Search results for: real estate valuation model

Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

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With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

Procedia PDF Downloads 326

Authors: Tzu-Jung Huang, Hsun-Jung Cho, Chien-Chia Liäm Huang

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To improve the level of service (LoS) of urban arterial systems containing a series of signalized intersections, a proper design of offsets for all intersections associated is of great importance. The MAXBAND model has been the most common approach for this purpose. In this paper, we propose a MAXBAND model with phase constraints so that the lengths of the phases in a cycle are variable. In other words, the length of a cycle is also variable in our setting. We conduct experiments on a real-world traffic network, having several major paths, in Taiwan for numerical evaluations. Actual traffic data were collected through on-site experiments. Numerical evidences suggest that the improvements are around 32%, on average, in terms of total delay of the entire network.

Keywords: arterial progression, MAXBAND, signal control, offset

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Authors: Isah Wada

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The current research investigates the role of financial development in an environmental sustainability-energy consumption nexus for OPEC-1 member countries. The empirical findings suggest that financial development increases environmental sustainability but energy consumption and real output expansion diminishes environmental sustainability, generally. Thus, whilst real output and financial development accelerates energy consumption, environmental sustainability quality diminishes clean energy initiatives. Even more so, energy consumption and financial development stimulates real output growth. The result empirically demonstrates that policy advocates must address broader issues relating to financial development whilst seeking to achieve environmental sustainability due largely to energy consumption.

Keywords: energy consumption, environmental sustainability, financial development, OPEC, real output

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: Medani Prasad Rijal

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Forest itself is a factory as well as product. It supplies tangible and intangible goods and services. It supplies timber, fuel wood, fodder, grass leaf litter as well as non timber edible goods and medicinal and aromatic products additionally provides environmental services. These environmental services are of local, national or even global importance. In Nepal, more than 19 thousands community forests are providing environmental service in less economic benefit than actual efficiency. There is a risk of cost of management of those forest exceeds benefits and forests get converted to open access resources in future. Most of the environmental goods and services do not have markets which mean no prices at which they are available to the consumers, therefore the valuation of these services goods and services establishment of paying mechanism for such services and insure the benefit to community is more relevant in local as well as global scale. There are few examples of carbon trading in domestic level to meet the country wide emission goal. In this contest, the study aims to explore the public attitude towards carbon offsetting and their responsibility over service providers. This study helps in promotion of environment service awareness among general people, service provider and community forest. The research helps to unveil the carbon pool scenario in community forest and willingness to pay for carbon offsetting of people who are consuming more energy than general people and emitting relatively more carbon in atmosphere. The study has assessed the carbon pool status in two community forest and valuated carbon service from community forest through willingness to pay in Dharan municipality situated in eastern. In the study, in two community forests carbon pools were assessed following the guideline “Forest Carbon Inventory Guideline 2010” prescribed by Ministry of Forest and soil Conservation, Nepal. Final outcomes of analysis in intensively managed area of Hokse CF recorded as 103.58 tons C /ha with 6173.30 tons carbon stock. Similarly in Hariyali CF carbon density was recorded 251.72 mg C /ha. The total carbon stock of intensively managed blocks in Hariyali CF is 35839.62 tons carbon.

Keywords: carbon, offsetting, sequestration, valuation, willingness to pay

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Authors: B. Makhlouf, O. Bouchhida, M. Nibouche, K. Laidi

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A variety of methods for selective harmonics elimination pulse width modulation have been developed, the most frequently used for real-time implementation based on look-up tables method. To address real-time requirements based in modified carrier signal is proposed in the presented work, with a general formulation to real-time harmonics control/elimination in switched inverters. Firstly, the proposed method has been demonstrated for a single value of the modulation index. However, in reality, this parameter is variable as a consequence of the voltage (amplitude) variability. In this context, a simple interpolation method for calculating the modified sine carrier signal is proposed. The method allows a continuous adjustment in both amplitude and frequency of the fundamental. To assess the performance of the proposed method, software simulations and hardware experiments have been carried out in the case of a single-phase inverter. Obtained results are very satisfactory.

