justice discourse and environmental policies, thus helping with the sustainability transition.

Keywords: collective responsibility, climate justice, climate change ethics, group responsibility, social ontology, structural analysis

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy (ECRGE) strategy focuses mainly on generating and proper utilization of renewable energy (RE). Nonetheless, the current electricity generation of the country is dominated by hydropower. The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources from solar and wind energy were only 8 %. On the other hand, the EEP electricity generation plan in 2030 indicates that 36.1 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the EnergyPLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EnergyPLAN (EP) analysis for two predictive scenarios. The EP simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EP simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was in the three rainy months of the year (June, July, and August). The outcome of the model also showed that in the dry seasons of the year, there would be excess power production in the country. Consequently, based on the validated outcomes of EP indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that if the excess power is utilized with a storage system, it can stabilize the grid system and be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming storage system to synchronize with potentials that can be generated from renewable energy.

Keywords: renewable energy, power, storage, wind, energy plan

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Authors: Gyeongbeom Yi

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The purpose of this study is to introduce the analytic solution for determining the optimal capacity (lot-size) of a multiproduct, multistage production and inventory system to meet the finished product demand. Reasonable decision-making about the capacity of processes and storage units is an important subject for industry. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ/EPQ (Economic Order Quantity/Economic Production Quantity) model, incorporated with practical experience. However, the unrealistic material flow assumption of the EOQ/EPQ model is not suitable for chemical plant design with highly interlinked processes and storage units. This study overcomes the limitation of the classical lot sizing method developed on the basis of the single product and single stage assumption. The superstructure of the plant considered consists of a network of serially and/or parallelly interlinked processes and storage units. The processes involve chemical reactions with multiple feedstock materials and multiple products as well as mixing, splitting or transportation of materials. The objective function for optimization is minimizing the total cost composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis method, PSW (Periodic Square Wave) model, is applied. The advantage of the PSW model comes from the fact that the model provides a set of simple analytic solutions in spite of a realistic description of the material flow between processes and storage units. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for plant design and operation problem confronted in diverse economic situations.

Keywords: analytic solution, optimal design, process-storage network

Procedia PDF Downloads 335

Authors: Brahim Brahmi, Mohammed Hamza Laraki, Mohammad Habibur Rahman, Islam M. Rasedul, M. Assad Uz-Zaman

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The humanoid robot, specifically the NAO robot must be able to provide a highly dynamic performance on the soccer field. Maintaining the balance of the humanoid robot during the required motion is considered as one of a challenging problems especially when the robot is subject to external disturbances, as contact with other robots. In this paper, a dynamic controller is proposed in order to ensure a robust walking (stabilization) and to improve the dynamic balance of the robot during its contact with the environment (external disturbances). The generation of the trajectory of the center of mass (CoM) is done by a model predictive controller (MPC) conjoined with zero moment point (ZMP) technique. Taking into account the properties of the rotational dynamics of the whole-body system, a modified previous control mixed with feedback control is employed to manage the angular momentum and the CoM’s acceleration, respectively. This latter is dedicated to provide a robust gait of the robot in the presence of the external disturbances. Simulation results are presented to show the feasibility of the proposed strategy.

Keywords: preview control, Nao robot, model predictive control

Procedia PDF Downloads 130

Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

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We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: Yuanhao Gao, Ping Lin, Kees Weijer

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An optimal control system model is proposed for the cell flow in the process of chick embryo gastrulation in this paper. The target is to determine the cellular interaction forces which are hard to measure. This paper will take an approach to investigate the forces with the idea of the inverse problem. By choosing the forces as the control variable and regarding the cell flow as Stokes fluid, an objective functional will be established to match the numerical result of cell velocity with the experimental data. So that the forces could be determined by minimizing the objective functional. The Lagrange multiplier method is utilized to derive the state and adjoint equations consisting the optimal control system, which specifies the first-order necessary conditions. Finite element method is used to discretize and approximate equations. A conjugate gradient algorithm is given for solving the minimum solution of the system and determine the forces.

