Search results for: prediction model accuracy

Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

Abstract:

Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

Procedia PDF Downloads 48

Authors: Qijiao He

Abstract:

MicroElectrical-Mechanical System (MEMS) is one of the most rapidly developing frontier research field both in theory study and applied technology. Micro-channel is a very important link component of MEMS. With the research and development of MEMS, the size of the micro-devices and the micro-channels becomes further smaller. Compared with the macroscale flow, the flow characteristics of gas in the micro-channel have changed, and the rarefaction effect appears obviously. However, for the rarefied gas and microscale flow, Navier-Stokes-Fourier (NSF) equations are no longer appropriate due to the breakup of the continuum hypothesis. A Nonlinear Coupled Constitutive Model (NCCM) has been derived from the Boltzmann equation to describe the characteristics of both continuum and rarefied gas flows. We apply the present scheme to simulate continuum and rarefied gas flows in a micro-channel structure. And for comparison, we apply other widely used methods which based on particle simulation or direct solution of distribution function, such as Direct simulation of Monte Carlo (DSMC), Unified Gas-Kinetic Scheme (UGKS) and Lattice Boltzmann Method (LBM), to simulate the flows. The results show that the present solution is in better agreement with the experimental data and the DSMC, UGKS and LBM results than the NSF results in rarefied cases but is in good agreement with the NSF results in continuum cases. And some characteristics of both continuum and rarefied gas flows are observed and analyzed.

Keywords: continuum and rarefied gas flows, discontinuous Galerkin method, generalized hydrodynamic equations, numerical simulation

Procedia PDF Downloads 176

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

Procedia PDF Downloads 299

Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

Abstract:

Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

Procedia PDF Downloads 254

Authors: Godwin Chigozie Okpara, Eugene Iheanacho

Abstract:

This paper examined the dynamic behavior of stock market development and the growth of Nigerian economy. The variables; market capitalization ratio, turnover ratio and liquidity proxies by the ratio of market capitalization to gross domestic product were sourced and computed from the Nigerian stock exchange fact books and the CBN statistical bulletin of the Central Bank of Nigeria. The variables were tested and found stationary and cointregrated using the augumented Dickey Fuller unit root test and the Johnson cointegration test respectively. The dynamic behavior of the stock market development model was verified using the error correction model. The result shows that about 0.4l percent of the short run deviation is corrected every year and also reveals that market capitalization ratio and market liquidity are positive and significant function of economic growth. In other words market capitalization ratio and liquidity positively and significantly impact economic growth. Market development variables such as turnover ratio and market restriction can exert positive but insignificant impact on the growth of the economy suggesting that securities transaction relative to the size of the securities market are not high enough to significantly engender economic growth in Nigeria. In the light of this, the researchers recommend that the regulatory body as well as the government, should provide a conducive environment capable of encouraging the growth and development of the stock market. This if well articulated will enhance the market turnover and the growth of the economy.

Keywords: market capitalization ratio, turnover ratio, liquidity, unit root test, cointegration

Procedia PDF Downloads 343

Authors: Mogens Saberi

Abstract:

The focus of this article is to present the experience gained from the design of a grouted pile-sleeve connection and to present simple design expressions which can be used in the preliminary design phase of such connections. The grout pile-sleeve connection serves as a connection between an offshore jacket foundation and pre-installed piles located in the seabed. The jacket foundation supports a wind turbine generator resulting in significant dynamic loads on the connection. The connection is designed with shear keys in order to optimize the overall design but little experience is currently available in the use of shear keys in such connections. It is found that the consequence of introducing shear keys in the design is a very complex stress distribution which requires special attention due to significant fatigue loads. An optimal geometrical shape of the shear keys is introduced in order to avoid large stress concentration factors and a relatively easy fabrication. The connection is analysed in ANSYS Mechanical where the grout is modelled by a non-linear material model which allows for cracking of the grout material and captures the elastic-plastic behaviour of the grout material. Special types of finite elements are used in the interface between the pile sleeve and the grout material to model the slip surface between the grout material and the steel. Based on the performed finite element modelling simple design expressions are introduced.