Keywords: harmonic elimination, Particle Swarm Optimisation (PSO), polynomial interpolation, pulse width modulation, real-time harmonics control, voltage inverter

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Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

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Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

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Authors: Mana Shrestha, Dhruba Khatri, Pralhad Kunwor

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The objective of the study was to explore the vehicle owners’ willingness to pay (WTP) for offsetting carbon that could eventually facilitate local governmental institutions to take further step in environmental conservation. Contingent valuation method was used to find out how much amount people were willing to pay for the carbon service they are getting from providers. Open ended questionnaire was carried out with 181 respondents randomly. The result shows different mean willingness to pay amount depending upon demographic variations like education, occupation, sex and residence but the occupation and the educational status significantly affected the WTP of respondent. Total WTP amount was calculated as 650 NRS.

Keywords: community forest, carbon offset, Kyoto, REDD WTP

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Authors: Mamoon M. Atout

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The Middle East Gulf region has witnessed rapid growth and development in many areas over the last two decades. The development of the real-estate sector, construction industry and infrastructure projects are a major share of the development that has participated in the civilization of the countries of the Gulf. Construction industry projects were planned and managed by different types of experts, who came from all over the world having different types of experiences in construction management and industry. Some of these projects were completed on time, while many were not, due to many accumulating factors. Many accumulated factors are considered as the principle reason for the problem experienced at the project construction stage, which reflected negatively on the project success. Specific causes of delay have been identified by construction managers to avoid any unexpected delays through proper analysis and considerations to some implications such as risk assessment and analysis for many potential problems to ensure that projects will be delivered on time. Construction management implications were adopted and considered by project managers who have experience and knowledge in applying the techniques of the system of engineering construction management. The aim of this research is to determine the benefits of the implications of construction management by the construction team and level of considerations of the techniques and processes during the project development and construction phases to avoid any delay in the projects. It also aims to determine the factors that participate to project completion delays in case project managers are not well committed to their roles and responsibilities. The results of the analysis will determine the necessity of the applications required by the project team to avoid the causes of delays that help them deliver projects on time, e.g. verifying tender documents, quantities and preparing the construction method of the project.

Keywords: construction management, control process, cost control, planning and scheduling

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Authors: Chao Jen-Chih, Hsu Kuo-Wei

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Climate change and natural disasters take effect on urban development. It has been discussed urban renewals can prevent natural disasters. Integrating green infrastructure and urban renewals may have great effect on adapting the impact of climate change. To highlight the economic value of green infrastructure development on urban renewals, some strategies need to be carry on to reduce environmental impact. A number of urban renewals studies has been conducted on right transfer, financial risk, urban renewal policy, and public participation. Little research has been devoted on the subject of the economic value of green infrastructure development on urban renewals. The purpose of this study is to investigate the affecting factors on the economic value of green infrastructure development on urban renewals. This study will present the benefits of green infrastructure development and summarize the critical factors of green infrastructure develop on urban renewals for real essence and non-real essence on economic value from literature. Our results indicate that factors of housing price, land value, floor area incentive, and facilitation of the construction industry affect the outcome of real essence economic value. Factors of enhancement of urban disaster prevention, improvement of urban environment and landscape, crime reduction, climate control, pollution reduction, biological diversity, health impacts, and leisure space affects the outcome of non-real essence economic value.

Keywords: economic value, green infrastructure, urban renewals, urban development

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Marlies Achenbach

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System competencies play a key role to ensure an effective and efficient improvement of production systems. Thus, there can be observed an increasing demand for developing system competencies in industry as well as in engineering education. System competencies consist of the following two main abilities: Evaluating the current state of a production system and developing a target state. The innovative course ‘multi-perspective learning in a real production plant (multi real)’ is developed to create a learning setting that supports the development of these system competencies. Therefore, the setting combines two innovative aspects: First, the Learning takes place in heterogeneous groups formed by students as well as professionals and managers from industry. Second, the learning takes place in a real production plant. This paper presents the innovative didactic concept of ‘multi real’ in detail, which will initially be implemented in October/November 2016 in the industrial engineering, logistics and mechanical master’s program at TU Dortmund University.