Keywords: optimal control model, Stokes equation, conjugate gradient method, finite element method, chick embryo gastrulation

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Authors: Alireza Dantism

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Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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Authors: Mario A. Blanco, Nicholas Burkhardt

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An important problem in satellite communication systems which operate in the Ka and EHF frequency bands consists of the overall degradation in link performance of mobile terminals due to various types of degradations in the link/channel, such as fading, blockage of the link to the satellite (especially in urban environments), intentional as well as other types of interference, etc. In this paper, we focus primarily on the interference problem, and we develop a very efficient and cost-effective solution based on the use of fountain codes. We first introduce a satellite communications (SATCOM) terminal uplink interference channel model that is classically used against communication systems that use spread-spectrum waveforms. We then consider the use of fountain codes, with focus on Raptor codes, as our main mitigation technique to combat the degradation in link/receiver performance due to the interference signal. The performance of the receiver is obtained in terms of average probability of bit and message error rate as a function of bit energy-to-noise density ratio, Eb/N0, and other parameters of interest, via a combination of analysis and computer simulations, and we show that the use of fountain codes is extremely effective in overcoming the effects of intentional interference on the performance of the receiver and associated communication links. We then show this technique can be extended to mitigate other types of SATCOM channel degradations, such as those caused by channel fading, shadowing, and hard-blockage of the uplink signal.

Keywords: SATCOM, interference mitigation, fountain codes, turbo codes, cross-layer

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Authors: S. Chuenchooklin

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This research was conducted in the Lower Ping River Basin downstream of the Bhumibol Dam and the Lower Wang River Basin in Tak Province, Thailand. Most of the tributary streams of the Ping can be considered as ungauged catchments. There are 10- pumping station installation at both river banks of the Ping in Tak Province. Recently, most of them could not fully operate due to the water amount in the river below the level that would be pumping, even though included water from the natural river and released flow from the Bhumibol Dam. The aim of this research was to increase the performance of those pumping stations using weir projects in the Ping. Therefore, the river analysis system model (HEC-RAS) was applied to study the hydraulic behavior of water surface profiles in the Ping River with both cases of existing conditions and proposed weirs during the violent flood in 2011 and severe drought in 2013. Moreover, the hydrologic modeling system (HMS) was applied to simulate lateral streamflow hydrograph from ungauged catchments of the Ping. The results of HEC-RAS model calibration with existing conditions in 2011 showed best trial roughness coefficient for the main channel of 0.026. The simulated water surface levels fitted to observation data with R2 of 0.8175. The model was applied to 3 proposed cascade weirs with 2.35 m in height and found surcharge water level only 0.27 m higher than the existing condition in 2011. Moreover, those weirs could maintain river water levels and increase of those pumping performances during less river flow in 2013.

Keywords: HEC-RAS, HMS, pumping stations, cascade weirs

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

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Authors: Hans Marquez Ramos, Cesar Hernandez, Ingrid Páez

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This paper develops a multiple channel assignment model, which allows to take advantage in most efficient way, spectrum opportunities in cognitive radio networks. Developed scheme allows make several available and frequency adjacent channel assignments, which require a bigger wide band, under an equality environment. The hybrid assignment model it is made by to algorithms, one who makes the ranking and select available frequency channels and the other one in charge of establishing an equality criteria, in order to not restrict spectrum opportunities for all other secondary users who wish to make transmissions. Measurements made were done for average bandwidth, average delay, as well fairness computation for several channel assignment. Reached results were evaluated with experimental spectrum occupational data from GSM frequency band captured. Developed model, shows evidence of improvement in spectrum opportunity use and a wider average transmit bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: bandwidth, fairness, multichannel, secondary users

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Authors: Ali Asghar Memon

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The simulation modeling of switched reluctance (SR) machine often relies and uses the three data tables identified as static torque characteristics that include flux linkage characteristics, co energy characteristics and static torque characteristics separately. It has been noticed from the literature that the data of static torque used in the simulation model is often calculated so far the literature is concerned. This paper presents the simulation model that include the data of measured and calculated static torque separately to see its effect on instantaneous torque profile of the machine. This is probably for the first time so far the literature review is concerned that static torque from co energy information, and measured static torque directly from experiments are separately used in the model. This research is helpful for accurate modeling of switched reluctance drive.