Keywords: fatigue design, non-linear finite element modelling, structural dynamics, simple design expressions

Procedia PDF Downloads 389

Authors: Michel A. Thomet

Abstract:

A discrete-event simulation model was used to perform a Reliability-Availability-Maintainability (RAM) study of a large petrochemical complex which included sixteen process units, and seven feeds and intermediate streams. All the feeds and intermediate streams have associated storage tanks, so that if a processing unit fails and shuts down, the downstream units can keep producing their outputs. This also helps the upstream units which do not have to reduce their outputs, but can store their excess production until the failed unit restart. Each process unit and each pipe section carrying the feeds and intermediate streams has a probability of failure with an associated distribution and a Mean Time Between Failure (MTBF), as well as a distribution of the time to restore and a Mean Time To Restore (MTTR). The utilities supporting the process units can also fail and have their own distributions with specific MTBF and MTTR. The model runs are for ten years or more and the runs are repeated several times to obtain statistically relevant results. One of the main results is the On-Stream factor (OSF) of each process unit (percent of hours in a year when the unit is running in nominal conditions). One of the objectives of the study was to investigate if the storage capacity of each of the feeds and the intermediate stream was adequate. This was done by increasing the storage capacities in several steps and through running the simulation to see if the OSF were improved and by how much. Other objectives were to see if the failure of the utilities were an important factor in the overall OSF, and what could be done to reduce their failure rates through redundant equipment.

Keywords: business continuity, on-stream factor, petrochemical, RAM study, simulation, MTBF

Procedia PDF Downloads 223

Authors: Justin Woulfe

Abstract:

Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

Procedia PDF Downloads 165

Authors: Qinglu Wu, Anna Wai-Man Choi, Peilian Chi

Abstract:

Gratitude is one individual strength that not only facilitates the mental health, but also fosters the relationship satisfaction in the romantic relationship. In terms of moral effect theory and stress-and-coping theory of forgiveness, present study not only investigated the association between grateful disposition and relationship satisfaction, but also explored the mechanism by comprehensively examining the potential mediating roles of three profiles of forgiveness (trait forgivingness, decisional forgiveness, emotional forgiveness), another character strength that highly related to the gratitude and relationship satisfaction. Structural equation modeling was used to conduct the multiple mediator model with a sample of 103 Chinese college students in dating relationship (39 male students and 64 female students, Mage = 19.41, SD = 1.34). Findings displayed that both gratitude and relationship satisfaction positively correlated with decisional forgiveness and emotional forgiveness. Emotional forgiveness was the only mediator, and it completely mediated the relationship between gratitude and relationship satisfaction. Gratitude was helpful in enhancing individuals’ perception of satisfaction in romantic relationship through replacing negative emotions toward partners with positive ones after transgression in daily life. It highlighted the function of emotional forgiveness in personal healing and peaceful state, which is important to the perception of satisfaction in relationship. Findings not only suggested gratitude could provide a stability for forgiveness, but also the mechanism of prosocial responses or positive psychological processes on relationship satisfaction. The significant roles of gratitude and emotional forgiveness could be emphasized in the intervention working on the romantic relationship development or reconciliation.

Keywords: decisional forgiveness, emotional forgiveness, gratitude, relationship satisfaction, trait forgivingness

Procedia PDF Downloads 276

Authors: Wan You Ning

Abstract:

Addressing the rising prevalence of mental health issues among youths, the Multi-dimensional Approach to Resilience and Support in Advanced School-based Mental Health Service Delivery (MARS-ASMHSD) framework proposes the implementation of advanced mental health services in low-resource areas to further instil mental health resilience among students in a school-based setting. Recognizing the unsustainability of direct service delivery due to rapidly growing demands and costs, the MARS-ASMHSD framework endorses the deinstitutionalization of mental healthcare and explores a tiered, multi-dimensional approach in mental healthcare provision, establishing advanced school-based mental health service delivery. The framework is developed based on sustainable and credible evidence-based practices and modifications of existing mental health service deliveries in Asia, including Singapore, Thailand, Malaysia, Japan, and Taiwan. Dissemination of the framework model for implementation will enable a more progressive and advanced school-based mental health service delivery in low-resource areas. Through the evaluation of the mental health landscape and the role of stakeholders in the respective countries, the paper concludes with a multi-dimensional framework model for implementation in low-resource areas. A mixed-method independent research study is conducted to facilitate the framework's development.

Keywords: mental health, youths, school-based services, framework development

Procedia PDF Downloads 50

Authors: Witthaya Mekhum, Jinjutha Srihera

Abstract:

This research aims to study customer satisfaction towards the services of Baan Bueng Resort in Nongprue Subdistrict, Baanlamung District, Chonburi Province. 108 sample were drawn by random sampling from Thai and foreign tourists at Baan Bueng Resort. Questionnaires were distributed. Data were analyzed using frequency, percentage, mean (X) and standard deviation (S.D.). The tool used in this research was questionnaire on satisfaction towards the services of Baan Bueng Resort in Nongprue Subdistrict, Baanlamung District, Chonburi Province. The questionnaire can be divided into 3 parts; i.e. Part 1: General information i.e. gender, age, educational level, occupation, income, and nationality, Part 2: Customer satisfaction towards the services of Baan Bueng Resort; and Part 3: Suggestions of respondents. It can be concluded that most of the respondents are male, aged between 25 – 35 years old with bachelor degree. Most of them are private company employees with income 10,000–20,000 Baht per month. The majority of customers are satisfied with the services at Baan Beung Resort. Overall satisfaction is at good level. Considering each item, the item with the highest satisfaction level is personality and manner of employees and promptness and accuracy of cashier staff. Overall satisfaction towards the cleanliness of the rooms is at very good level. When considering each item, the item with the highest satisfaction level is that the guest room is cleaned everyday, while the satisfaction towards the quality of food and beverages at Baan Bueng Resort in Nongprue Subdistrict, Baanlamung District, Chonburi Province is at very good level. The item with the highest satisfaction is hotel facilities.

Keywords: satisfaction study, service, hotel, customer

Procedia PDF Downloads 333

Authors: Rosa Hendijani, Mohammadhesam Hajighasemi

Abstract:

As of late, the sharing economy has become an important type of business model. Online taxi services are one example that has grown rapidly around the world. This study examines the factors influencing the use of online taxis as one form of IT-enabled sharing services based on the theory of planned behavior (TPB). Based on the theory of planned behavior, these factors can be divided into three categories, including the ones related to attitude (e.g., image and perceived usefulness), normative believes (e.g., subjective norms), and behavioral control (e.g., technology facilitating conditions and self-efficacy). Three other factors were also considered based on the literature, including perceived economic benefits, openness towards using shared services, and perceived availability. The effect of all these variables was tested both directly and indirectly through intention as the mediating variable. A survey method was used to test the research hypotheses. In total, 361 individuals partook in the study. The results of a multiple regression analysis on behavior showed that perceived economic benefits, compatibility, and subjective norms were important factors influencing behavior among online taxi users. In addition, intention partially mediated the effect of perceived economic benefits and compatibility on behavior. It can be concluded that perceived economic benefits, compatibility, and subjective norms are the three main factors that influence behavior among online taxi users.