Keywords: experiential learning, heterogeneous groups, improving production systems, system competencies

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Ji-yang Yu, Dan Huang, Guo-ping Feng, Xin Li, Lu-yuan Wang

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The navigation satellite network, especially the Beidou MEO Constellation, can relay data effectively with wide coverage and is applied in navigation, detection, and position widely. But the constellation has not been completed, and the amount of satellites on-board is not enough to cover the earth, which makes the data-relay disrupted or delayed in the transition process. The data-relay function needs to tolerant the delay or disruption in some extension, which make the Beidou MEO Constellation a delay/disruption-tolerant network (DTN). The traditional DTN designs mainly employ the relay table as the basic of data path schedule computing. But in practical application, especially in critical condition, such as the war-time or the infliction heavy losses on the constellation, parts of the nodes may become invalid, then the traditional DTN design could be useless. Furthermore, when transmitting the critical message in the navigation system, the maximum priority strategy is used, but the nodes still inquiry the relay table to design the path, which makes the delay more than minutes. Under this circumstances, it needs a function which could compute the optimum data path on-board in real-time according to the constellation states. The on-board critical message transmission design for navigation satellite delay/disruption-tolerant network (DTN) is proposed, according to the characteristics of navigation satellite network. With the real-time computation of parameters in the network link, the least-delay transition path is deduced to retransmit the critical message in urgent conditions. First, the DTN model for constellation is established based on the time-varying matrix (TVM) instead of the time-varying graph (TVG); then, the least transition delay data path is deduced with the parameters of the current node; at last, the critical message transits to the next best node. For the on-board real-time computing, the time delay and misjudges of constellation states in ground stations are eliminated, and the residual information channel for each node can be used flexibly. Compare with the minute’s delay of traditional DTN; the proposed transmits the critical message in seconds, which improves the re-transition efficiency. The hardware is implemented in FPGA based on the proposed model, and the tests prove the validity.

Keywords: critical message, DTN, navigation satellite, on-board, real-time

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Damianos Tzoupis

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In the context of the canon debate, assumptions regarding the place, value, and impact of classical texts have come under increased scrutiny. Factors like the distance of time, the depreciation of tradition, or the increased cultural omnivorousness and eclecticism have allegedly played a part in destabilizing classics’ authority. However, despite all these developments, classics’ position and influence is strong both in contemporary institutions and among readers’ preferences. Within this background of conflicted narratives, the study maps the varied discourses, value grammars, and justifications that lay cultural consumers employ to discuss those texts which have come to be the most consecrated and valuable cultural objects. The study centers on reviews posted on Goodreads. These online reviews offer unique access to unsolicited reception data produced by lay readers themselves, thus providing a clearer picture of lay cultural consumption and lay theories about classics. Moreover, the approach taken relies on the micro-practices of evaluation: the study investigates the evaluation of a specific cultural object, namely Plato’s allegory of the Cave, and treats it as an exemplary case to identify interpretive repertoires and valuation grammars about classical texts in general. The analysis uncovers a wide range of discourses used to construct the concept of the “classical text”. At first sight, lay reviewers seem to adopt interpretive repertoires that highlight qualities such as universality, timelessness, canonicity, cultural impact, and difficulty. These repertoires seem in principle to follow generalized and institutionalized discourses about classical texts, as these are established and circulated by institutions and cultural brokers like schools, academics, critics, etc. However, the study also uncovers important variations of these discourses. Lay readers tend to (re)negotiate the meanings/connotations of the above qualities and also structure their discourses by “modalities” such as necessity or surprise. These variations in interpretive repertoires are important in cultural sociology’s attempt to better grasp the principles informing the grammars of valuation that lay cultural consumers employ and to understand the kinds of impact that consecrated cultural objects have on people’s lives.