Keywords: static characteristics, current chopping, flux linkage characteristics, switched reluctance motor

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: William Kerua

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The PNG University of Technology (Unitech) has mandatory access to teaching, research and extension education. Given such function, the Agriculture Department has established the ‘South Pacific Institute of Sustainable Agriculture and Rural Development (SPISARD)’ in 2004. SPISARD is established as a vehicle to improve farming systems practiced in selected villages by undertaking pluralistic extension method through ‘Educational Institutional Approach’. Unlike other models, SPISARD’s educational institutional approach stresses on improving the whole farming systems practiced in a holistic manner and has a two-fold focus. The first is to understand the farming communities and improve the productivity of the farming systems in a sustainable way to increase income, improve nutrition and food security as well as livelihood enhancement trainings. The second is to enrich the Department’s curriculum through teaching, research, extension and getting inputs from farming community. SPISARD has established number of model villages in various provinces in Papua New Guinea (PNG) and with many positive outcome and success stories. Adaption of ‘educational institutional approach’ thus binds research, extension and training into one package with the use of students and academic staff through model village establishment in delivering development and extension to communities. This centre (SPISARD) coordinates the activities of the model village programs and linkages. The key to the development of the farming systems is establishing and coordinating linkages, collaboration, and developing partnerships both within and external institutions, organizations and agencies. SPISARD has a six-point step strategy for the development of sustainable agriculture and rural development. These steps are (i) establish contact and identify model villages, (ii) development of model village resource centres for research and trainings, (iii) conduct baseline surveys to identify problems/needs of model villages, (iv) development of solution strategies, (v) implementation and (vi) evaluation of impact of solution programs. SPISARD envisages that the farming systems practiced being improved if the villages can be made the centre of SPISARD activities. Therefore, SPISARD has developed a model village approach to channel rural development. The model village when established become the conduit points where teaching, training, research, and technology transfer takes place. This approach is again different and unique to the existing ones, in that, the development process take place in the farmers’ environment with immediate ‘real time’ feedback mechanisms based on the farmers’ perspective and satisfaction. So far, we have developed 14 model villages and have conducted 75 trainings in 21 different areas/topics in 8 provinces to a total of 2,832 participants of both sex. The aim of these trainings is to directly participate with farmers in the pursuit to improving their farming systems to increase productivity, income and to secure food security and nutrition, thus to improve their livelihood.

Keywords: development, educational institutional approach, livelihood improvement, sustainable agriculture

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Authors: Riccardo Houngbegnon, Loic Chrislin Nguedjio, Valery Doko, José Xavier, Miran Merhar, Rostand Moutou Pitti

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Against a backdrop of heightened awareness of environmental impact and the reduction of space debris, the use of sustainable materials for mobility applications is emerging as a promising solution to minimize the environmental footprint of our technologies. Among recent innovative developments in the use of wood, the Japanese species Magnolia obovata attracted particular interest when it was used in the design of the first wooden satellite launched in November 2024. The aim of this project is to explore new species that could replace M. obovata in a mobile context. Khaya ivorensis, a tropical African species, was selected and compared to M. obovata in terms of resistance to cracking, a key criterion in the durability of mobility infrastructures. Prior to the cracking tests, K. ivorensis and M. obovata were characterized to determine their basic mechanical properties. The results presented here relate to this characterization phase, in particular the four-point bending, compression and BING tests, which provided us with strengths and moduli. These results were compared with those found in the literature, which allowed us to observe a number of differences. CHARPY resilience tests were also performed and compare to critical energy release rate in order to estimate the ability of the two species to absorb energy, particularly following impacts and various shocks.

Keywords: energy release rate, Khaya ivorensis, magnolia obovata, wood for mobility

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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Authors: Samiha Ramdani, Abdelhamid Geuttala

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There is no doubt that the batteries increasingly used tires create environmental concerns. Algeria generates large amounts of by industrial and household waste, such as used tires and colored glass bottles and dishes, whose valuation in cementitious materials could be an interesting ecological and economical alternative for broadening eliminating cumbersome landfills. This work is a contribution to the promotion of local materials with the use of waste tires and glass bottle in the development of a new cementitious composite having the acceptable compressive strength and a capacity of improved strains. For this purpose, rubber crumb (GC) from shredding used tires were used as partial replacement of quarry sand with 10%, 20%, 40, 60%. In addition, some mixtures also contain glass powder at15% cement replacement by volume. The compressive strength, tensile strength, deformability, the water permeability and penetration Inions chlorides are studied. As results; an acceptable compressive strength was obtained with the substitution rate of 10% and 20% by volume, the deformability of the composite increases with increased replacement rate. The addition of finely ground glass as a partial replacement of cement concrete increases the resistance to penetration of Inions chloride and reduce the water permeability thereof; then increases their durability.