Keywords: collaborative consumption, IT-enabled sharing services model, online taxi, sharing economy, theory of planned behavior

Procedia PDF Downloads 140

Authors: Anicet Dansou

Abstract:

Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

Procedia PDF Downloads 111

Authors: Salwa Hagag Abdelaziz, Naglaa Fathy Youssef, Nadia Abdellatif Hassan, Rasha Wesam Abdelrahman

Abstract:

Breast cancer is considered as a substantial health concern and practicing mammography screening [MS] is important in minimizing its related morbidity. So it is essential to have a better understanding of breast cancer screening behaviors of women and factors that influence utilization of them. The aim of this study is to identify the factors that are linked to MS behaviors among the Egyptian women. A cross-sectional descriptive design was carried out to provide a snapshot of the factors that are linked to MS behaviors. A convenience sample of 311 women was utilized and all eligible participants admitted to the Women Imaging Unit who are 40 years of age or above, coming for mammography assessment, not pregnant or breast feeding and who accepted to participate in the study were included. A structured questionnaire was developed by the researchers and contains three parts; Socio-demographic data; Motivating factors associated with MS; and association between MS and model of behavior change. The analyzed data indicated that most of the participated women (66.6 %) belonged to the age group of 40-49.A high proportion of participants (58.1%) of group having previous MS influenced by their neighbors to practice MS, whereas 32.7 % in group not having previous MS were influenced by family members which indicated significant differences (P <0.05). Doctors and media are shown to be the least influence of others to practice MS. Women with intention to have a future mammogram had higher OR (1.404) for practicing MS compared with women with no intention. Further studies are needed to examine the relation between Trans-theoretical Model [TTM] and practicing MS.

Keywords: breast cancer, mammography, screening behaviors, morbidity

Procedia PDF Downloads 446

Authors: Ernestina Ohenewaah Denchie, Kevin Lo

Abstract:

Access to clean water is a key element of sustainable development, yet many nations cannot provide reliable water supply to their inhabitants, particularly in rural areas. In Ghana, public smart taps with pre-paid tokens for public standpipe management have been introduced to enhance access to clean water in small towns and rural communities. This research article highlights the impact of pre-paid token systems on water accessibility in small towns and rural Ghana, focusing on their alignment with Sustainable Development Goal 6. We utilize the Technology Acceptance Model (TAM) with data obtained from both quantitative and qualitative responses to demonstrate the user’s acceptance and overall effectiveness of the pre-paid token system in improving access to clean water. We find that among the characteristics of the pre-paid token system, convenience of use, user satisfaction, proximity and accessibility impact smart tap usage positively. Further analyses reveal that providing token loading points at vantage points within communities would improve smart tap usage by about 96%. Finally, our thematic analyses reveal that the problems of the smart tap system can be improved through regular maintenance and technical support, system improvement such as developing an online app for credit loading, restoring lost or unused credits, and better tracking of lost tokens.

Keywords: smart tap, pre-paid, technology acceptance model, water supply

Procedia PDF Downloads 17

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

Abstract:

Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

Procedia PDF Downloads 483

Authors: M. O. Oke, T. S. Workneh

Abstract:

Drying behaviour of blanched sweet potato in a cabinet dryer using different five air temperatures (40-80oC) and ten sweet potato varieties sliced to 5 mm thickness were investigated. The drying data were fitted to eight models. The Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data obtained during the drying of all the varieties while Newton (Lewis) and Wang and Singh models gave the least fit. The values of Deff obtained for Bophelo variety (1.27 x 10-9 to 1.77 x 10-9 m2/s) was the least while that of S191 (1.93 x 10-9 to 2.47 x 10-9 m2/s) was the highest which indicates that moisture diffusivity in sweet potato is affected by the genetic factor. Activation energy values ranged from 0.27-6.54 kJ/mol. The lower activation energy indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method. The drying behavior of blanched sweet potato was investigated in a cabinet dryer. Drying time decreased considerably with increase in hot air temperature. Out of the eight models fitted, the Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data on all the varieties while Newton, Wang and Singh models gave the least. The lower activation energy (0.27-6.54 kJ/mol) obtained indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method.