Keywords: classics, interpretive repertoires around classicalness, institutionalized discourses, lay readers, online reviews/criticism

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Authors: Dong Chen, Han Song, Tingting Wei

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Industrial zones have made significant contributions to the economic development of Chinese urban areas for decades. In the background of China's New Normal, numbers of mature industrial zones are stepping into a new stage of inventory development instead of increment development. The aim of this study is to discover new characteristics and problems and corresponding inventory planning guidance of mature industrial zones. A case of Yangzhou Hi-Tech Industrial Development Zone is reported in this study. Based on a historical analysis and data analysis of land-use, it is found that land-use of the zone is near saturation and signs of land updating have begun to appear. It is observed that the zone is facing problems including disorder of land development, low economic productivity and single function. Through the data of economic output, tax contribution, industrial category, industry life cycle and environmental influence, a comprehensive assessment based on two dimensions, economic benefits and industrial matchup, is made upon every parcel in the zone. According to the assessment, the zone is divided into spatial units of the update with specific planning guidance. It comes to a conclusion as four directions of inventory planning guidance in mature industrial zones: moving industries with poor economic benefit and negative environmental influence, adding urban function and new industrial function to the zone, optimizing the function of important space, and restricting the mass layout of the real estate industry to provide space for industrial upgrading.

Keywords: China's new normal, mature industrial zones, land-use, inventory planning

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Authors: Fawwaz Eniola Fajingbesi, Nur Shahida Midia, Elsheikh M. A. Elsheikh, Siti Hajar Yusoff

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Empirical analysis of lightning related phenomena in real time is extremely dangerous due to the relatively high electric discharge involved. Hence, design and optimization of efficient grounding systems depending on real time empirical methods are impeded. Using numerical methods, the dynamics of complex systems could be modeled hence solved as sets of linear and non-linear systems . In this work, the induced current distribution as lightning strike traverses the soil have been numerically modeled in a 2D axial-symmetry and solved using finite element method (FEM) in COMSOL Multiphysics 5.2 AC/DC module. Stratified and non- stratified electrode system were considered in the solved model and soil conductivity (σ) varied between 10 – 58 mS/m. The result discussed therein were the electric field distribution, current distribution and soil ionization phenomena. It can be concluded that the electric field and current distribution is influenced by the injected electric potential and the non-linearity in soil conductivity. The result from numerical calculation also agrees with previously laboratory scale empirical results.

Keywords: current distribution, grounding systems, lightning discharge, numerical model, soil conductivity, soil ionization

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Authors: Golden J. Zhang, Dongbao Zhou

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Darcy’s law is the fundamental theory in fluid dynamics and engineering applications. Although Darcy linearity was found to be valid for slow, viscous flow, non-linear and non-Darcian flow has been well documented under both small and large velocity fluid flow. Various classical models were proposed and used widely to quantify non-Darcian flow, including the well-known Forchheimer, Izbash, and Swartzendruber models. Applications, however, revealed limitations of these models. Here we propose a general model built upon the Caputo fractional derivative to quantify non-Darcian flow for various flows (laminar to turbulence).Real-world applications and model comparisons showed that the new fractional-derivative model, which extends the fractional model proposed recently by Zhou and Yang (2018), can capture the non-Darcian flow in the relatively small velocity in low-permeability deposits and the relatively high velocity in high-permeability sand. A scale effect was also identified for non-Darcian flow in fractured rocks. Therefore, fractional calculus may provide an efficient tool to improve classical models to quantify fluid dynamics in aquatic environments.