Keywords: crumb rubber, deformability, compressive strength, finely ground glass, durability, behavior law

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Authors: Arum Kingsley Chinedu, Ugwuowo Fidelis Ifeanyi, Oranye Henrietta Ebele

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The Poisson regression model (PRM) is a nonlinear model that belongs to the exponential family of distribution. PRM is suitable for studying count variables using appropriate covariates and sometimes experiences the problem of multicollinearity in the explanatory variables and outliers on the response variable. This study aims to address the problem of multicollinearity and outliers jointly in a Poisson regression model. We developed an estimator called the robust modified jackknife PCKL parameter estimator by combining the principal component estimator, modified jackknife KL and transformed M-estimator estimator to address both problems in a PRM. The superiority conditions for this estimator were established, and the properties of the estimator were also derived. The estimator inherits the characteristics of the combined estimators, thereby making it efficient in addressing both problems. And will also be of immediate interest to the research community and advance this study in terms of novelty compared to other studies undertaken in this area. The performance of the estimator (robust modified jackknife PCKL) with other existing estimators was compared using mean squared error (MSE) as a performance evaluation criterion through a Monte Carlo simulation study and the use of real-life data. The results of the analytical study show that the estimator outperformed other existing estimators compared with by having the smallest MSE across all sample sizes, different levels of correlation, percentages of outliers and different numbers of explanatory variables.

Keywords: jackknife modified KL, outliers, multicollinearity, principal component, transformed M-estimator.

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Authors: Y. T. Ku, S. W. Chen, J. R. Wang, C. Shih, Y. F. Chang

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In order to respond the policy decision of non-nuclear homes, Tai Power Company (TPC) will provide the decommissioning project of Kuosheng Nuclear power plant (KSNPP) to meet the regulatory requirement in near future. In this study, the computational fluid dynamics (CFD) methodology has been employed to develop a flow prediction model for boiling water reactor (BWR) with upper pool under decommissioning stage. The model can be utilized to investigate the flow behavior as the vessel combined with upper pool and continuity cooling system. At normal operating condition, different parameters are obtained for the full fluid area, including velocity, mass flow, and mixing phenomenon in the reactor pressure vessel (RPV) and upper pool. Through the efforts of the study, an integrated simulation model will be developed for flow field analysis of decommissioning KSNPP under normal operating condition. It can be expected that a basis result for future analysis application of TPC can be provide from this study.

Keywords: CFD, BWR, decommissioning, upper pool

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Authors: Chun-Yu Chen, Kua-Rong Wu, Yu-Cheng Chen, Perng-Jy Tsai

