Search results for: hybrid air quality model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25966

Search results for: hybrid air quality model

24796 A Deep Learning Approach for the Predictive Quality of Directional Valves in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

Procedia PDF Downloads 244
24795 The Effect of Benson Relaxation Method on Quality of Life in Hemodialysis Patients in 2012-2013, Kermanshah, Iran

Authors: Fateme Hadadian, Behnam Khaledi Paveh, Hosein Feizi

Abstract:

Background: High number of patients with end-stage renal disease worldwide, and Iran and the patients required hemodialysis, As well as symptoms and treatment process and its impact on quality of life The researcher had to take a step towards solving these problems. Methods: In randomized clinical trial in 60 hemodialysis patients admitted to hospital hemodialysis Imam Reza (AS) were studied. Using questionnaires dialysis patients' QOL, quality of life was measured in patients and controls were divided randomly into two groups. Benson's relaxation method for the experimental group and two months at home, once per day, respectively and the control group received no special action. Immediately after the end of the period with was used for evaluating the quality of life in both the experimental and control groups were survey and data using independent t-test were used for statistical analysis. Results: The general dimensions of quality of life scores before and after intervention, there was significant difference (P=0/001). But this difference was not significant after QOL (P=0/2). Between QOL scores before and after treatment between the two groups was statistically significant (P=0/02). Conclusion: Benson relaxation has the desired effect on quality of life in hemodialysis patients and can be used as a useful method to enhance the quality of life in hemodialysis patients, implementation and training will be given.

Keywords: hemodialysis, quality of life, Benson muscle relaxation, biomedicine

Procedia PDF Downloads 428
24794 Perception of TQM Implementation and Perceived Cost of Poor Quality: A Case Study of Local Automotive Company’s Supplier

Authors: Fakhruddin Esa, Yusri Yusof

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The confirmatory of Total Quality Management (TQM) implementation is most vital in quality management. This paper focuses on employees' perceptions towards TQM implementation in a local automotive company supplier. The objectives of this study are first and foremost to determine the perception of TQM implementation among the staff, and secondly to ascertain the correlation between the variables, and lastly to identify the relative influence of the 10 TQM variables on the cost of poor quality (COPQ). The TQM implementation is perceived to be moderate. All correlation is found to be significant and five variables having positively moderate to high correlation. Out of 10 variables, quality system improvement, reward and recognition and customer focus influence the perceived COPQ. This study extended a discussion on these three variables contribution to TQM in general and the human resource development in the organization. A significant recommendation to lowering costs of internal error, such as trouble shooting and scraps are also discussed. Certain components of further research that would add value to this study have also been suggested and perhaps could be implemented at policy-level initiatives.

Keywords: cost of poor quality (COPQ), correlation, total quality management (TQM), variables

Procedia PDF Downloads 217
24793 Sustainable Cities: Viability of a Hybrid Aeroponic/Nutrient Film Technique System for Cultivation of Tomatoes

Authors: D. Dannehl, Z. Taylor, J. Suhl, L. Miranda, R., Ulrichs, C., Salazar, E. Fitz-Rodriguez, I. Lopez-Cruz, A. Rojano-Aguilar, G. Navas-Gomez, U. Schmidt

Abstract:

Growing environmental and sustainability concerns have driven continual modernization of horticultural practices, especially for urban farming. Controlled environment and soilless production methods are increasing in popularity because of their efficient resource use and intensive cropping capabilities. However, some popular substrates used for hydroponic cultivation, particularly rock wool, represent a large environmental burden in regard to their manufacture and disposal. Substrate-less hydroponic systems are effective in producing short cropping cycle plants such as lettuce or herbs, but less information is available for the production of plants with larger root-systems and longer cropping times. Here, we investigated the viability of a hybrid aeroponic/nutrient film technique (AP/NFT) system for the cultivation of greenhouse tomatoes (Solanum lycopersicum ‘Panovy’). The plants grown in the AP/NFT system had a more compact phenotype, accumulated more Na+ and less P and S than the rock wool grown counterparts. Due to forced irrigation interruptions, we propose that the differences observed were cofounded by the differing severity of water-stress for plants with and without substrate. They may also be caused by a higher root zone temperature predominant in plants exposed to AP/NFT. However, leaf area, stem diameter, and number of trusses did not differ significantly. The same was found for leaf pigments and plant photosynthetic efficiency. Overall, the AP/NFT system appears to be viable for the production of greenhouse tomato, enabling the environment to be relieved by way of lessening rock wool usage.