Keywords: fractional derivative, darcy’s law, non-darcian flow, fluid dynamics

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Authors: Aya Al Masri, Stefaan Carpentier, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis and ulceration to appear. In order to prevent these deterministic effects, an accurate calculation of the patient skin-dose mapping is essential. For most machines, the 'Dose Area Product (DAP)' and fluoroscopy time are the only information available for the operator. These two parameters are a very poor indicator of the peak skin dose. We developed a mathematical model that reconstructs the magnitude (delivered dose), shape, and localization of each irradiation field on the patient skin. In case of critical dose exceeding, the system generates warning alerts. We present the results of its comparison with clinical studies. Materials and methods: Two series of comparison of the skin-dose mapping of our mathematical model with clinical studies were performed: 1. At a first time, clinical tests were performed on patient phantoms. Gafchromic films were placed on the table of the IR machine under of PMMA plates (thickness = 20 cm) that simulate the patient. After irradiation, the film darkening is proportional to the radiation dose received by the patient's back and reflects the shape of the X-ray field. After film scanning and analysis, the exact dose value can be obtained at each point of the mapping. Four experimentation were performed, constituting a total of 34 acquisition incidences including all possible exposure configurations. 2. At a second time, clinical trials were launched on real patients during real 'Chronic Total Occlusion (CTO)' procedures for a total of 80 cases. Gafchromic films were placed at the back of patients. We performed comparisons on the dose values, as well as the distribution, and the shape of irradiation fields between the skin dose mapping of our mathematical model and Gafchromic films. Results: The comparison between the dose values shows a difference less than 15%. Moreover, our model shows a very good geometric accuracy: all fields have the same shape, size and location (uncertainty < 5%). Conclusion: This study shows that our model is a reliable tool to warn physicians when a high radiation dose is reached. Thus, deterministic effects can be avoided.

Keywords: clinical experimentation, interventional radiology, mathematical model, patient's skin-dose mapping.

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Authors: Larissa Bolliger, Junoš Lukan, Mitja Lustrek, Dirk De Bacquer, Els Clays

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Introduction and Aim: Chronic workplace stress and its health-related consequences like mental and cardiovascular diseases have been widely investigated. This project focuses on the sources and context of psychosocial daily workplace stress in a real-world setting. The main objective is to analyze and model real-time relationships between (1) psychosocial stress experiences within the natural work environment, (2) micro-level work activities and events, and (3) physiological signals and behaviors in office workers. Methods: An Ecological Momentary Assessment (EMA) protocol has been developed, partly building on machine learning techniques. Empatica® wristbands will be used for real-life detection of stress from physiological signals; micro-level activities and events at work will be based on smartphone registrations, further processed according to an automated computer algorithm. A field study including 100 office-based workers with high-level problem-solving tasks like managers and researchers will be implemented in Slovenia and Belgium (50 in each country). Data mining and state-of-the-art statistical methods – mainly multilevel statistical modelling for repeated data – will be used. Expected Results and Impact: The project findings will provide novel contributions to the field of occupational health research. While traditional assessments provide information about global perceived state of chronic stress exposure, the EMA approach is expected to bring new insights about daily fluctuating work stress experiences, especially micro-level events and activities at work that induce acute physiological stress responses. The project is therefore likely to generate further evidence on relevant stressors in a real-time working environment and hence make it possible to advise on workplace procedures and policies for reducing stress.

Keywords: ecological momentary assessment, real-time, stress, work

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Authors: Raouf Mbarki, Fadi Al Khatib, Malek Adouni

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Knee collateral ligaments play a significant role in restraining excessive frontal motion (varus/valgus rotations). In this investigation, a multiscale frame was developed based on structural hierarchies of the collateral ligaments starting from the bottom (tropocollagen molecule) to up where the fibred reinforced structure established. Experimental data of failure tensile test were considered as the principal driver of the developed model. This model was calibrated statistically using Bayesian calibration due to the high number of unknown parameters. Then the model is scaled up to fit the real structure of the collateral ligaments and simulated under realistic boundary conditions. Predications have been successful in describing the observed transient response of the collateral ligaments during tensile test under pre- and post-damage loading conditions. Collateral ligaments maximum stresses and strengths were observed near to the femoral insertions, a results that is in good agreement with experimental investigations. Also for the first time, damage initiation and propagation were documented with this model as a function of the cross-link density between tropocollagen molecules.