Keywords: sweet potato slice, drying models, moisture ratio, moisture diffusivity, activation energy

Procedia PDF Downloads 521

Authors: Jessica Gu, Yu Chen

Abstract:

Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

Procedia PDF Downloads 246

Authors: Muhammad Umair, Yuri Nikolaev, Denis Artemov, Ighor Uzhinsky

Abstract:

A flexible manufacturing system is an integral part of a smart factory of industry 4.0 in which every machine is interconnected and works autonomously. Robots are in the process of replacing humans in every industrial sector. As the cyber-physical-system (CPS) and artificial intelligence (AI) are advancing, the manufacturing industry is getting more dependent on computers than human brains. This modernization has boosted the production with high quality and accuracy and shifted from classic production to smart manufacturing systems. However, material handling for such automated productions is a challenge and needs to be addressed with the best possible solution. Conventional clamping systems are designed for manual work and not suitable for highly automated production systems. Researchers and engineers are trying to find the most economical solution for loading/unloading and transportation workpieces from a warehouse to a machine shop for machining operations and back to the warehouse without human involvement. This work aims to propose an advanced multi-shape tooling solution for highly automated manufacturing systems. The currently obtained result shows that it could function well with automated guided vehicles (AGVs) and modern conveyor belts. The proposed solution is following requirements to be automation-friendly, universal for different part geometry and production operations. We used a bottom-up approach in this work, starting with studying different case scenarios and their limitations and finishing with the general solution.

Keywords: artificial intelligence, cyber physics system, Industry 4.0, material handling, smart factory, flexible manufacturing system

Procedia PDF Downloads 136

Authors: Kwak, Hyo-Gyung, Gang, Han Gul

Abstract:

In the context of an increasing need for reliability and safety in concrete structures under blast and impact loading condition, the behavior of concrete under high strain rate condition has been an important issue. Since concrete subjected to impact loading associated with high strain rate shows quite different material behavior from that in the static state, several material models are proposed and used to describe the high strain rate behavior under blast and impact loading. In the process of modelling, in advance, mesh dependency in the used finite element (FE) is the key problem because simulation results under high strain-rate condition are quite sensitive to applied FE mesh size. It means that the accuracy of simulation results may deeply be dependent on FE mesh size in simulations. This paper introduces an improved criterion which can minimize the mesh-dependency of simulation results on the basis of the fracture energy concept, and HJC (Holmquist Johnson Cook), CSC (Continuous Surface Cap) and K&C (Karagozian & Case) models are examined to trace their relative sensitivity to the used FE mesh size. To coincide with the purpose of the penetration test with a concrete plate under a projectile (bullet), the residual velocities of projectile after penetration are compared. The correlation studies between analytical results and the parametric studies associated with them show that the variation of residual velocity with the used FE mesh size is quite reduced by applying a unique failure strain value determined according to the proposed criterion.

Keywords: high strain rate concrete, penetration simulation, failure strain, mesh-dependency, fracture energy

Procedia PDF Downloads 526

Authors: Atefeh Salehipoor

Abstract:

Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: 1. Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. 2. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. 3. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. 4. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. 5. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. 6. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension

Procedia PDF Downloads 91

Authors: Dhiraj Biswas, Chaitali Ray

Abstract:

A modified refined higher order zigzag theory has been developed in this paper in order to compute the accurate interlaminar stresses within hybrid laminates. Warping has significant effect on the mechanical behaviour of the laminates. To the best of author(s)’ knowledge the stress analysis of hybrid laminates is not reported in the published literature. The present paper aims to develop a new C0 continuous element based on the refined higher order zigzag theories considering warping effect in the formulation of hybrid laminates. The eight noded isoparametric plate bending element is used for the flexural analysis of laminated composite plates to study the performance of the proposed model. The transverse shear stresses are computed by using the differential equations of stress equilibrium in a simplified manner. A computer code has been developed using MATLAB software package. Several numerical examples are solved to assess the performance of the present finite element model based on the proposed higher order zigzag theory by comparing the present results with three-dimensional elasticity solutions. The present formulation is validated by comparing the results obtained from the relevant literature. An extensive parametric study has been carried out on the hybrid laminates with varying percentage of materials and angle of orientation of fibre content.