Keywords: closed aeroponic systems, fruit quality, nutrient dynamics, substrate waste reduction, urban farming systems, water savings

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24792 From Avatars to Humans: A Hybrid World Theory and Human Computer Interaction Experimentations with Virtual Reality Technologies

Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

Procedia PDF Downloads 142
24791 Data Quality on Regular Immunization Programme at Birkod District: Somali Region, Ethiopia

Authors: Eyob Seife, Tesfalem Teshome, Bereket Seyoum, Behailu Getachew, Yohans Demis

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Developing countries continue to face preventable communicable diseases, such as vaccine-preventable diseases. The Expanded Programme on Immunization (EPI) was established by the World Health Organization in 1974 to control these diseases. Health data use is crucial in decision-making, but ensuring data quality remains challenging. The study aimed to assess the accuracy ratio, timeliness, and quality index of regular immunization programme data in the Birkod district of the Somali Region, Ethiopia. For poor data quality, technical, contextual, behavioral, and organizational factors are among contributors. The study used a quantitative cross-sectional design conducted in September 2022GC using WHO-recommended data quality self-assessment tools. The accuracy ratio and timeliness of reports on regular immunization programmes were assessed for two health centers and three health posts in the district for one fiscal year. Moreover, the quality index assessment was conducted at the district level and health facilities by trained assessors. The study found poor data quality in the accuracy ratio and timeliness of reports at all health units, which includes zeros. Overreporting was observed for most facilities, particularly at the health post level. Health centers showed a relatively better accuracy ratio than health posts. The quality index assessment revealed poor quality at all levels. The study recommends that responsible bodies at different levels improve data quality using various approaches, such as the capacitation of health professionals and strengthening the quality index components. The study highlighted the need for attention to data quality in general, specifically at the health post level, and improving the quality index at all levels, which is essential.

Keywords: Birkod District, data quality, quality index, regular immunization programme, Somali Region-Ethiopia

Procedia PDF Downloads 90
24790 Assessment of Air Quality Status Using Pollution Indicators in Industrial Zone of Brega City

Authors: Tawfig Falani, Abdulalaziz Saleh

Abstract:

Air pollution has become a major environmental issue with definitive repercussions on human health. Global concerns have been raised about the health effects of deteriorating air quality due mainly to widespread industrialization and urbanization. To assess the quality of air in Brega, air quality indicators were calculated using the U.S. Environmental Protection Agency procedure. Air quality was monitored from 01/10/2019 to 28/02/2021 with a daily average measuring six pollutants of particulate matter <2.5µm (PM2.5), and <10µm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO). The result indicated that air pollution at general air quality monitoring sites for sulphur dioxide, carbon monoxide, PM₁₀ and PM2.5 and nitrogen dioxide are always within the permissible limit. Referring to a monthly average of Pollutants in the Brega Industrial area, all months were out of AQG limit for NO₂, and the same with O₃ except for two months. For PM2.5 and PM₁₀ 7, 5 out of 17 months were out of limits, respectively. Relative AQI for ozone is found in the range of moderate category of general air pollution, and the worst month was Nov. 2020, which was marked as Very Unhealthy category, then the next two months (Dec. 2020 and Jan. 2021 ) were Unhealthy categories. It's the first time that we have used the AQI in SOC, and not usually used in Libya to identify the quality of air pollution. So, I think it will be useful if AQI is used as guidance for specified air pollution. That dictate putting monitoring stations beside any industrial activity that has emissions of the six major air pollutants.

Keywords: air quality, air pollutants, air quality index (AQI), particulate matter

Procedia PDF Downloads 52
24789 Machine Learning Data Architecture

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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24788 Detection of Voltage Sag and Voltage Swell in Power Quality Using Wavelet Transforms

Authors: Nor Asrina Binti Ramlee

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Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

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24787 Implementation of a Quality Management Approach in the Laboratory of Quality Control and the Repression of Fraud (CACQE) of the Wilaya of Bechar

Authors: Khadidja Mebarki, Naceur Boussouar, Nabila Ihaddadene, M. Akermi

Abstract:

Food products are particularly sensitive, since they concern the health of the consumer, whether it’s be from the health point of view or commercial, this kind of product must be subjected to rigorous controls, in order to prevent any fraud. Quality and safety are essential for food security, public health and economic development. The strengthening of food security is essential to increase food security which is considered reached when all individuals can at any time access safe and nutritious food they need to lead healthy and active lives. The objective of this project is to initiate a quality approach in the laboratories of the quality control and the repression of fraud. It will be directed towards the application of good laboratory practices, traceability, management of quality documents (quality, procedures and specification manual) and quality audits. And to prepare the ground for a possible accreditation by ISO 17025 standard of BECHAR laboratory’s. The project will take place in four main stages: 1- Preparation of an audit grid; 2- Realization of a quality audit according to the method of 5 M completed by a section on quality documentation; 3- Drafting of an audit report and proposal for recommendations; 4- Implementation of corrective actions on the ground. This last step consisted in the formalization of the cleaning disinfection plan; work on good hygiene practices, establishment of a mapping of processes and flow charts of the different processes of the laboratory, classifying quality documents and formalizing the process of document management. During the period of the study within the laboratory, all facets of the work were almost appreciated, as we participated in the expertise performed in within it.

Keywords: quality, management, ISO 17025 accreditation, GLP

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24786 Application of Harris Hawks Optimization Metaheuristic Algorithm and Random Forest Machine Learning Method for Long-Term Production Scheduling Problem under Uncertainty in Open-Pit Mines

Authors: Kamyar Tolouei, Ehsan Moosavi

Abstract:

In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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24785 Development of Sustainable Building Environmental Model (SBEM) in Hong Kong

Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

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This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption, they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation and 15% in field measurement of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.

Keywords: sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving

Procedia PDF Downloads 636
24784 Anisotropic Total Fractional Order Variation Model in Seismic Data Denoising

Authors: Jianwei Ma, Diriba Gemechu

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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

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24783 Study of Flow-Induced Noise Control Effects on Flat Plate through Biomimetic Mucus Injection

Authors: Chen Niu, Xuesong Zhang, Dejiang Shang, Yongwei Liu

Abstract:

Fishes can secrete high molecular weight fluid on their body skin to enable their rapid movement in the water. In this work, we employ a hybrid method that combines Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) to investigate the effects of different mucus viscosities and injection velocities on fluctuation pressure in the boundary layer and flow-induced structural vibration noise of a flat plate model. To accurately capture the transient flow distribution on the plate surface, we use Large Eddy Simulation (LES) while the mucus inlet is positioned at a sufficient distance from the model to ensure effective coverage. Mucus injection is modeled using the Volume of Fluid (VOF) method for multiphase flow calculations. The results demonstrate that mucus control of pulsating pressure effectively reduces flow-induced structural vibration noise, providing an approach for controlling flow-induced noise in underwater vehicles.

Keywords: mucus, flow control, noise control, flow-induced noise

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24782 Optimizing Production Yield Through Process Parameter Tuning Using Deep Learning Models: A Case Study in Precision Manufacturing

Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

Procedia PDF Downloads 33
24781 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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24780 A Hybrid Distributed Algorithm for Solving Job Shop Scheduling Problem

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

Procedia PDF Downloads 387
24779 Association Between Friendship Quality and Subjective Wellbeing Among Adolescents: A Systematic Review

Authors: Abdullah Alsarrani, Leandro Garcia, Ruth Hunter, Laura Dunne

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Social integration with friends has an important role in shaping adolescents’ behavior and determining their well-being. Friendship features such as companionship, trust, closeness, intimacy, and conflicts all form the concept of friendship quality. The quality of friendship relationships can either enhance or impede mental development during adolescence. Therefore, this systematic review was conducted to understand the association between friendship quality and adolescents’ mental wellbeing. The evidence was synthesized from a search of five databases (Medline, Embase, ProQuest, Scopus, and PsycINFO). Thirty-two articles out of 18801 records were included in the review. The relationship between friendship quality and depression has been investigated extensively in the literature and negative (beneficial) associations were found in twelve studies out of sixteen. Poor peer relationship was linked to loneliness in eight studies out of nine. All five studies on life satisfaction and quality of peer connection found a positive association. In five studies, optimal peer relationship was found to be associated with happiness. A positive association between friendship quality and self-esteem in four out of five applicable studies. Friendship quality was found to be correlated with subjective well-being in all of three included studies focused on this area. The review demonstrates the paramount value of promoting healthy friendship to adolescents’ subjective well-being constructs. Interventions that aim to promote subjective wellbeing among adolescents should consider the development and maintenance of healthy friendships.