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Cooking fumes are known containing polycyclic aromatic hydrocarbons (PAHs) and aldehydes, and some of them have been proven carcinogenic or possibly carcinogenic to humans. Considering their chronic health effects, long-term exposure data is required for assessing cooking workers’ lifetime health risks. Previous exposure assessment studies, due to both time and cost constraints, mostly were based on the cross-sectional data. Therefore, establishing a long-term exposure data has become an important issue for conducting health risk assessment for cooking workers. An approach was proposed in this study. Here, the generation rates of both PAHs and aldehydes from a cooking process were determined by placing a sampling train exactly under the under the exhaust fan under the both the total enclosure condition and normal operating condition, respectively. Subtracting the concentration collected by the former (representing the total emitted concentration) from that of the latter (representing the hood collected concentration), the fugitive emitted concentration was determined. The above data was further converted to determine the generation rates based on the flow rates specified for the exhaust fan. The determinations of the above generation rates were conducted in a testing chamber with a selected cooking process (deep-frying chicken nuggets under 3 L peanut oil at 200°C). The sampling train installed under the exhaust fan consisted respectively an IOM inhalable sampler with a glass fiber filter for collecting particle-phase PAHs, followed by a XAD-2 tube for gas-phase PAHs. The above was also used to sample aldehydes, however, installed with a filter pre-coated with DNPH, and followed by a 2,4-DNPH-cartridge for collecting particle-phase and gas-phase aldehydes, respectively. PAHs and aldehydes samples were analyzed by GC/MS-MS (Agilent 7890B), and HPLC-UV (HITACHI L-7100), respectively. The obtained generation rates of both PAHs and aldehydes were applied to the near-field/ far-field exposure model to estimate the exposures of cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration). For validating purposes, both PAHs and aldehydes samplings were conducted simultaneously using the same sampling train at both near-field and far-field sites of the testing chamber. The sampling results, together with the use of the mixed-effect model, were used to calibrate the estimated near-field/ far-field exposures. In the present study, the obtained emission rates were further converted to emission factor of both PAHs and aldehydes according to the amount of food oil consumed. Applying the long-term food oil consumption records, the emission rates for both PAHs and aldehydes were determined, and the long-term exposure databanks for cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration) were then determined. Results show that the proposed approach was adequate to determine the generation rates of both PAHs and aldehydes under various fan exhaust flow rate conditions. The estimated near-field/ far-field exposures, though were significantly different from that obtained from the field, can be calibrated using the mixed effect model. Finally, the established long-term data bank could provide a useful basis for conducting long-term exposure assessments for cooking workers exposed to PAHs and aldehydes.

Keywords: aldehydes, cooking oil fumes, long-term exposure assessment, modeling, polycyclic aromatic hydrocarbons (PAHs)

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Authors: Obed Asamoah

Abstract:

Forests are very vital for human survival and our well-being. During the past years, the world has taken an increasingly significant role in the modification of the global environment. The high rate of deforestation in Ghana is of primary national concern as the forests provide many ecosystem services and functions that support the country’s predominantly agrarian economy and foreign earnings. Ghana forest is currently major source of carbon sink that helps to mitigate climate change. Ghana forests, both the reserves and off-reserves, are under pressure of deforestation. The causes of deforestation are varied but can broadly be categorized into anthropogenic and natural factors. For the anthropogenic factors, increased wood fuel collection, clearing of forests for agriculture, illegal and poorly regulated timber extraction, social and environmental conflicts, increasing urbanization and industrialization are the primary known causes for the loss of forests and woodlands. Mineral exploitation in the forest areas is considered as one of the major causes of deforestation in Ghana. Mining activities especially mining of gold by both the licensed mining companies and illegal mining groups who are locally known as "gallantly mining" also cause damage to the nation's forest reserves. Several works have been conducted regarding the causes of the high rate of deforestation in Ghana, major attention has been placed on illegal logging and using forest lands for illegal farming and mining activities. Less emphasis has been placed on the timber production companies on their harvesting methods in the forests in Ghana and other activities that are carried out in the forest. The main objective of the work is to find out the harvesting methods and the activities of the timber production companies and their effects on the forests in Ghana. Both qualitative and quantitative research methods were engaged in the research work. The study population comprised of 20 Timber industries (Sawmills) forest areas of Ghana. These companies were selected randomly. The cluster sampling technique was engaged in selecting the respondents. Both primary and secondary data were employed. In the study, it was observed that most of the timber production companies do not know the age, the weight, the distance covered from the harvesting to the loading site in the forest. It was also observed that old and heavy machines are used by timber production companies in their operations in the forest, which makes the soil compact prevents regeneration and enhances soil erosion. It was observed that timber production companies do not abide by the rules and regulations governing their operations in the forest. The high rate of corruption on the side of the officials of the Ghana forestry commission makes the officials relax and do not embark on proper monitoring on the operations of the timber production companies which makes the timber companies to cause more harm to the forest. In other to curb this situation the Ghana forestry commission with the ministry of lands and natural resources should monitor the activities of the timber production companies and sanction all the companies that make foul play in their activities in the forest. The commission should also pay more attention to the policy “fell one plant 10” to enhance regeneration in both reserves and off-reserves forest.