Keywords: hybrid laminate, Interlaminar stress, refined higher order zigzag theory, warping effect

Procedia PDF Downloads 225

Authors: Dimitri Bigot, Bruno Malet-Damour, Jérôme Vigneron

Abstract:

Many studies have been made about using bio-based materials in buildings. The goal is to reduce its environmental footprint by analyzing its life cycle. This can lead to minimize the carbon emissions or energy consumption. A previous work proposed to numerically study the feasibility of using wood chips to regulate relative humidity inside a building. This has shown the capability of a wood chips bed to regulate humidity inside the building, to improve thermal comfort, and so potentially reduce building energy consumption. However, it also shown that some physical parameters of the wood chips must be identified to validate the proposed model and the associated results. This paper presents an experimental setup able to study such a wood chips bed with different solicitations. It consists of a simple duct filled with wood chips and crossed by an air flow with variable temperature and relative humidity. Its main objective is to study the thermal behavior of the wood chips bed by controlling temperature and relative humidity of the air that enters into it and by observing the same parameters at the output. First, the experimental set up is described according to previous results. A focus is made on the particular properties that have to be characterized. Then some case studies are presented in relation to the previous results in order to identify the key physical properties. Finally, the feasibility of the proposed technology is discussed, and some model validation paths are given.

Keywords: wood chips bed, experimental set-up, bio-based material, desiccant, relative humidity, water content, thermal behaviour, air treatment

Procedia PDF Downloads 129

Authors: Luofu Liu, Fei Xiao Jr., Fei Xiao

Abstract:

Through the analysis technology of gas chromatography-mass spectrometry (GC-MS), the composition and distribution characteristics of aromatic hydrocarbons in the Chepaizi area of the Junggar Basin were analyzed in detail. Based on that, the biological input, maturity of crude oils and sedimentary environment of the corresponding source rocks were determined and the origin types of crude oils were divided. The results show that there are three types of crude oils in the study area including Type I, Type II and Type III oils. The crude oils from the 1st member of the Neogene Shawan Formation are the Type I oils; the crude oils from the 2nd member of the Neogene Shawan Formation are the Type II oils; the crude oils from the Cretaceous Qingshuihe and Jurassic Badaowan Formations are the Type III oils. For the Type I oils, they show a single model in the late retention time of the chromatogram of total aromatic hydrocarbons. The content of triaromatic steroid series is high, and the content of dibenzofuran is low. Maturity parameters related to alkyl naphthalene, methylphenanthrene and alkyl dibenzothiophene all indicate low maturity for the Type I oils. For the Type II oils, they have also a single model in the early retention time of the chromatogram of total aromatic hydrocarbons. The content of naphthalene and phenanthrene series is high, and the content of dibenzofuran is medium. The content of polycyclic aromatic hydrocarbon representing the terrestrial organic matter is high. The aromatic maturity parameters indicate high maturity for the Type II oils. For the Type III oils, they have a bi-model in the chromatogram of total aromatic hydrocarbons. The contents of naphthalene series, phenanthrene series, and dibenzofuran series are high. The aromatic maturity parameters indicate medium maturity for the Type III oils. The correlation results of triaromatic steroid series fingerprint show that the Type I and Type III oils have similar source and are both from the Permian Wuerhe source rocks. Because of the strong biodegradation and mixing from other source, the Type I oils are very different from the Type III oils in aromatic hydrocarbon characteristics. The Type II oils have the typical characteristics of terrestrial organic matter input under oxidative environment, and are the coal oil mainly generated by the mature Jurassic coal measure source rocks. However, the overprinting effect from the low maturity Cretaceous source rocks changed the original distribution characteristics of aromatic hydrocarbons to some degree.