Keywords: multiscale model, tropocollagen, fibrils, ligaments commas

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Authors: Manoj M. Sarode, Sharad P. Jadhav, Mukesh D. Patil, Pushparaj S. Suryawanshi

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Even though the PID controller is widely used in industrial process, tuning of PID parameters are not easy. It is a time consuming and requires expert people. Another drawback of PID controller is that process dynamics might change over time. This can happen due to variation of the process load, normal wear and tear etc. To compensate for process behavior change over time, expert users are required to recalibrate the PID gains. Implementation of model based controllers usually needs a process model. Identification of process model is time consuming job and no guaranty of model accuracy. If the identified model is not accurate, performance of the controller may degrade. Model based controllers are quite expensive and the whole procedure for the implementation is sometimes tedious. To eliminate such issues Autotuning PID controller becomes vital element. Software based Relay Feedback Autotuning Controller proves to be efficient, upgradable and maintenance free controller. In Relay Feedback Autotune controller PID parameters can be achieved with a very short span of time. This paper presents the real time implementation of LabVIEW based Relay Feedback Autotuning PID controller. It is successfully developed and implemented to control level of a laboratory setup. Its performance is analyzed for different setpoints and found satisfactorily.

Keywords: autotuning, PID, liquid level control, recalibrate, labview, controller

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Authors: Mazlynda Md Yusuf, Wafa' Mahadzir, Mohamad Yazis Ali Basah

Abstract:

Nowadays, financing long-term care for elderly people is a crucial issue, either towards the family members or the care institution. Corresponding with the growing number of ageing population in Malaysia, there’s a need of concern on the uncertaintiness of future family care and the need for long-term care services. Moreover, with the increasing cost of living, children feels the urge of needing to work and receive a fixed monthly income that results to sending their elderly parents to care institutions. Currently, in Malaysia, the rates for private nursing homes can amount up to RM 4,000 per month excluding medical treatments and other recurring expenses. These costs are expected to be paid using their Employees Provident Fund (EPF) savings that they accumulate during their working years, especially for those working under private sectors. Hence, this study identifies the adequacy of EPF in funding the cost of long-term care service during old age. This study used a hypothetical simulation model to simulate different scenarios. The findings of this study could be used for individuals to prepare on the importance of planning for retirement, especially with the increasing cost of long-term care services.

Keywords: long-term care cost, employees provident fund Malaysia, ageing population, Malaysian elderly

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Authors: Kahil Amar, Meziani Faroudja, Khelil Nacim

Abstract:

The principal objective of this study is the evaluation of the seismic performance of reinforced concrete frame structures, taking into account of the behavior laws, reflecting the real behavior of materials, using CASTEM2000 software. A finite element model used is based in modified Takeda model with Timoshenko elements for columns and beams. This model is validated on a Vecchio experimental reinforced concrete (RC) frame model. Then, a study focused on the behavior of a RC frame with three-level and three-story in order to visualize the positioning the plastic hinge (plastic rotation), determined from the curvature distribution along the elements. The results obtained show that the beams of the 1^st and 2^nd level developed a very large plastic rotations, or these rotations exceed the values corresponding to CP (Collapse prevention with cp q_CP = 0.02 rad), against those developed at the 3^rd level, are between IO and LS (Immediate occupancy and life Safety with q_IO = 0.005 rad and rad q_LS = 0.01 respectively), so the beams of first and second levels submit a very significant damage.

Keywords: seismic performance, performance level, pushover analysis, plastic rotation, plastic hinge

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

Abstract:

Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

Abstract:

This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

Procedia PDF Downloads 277