Keywords: companies, deforestation, forest, Ghana, timber

Procedia PDF Downloads 207

Authors: Alireza Gholipour, Mergen H. Ghayesh, Anthony Zander, Stephen J. Nicholls, Peter J. Psaltis

Abstract:

A three-dimensional numerical model of an atherosclerotic coronary ‎artery is developed for the determination of high-risk situation and ‎hence heart attack prediction. Employing the finite element method ‎‎(FEM) using ANSYS, fluid-structure interaction (FSI) model of the ‎artery is constructed to determine the shear stress distribution as well ‎as the von Mises stress field. A flexible model for an atherosclerotic ‎coronary artery conveying pulsatile blood is developed incorporating ‎three-dimensionality, artery’s tapered shape via a linear function for ‎artery wall distribution, motion of the artery, blood viscosity via the ‎non-Newtonian flow theory, blood pulsation via use of one-period ‎heartbeat, hyperelasticity via the Mooney-Rivlin model, viscoelasticity ‎via the Prony series shear relaxation scheme, and micro-calcification ‎inside the plaque. The material properties used to relate the stress field ‎to the strain field have been extracted from clinical data from previous ‎in-vitro studies. The determined stress fields has potential to be used as ‎a predictive tool for plaque rupture and dissection.‎ The results show that stress concentration due to micro-calcification ‎increases the von Mises stress significantly; chance of developing a ‎crack inside the plaque increases. Moreover, the blood pulsation varies ‎the stress distribution substantially for some cases.‎

Keywords: atherosclerosis, fluid-structure interaction‎, coronary arteries‎, pulsatile flow

Procedia PDF Downloads 177

Authors: Parvin Abedi, Fatemeh Malchi, Mina Iravani, Elham Maraghi, Eesa Mohammadi, Najmieh Saadati

Abstract:

Background: Adolescent pregnancy has major health and social consequences and can lead to adverse maternal and neonatal outcomes. Objectives: The objective of this study was to evaluate the impact of group prenatal care (GPNC) of adolescents on their maternal and neonatal outcomes. Methods: In this study, 294 adolescent pregnant women (aged 15-19) were randomly assigned into two groups of prenatal care (n=147) and individual prenatal care (IPNC) (n=147). Participants in the intervention group received GPNC at 16-20 weeks of gestational age, while the control group received (IPNC). The data were analyzed using the Chi-square test, independent t-test, and linear and logistic tests. Results: As far as weight gain was concerned, 91.7% and 62.1% of the participants in the GPNC and IPNC groups had an appropriate weight gain during pregnancy, respectively OR 6.72 (95% CI 3.40, 13.26). In the GPNC group, 79.2% of participants had exclusive breastfeeding in the first 6 weeks after childbirth and while this rate was 49.7% in the IPNC group, OR 3.92 (95% CI 2.36, 6.64). Preterm birth was observed in 3.4% of the participants in the GPNC group as opposed to 9.5% in the IPNC group OR 6.17 (95% CI 0.73, 51.93). Conclusion: Adolescent women in GPNC have more appropriate weight gain and a higher rate of exclusive breastfeeding compared to adolescent women in IPNC. Group prenatal care could be considered a viable method of care for adolescent pregnant women.

Keywords: group prenatal car, adolescents pregnant women, pregnancy outcomes, neonatal outcomes

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Authors: Umar Adli Amran, Tan Choon Chek, Mohd Shahkhirat Norizan, Then Kek Hoe

Abstract:

Controlled release fertilizer (CRF) enables a regulated nutrients release for more efficient plant uptake compared to the normal granular fertilizer. It reduces nutrients loss via surface run-off and leaching, hence promotes sustainable agriculture. Although the performance of CRF in providing consistent and timely nutrients supply is well known, its expensive price limits it usage in a large scale plantation. This study is conducted to evaluate the properties and performance of bio-based polyurethane (PU)-coated CRF via laboratory and oil palm main nursery trial. The CRF is produced by coating of a normal commercial compound granular fertilizer from FGV Fertiliser Sdn. Bhd., namely Felda 10 (10.5-8-20-3+0.5B), and designated as CRF FGV10. Based on laboratory evaluation, the CRF FGV10 can sustain nutrients release for more than 6 months. Vegetative growth parameters such as girth size, palm height, third frond length, and the total number of fronds produced were recorded. Besides that, dry biomass of the oil palm seedlings was also determined. From the evaluation, it is proved that at 50% reduction of nutrients application rate and for only two times application (T3), CRF FGV10 enabled the oil palm seedlings to achieve similar vegetative growth with the control samples (T1). It is also proven that only PU-coated CRF FGV10 had allowed the reduction of fertilizer rate and application rounds.