Keywords: oil source, geochemistry, aromatic hydrocarbons, crude oils, chepaizi area, Junggar Basin

Procedia PDF Downloads 357

Authors: Selin Kara-Bahçekapılı, Bengisu Nehir Aydın

Abstract:

Objective: In this study, it is aimed to examine the relationship between childhood traumas (overprotection-control, emotional/physical/sexual abuse, emotional/physical neglect), age, emotional regulation difficulties, and the tendency of violence in adults. In the study, the direct and indirect effects of 6 sub-factors of childhood traumas, emotion regulation difficulties, and age on tendency to violence are evaluated on a model that theoretically reveals. Method: The population of this cross-sectional study consists of individuals between the ages of 18-65 living in Turkey. The data from 527 participants were obtained by online surveys and convenience sampling method within the scope of the study. As a result of exclusion criteria and then outlier data analysis, the data of 443 participants were included in the analysis. Data were collected by demographic information form, childhood trauma scale, emotion regulation difficulty scale, and violence tendency scale. Research data were analyzed by SPSS and AMOS using correlation, path analysis, direct and indirect effects. Results: According to the research findings, the variables in the model explained 28.2% of the variance of the mean scores of the individuals' tendency to violence. Emotion regulation difficulties have the most direct effect on the tendency to violence (d=.387; p<.01). The effects of excessive protection and control, emotional neglect, and physical neglect variables on the tendency to violence are not significant. When the significant and indirect effects of the variables on tendency to violence over emotion regulation difficulties are examined, age has a negative effect, emotional neglect has a positive effect, emotional abuse has a positive effect, and overprotection-control has a positive effect. The indirect effects of sexual abuse, physical neglect, and physical abuse on tendency to violence are not significant. Childhood traumas and age variables in the model explained 24.1% of the variance of the mean scores of the individuals’ emotion regulation difficulties. The variable that most affects emotion regulation difficulties is age (d=-.268; p<.001). The direct effects of sexual abuse, physical neglect, and physical abuse on emotion regulation difficulties are not significant. Conclusion: The results of the research emphasize the critical role of difficulty in emotion regulation on the tendency to violence. Difficulty in emotion regulation affects the tendency to violence both directly and by mediating different variables. In addition, it is seen that some sub-factors of childhood traumas have direct and/or indirect effects on the tendency to violence. Emotional abuse and age have both direct and indirect effects on the tendency to violence over emotion regulation difficulties.

Keywords: childhood trauma, emotion regulation difficulties, tendency to violence, path analysis

Procedia PDF Downloads 99

Authors: Umamaheswari Shanmugam, Silvia Ronchi

Abstract:

Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

Procedia PDF Downloads 93

Authors: Brayden Mi

Abstract:

Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

Procedia PDF Downloads 77

Authors: Ahmet Erten, Adil Mustafa, Ayşenur Eser, Özlem Yalçın

Abstract:

We present a new viscometer based on a microfluidic chip with elastic high aspect ratio micropillar arrays. The displacement of pillar tips in flow direction can be used to analyze viscosity of liquid. In our work, Computational Fluid Dynamics (CFD) is used to analyze pillar displacement of various micropillar array configurations in flow direction at different viscosities. Following CFD optimization, micro-CNC based rapid prototyping is used to fabricate molds for microfluidic chips. Microfluidic chips are fabricated out of polydimethylsiloxane (PDMS) using soft lithography methods with molds machined out of aluminum. Tip displacements of micropillar array (300 µm in diameter and 1400 µm in height) in flow direction are recorded using a microscope mounted camera, and the displacements are analyzed using image processing with an algorithm written in MATLAB. Experiments are performed with water-glycerol solutions mixed at 4 different ratios to attain 1 cP, 5 cP, 10 cP and 15 cP viscosities at room temperature. The prepared solutions are injected into the microfluidic chips using a syringe pump at flow rates from 10-100 mL / hr and the displacement versus flow rate is plotted for different viscosities. A displacement of around 1.5 µm was observed for 15 cP solution at 60 mL / hr while only a 1 µm displacement was observed for 10 cP solution. The presented viscometer design optimization is still in progress for better sensitivity and accuracy. Our microfluidic viscometer platform has potential for tailor made microfluidic chips to enable real time observation and control of viscosity changes in biological or chemical reactions.

Keywords: Computational Fluid Dynamics (CFD), high aspect ratio, micropillar array, viscometer

Procedia PDF Downloads 249

Authors: Raymond K. Jonkers

Abstract:

The present study investigated approaches and techniques to enhance strategic management governance and decision making within the framework of a performance-based balanced scorecard. The review of best practices from strategic, program, process, and systems engineering management provided for a holistic approach toward effective outcome-based capability management. One technique, based on factorial experimental design methods, was used to develop an empirical model. This model predicted the degree of capability effectiveness and is dependent on controlled system input variables and their weightings. These variables represent business performance measures, captured within a strategic balanced scorecard. The weighting of these measures enhances the ability to quantify causal relationships within balanced scorecard strategy maps. The focus in this study was on the performance of tangible assets within the scorecard rather than the traditional approach of assessing performance of intangible assets such as knowledge and technology. Tangible assets are represented in this study as physical systems, which may be thought of as being aboard a ship or within a production facility. The measures assigned to these systems include project funding for upgrades against demand, system certifications achieved against those required, preventive maintenance to corrective maintenance ratios, and material support personnel capacity against that required for supporting respective systems. The resultant scorecard is viewed as complimentary to the traditional balanced scorecard for program and performance management. The benefits from these scorecards are realized through the quantified state of operational capabilities or outcomes. These capabilities are also weighted in terms of priority for each distinct system measure and aggregated and visualized in terms of overall state of capabilities achieved. This study proposes the use of interactive controls within the scorecard as a technique to enhance development of alternative solutions in decision making. These interactive controls include those for assigning capability priorities and for adjusting system performance measures, thus providing for what-if scenarios and options in strategic decision-making. In this holistic approach to capability management, several cross functional processes were highlighted as relevant amongst the different management disciplines. In terms of assessing an organization’s ability to adopt this approach, consideration was given to the P3M3 management maturity model.

Keywords: management, systems, performance, scorecard

Procedia PDF Downloads 324

Authors: Matthew J. I. Woolley, Gemma J. M. Read, Paul M. Salmon, Natassia Goode

Abstract:

The significance of high consequence, workplace failures within construction continues to resonate with a combined average of 12 fatal incidents occurring daily throughout Australia, the United Kingdom, and the United States. Within the Australian construction domain, more than 35 serious, compensable injury incidents are reported daily. These alarming figures, in conjunction with the continued occurrence of fatal and serious, occupational injury incidents globally suggest existing approaches to incident analysis may not be achieving required injury prevention outcomes. One reason may be that, incident analysis methods used in construction have not kept pace with advances in the field of safety science and are not uncovering the full range system-wide contributory factors that are required to achieve optimal levels of construction safety performance. Another reason underpinning this global issue may also be the absence of information surrounding the construction operating and project delivery system. For example, it is not clear who shares the responsibility for construction safety in different contexts. To respond to this issue, to the author’s best knowledge, a first of its kind, control structure model of the construction industry is presented and then used to analyse a fatal construction incident. The model was developed by applying and extending the Systems Theoretic and Incident Model and Process method to hierarchically represent the actors, constraints, feedback mechanisms, and relationships that are involved in managing construction safety performance. The Causal Analysis based on Systems Theory (CAST) method was then used to identify the control and feedback failures involved in the fatal incident. The conclusions from the Coronial investigation into the event are compared with the findings stemming from the CAST analysis. The CAST analysis highlighted additional issues across the construction system that were not identified in the coroner’s recommendations, suggested there is a potential benefit in applying a systems theory approach to incident analysis in construction. The findings demonstrate the utility applying systems theory-based methods to the analysis of construction incidents. Specifically, this study shows the utility of the construction control structure and the potential benefits for project leaders, construction entities, regulators, and construction clients in controlling construction performance.

Keywords: construction project management, construction performance, incident analysis, systems thinking

Procedia PDF Downloads 134