Keywords: nutrition, oil palm seedlings, polyurethane, sustainable manuring, vegetative growth

Procedia PDF Downloads 66

Authors: Edward C. W. Chan, Benny C. F. Cheung

Abstract:

In the knowledge economy, the financial indicator is not the unique instrument to gauge the performance of a company. The role of intellectual capital contributing to the company performance is increasing. To measure the company performance due to intellectual capital, the value-added intellectual capital (VAIC) model is adopted to measure the intellectual capital utilisation efficiency of the subject companies. The purpose of this study is to review the readiness of measuring intellectual capital for the Hong Kong listed companies in the property development and property investment industry by using VAIC model. This study covers the financial reports from the representative Hong Kong listed property development companies and property investment companies in the period 2014-2019. The findings from this study indicated the industry is ready for IC measurement employing VAIC framework but not yet ready for using the extended VAIC model.

Keywords: intellectual capital, intellectual capital measurement, property development, property investment, Skandia navigator, VAIC

Procedia PDF Downloads 121

Authors: Gholamhassan Kakha, Mohsen Jami, Daniel Alex Merino Natorce

Abstract:

Sustainable development refers to the creation of a balance between the development and the environment too; it consists of three key principles namely environment, society and economy. These three parameters are related to each other and the imbalance occurs in each will lead to the disparity of the other parts. Mining is one of the most important tools of the economic growth and social welfare in many countries. Meanwhile, assessment of the environmental impacts has directed to the attention of planners toward the natural environment of the areas surrounded by mines and allowing for monitoring and controlling of the current situation by the designers. In this look upon, a semi-quantitative model using a matrix method is presented for assessing the environmental impacts in the BOOG Granite Mine located in Sistan and Balouchestan, one of the provinces of Iran for determining the effective factors and environmental components. For accomplishing this purpose, the initial data are collected by the experts at the next stage; the effect of the factors affects each environmental component is determined by specifying the qualitative viewpoints. Based on the results, factors including air quality, ecology, human health and safety along with the environmental damages resulted from mining activities in that area. Finally, the results gained from the assessment of the environmental impact are used to evaluate the sustainability by using Philips mathematical model. The results show that the sustainability of this area is weak, so environmental preventive measures are recommended to reduce the environmental damages to its components.

Keywords: sustainable development, environmental impacts' assessment, BOOG granite, Philips mathematical model

Procedia PDF Downloads 203

Authors: Thanura Randula Abeywardena

Abstract:

This study recognized the effectiveness of cold-water immersion recovery post exhaustive short-term exercise. The purpose of this study was to understand if 16- 20°C of cold-water immersion would be beneficial in a tropical environment to achieve optimal recovery in sprint swim performance in comparison to 10-15°C of water immersion. Two 100m-sprint swim performance times were measured along with blood lactate (BLa), heart rate (HR) and rate of perceived exertion (RPE) in a 25m swimming pool with full body head out horizontal water immersions of 10-15°C, 16-20°C and 29-32°C (pool temperature) for 10 minutes followed by 5 minutes of seated passive rest outside; in between the two swim performances. Twelve well-trained adult swimmers (5 male and 5 female) within the top twenty in the Sri Lankan national swimming championships in 100m Butterfly and Freestyle in the years 2020 & 2021 volunteered for this study. One-way ANOVA analysis (p<0.05) suggested performance time, Bla and HR had no significant differences between the 3 conditions after the second sprint; however, RPE was significantly different with p=0.034 between 10-15°C and 16-20°C immersion conditions. The study suggested that the recovery post the two cold-water immersion conditions were similar in terms of performance and physiological factors; however, the 16-20°C temperature had a better “feel good” factor post sprint 2. Further study is recommended as there was participant bias with the swimmers not reaching optimal levels in sprint 1. Therefore, they might have possibly fully recovered before sprint 2, invalidating the physiological effect of recovery.

Keywords: hydrotherapy, blood lactate, fatigue, recovery, sprint-performance, sprint-swimming

Procedia PDF Downloads 105