Keywords: adolescents, friendship quality, peer, wellbeing

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24778 Investigating the Indoor Air Quality of the Respiratory Care Wards

Authors: Yu-Wen Lin, Chin-Sheng Tang, Wan-Yi Chen

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Various biological specimens, drugs, and chemicals exist in the hospital. The medical staffs and hypersensitive inpatients expose might expose to multiple hazards while they work or stay in the hospital. Therefore, the indoor air quality (IAQ) of the hospital should be paid more attention. Respiratory care wards (RCW) are responsible for caring the patients who cannot spontaneously breathe without the ventilators. The patients in RCW are easy to be infected. Compared to the bacteria concentrations of other hospital units, RCW came with higher values in other studies. This research monitored the IAQ of the RCW and checked the compliances of the indoor air quality standards of Taiwan Indoor Air Quality Act. Meanwhile, the influential factors of IAQ and the impacts of ventilator modules, with humidifier or with filter, were investigated. The IAQ of two five-bed wards and one nurse station of a RCW in a regional hospital were monitored. The monitoring was proceeded for 16 hours or 24 hours during the sampling days with a sampling frequency of 20 minutes per hour. The monitoring was performed for two days in a row and the AIQ of the RCW were measured for eight days in total. The concentrations of carbon dioxide (CO₂), carbon monoxide (CO), particulate matter (PM), nitrogen oxide (NOₓ), total volatile organic compounds (TVOCs), relative humidity (RH) and temperature were measured by direct reading instruments. The bioaerosol samples were taken hourly. The hourly air change rate (ACH) was calculated by measuring the air ventilation volume. Human activities were recorded during the sampling period. The linear mixed model (LMM) was applied to illustrate the impact factors of IAQ. The concentrations of CO, CO₂, PM, bacterial and fungi exceeded the Taiwan IAQ standards. The major factors affecting the concentrations of CO, PM₁ and PM₂.₅ were location and the number of inpatients. The significant factors to alter the CO₂ and TVOC concentrations were location and the numbers of in-and-out staff and inpatients. The number of in-and-out staff and the level of activity affected the PM₁₀ concentrations statistically. The level of activity and the numbers of in-and-out staff and inpatients are the significant factors in changing the bacteria and fungi concentrations. Different models of the patients’ ventilators did not affect the IAQ significantly. The results of LMM can be utilized to predict the pollutant concentrations under various environmental conditions. The results of this study would be a valuable reference for air quality management of RCW.

Keywords: respiratory care ward, indoor air quality, linear mixed model, bioaerosol

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24777 Fire Resistance of High Alumina Cement and Slag Based Ultra High Performance Fibre-Reinforced Cementitious Composites

Authors: A. Q. Sobia, M. S. Hamidah, I. Azmi, S. F. A. Rafeeqi

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Fibre-reinforced polymer (FRP) strengthened reinforced concrete (RC) structures are susceptible to intense deterioration when exposed to elevated temperatures, particularly in the incident of fire. FRP has the tendency to lose bond with the substrate due to the low glass transition temperature of epoxy; the key component of FRP matrix.  In the past few decades, various types of high performance cementitious composites (HPCC) were explored for the protection of RC structural members against elevated temperature. However, there is an inadequate information on the influence of elevated temperature on the ultra high performance fibre-reinforced cementitious composites (UHPFRCC) containing ground granulated blast furnace slag (GGBS) as a replacement of high alumina cement (HAC) in conjunction with hybrid fibres (basalt and polypropylene fibres), which could be a prospective fire resisting material for the structural components. The influence of elevated temperatures on the compressive as well as flexural strength of UHPFRCC, made of HAC-GGBS and hybrid fibres, were examined in this study. Besides control sample (without fibres), three other samples, containing 0.5%, 1% and 1.5% of basalt fibres by total weight of mix and 1 kg/m3 of polypropylene fibres, were prepared and tested. Another mix was also prepared with only 1 kg/m3 of polypropylene fibres. Each of the samples were retained at ambient temperature as well as exposed to 400, 700 and 1000 °C followed by testing after 28 and 56 days of conventional curing. Investigation of results disclosed that the use of hybrid fibres significantly helped to improve the ambient temperature compressive and flexural strength of UHPFRCC, which was found to be 80 and 14.3 MPa respectively. However, the optimum residual compressive strength was marked by UHPFRCC-CP (with polypropylene fibres only), equally after both curing days (28 and 56 days), i.e. 41%. In addition, the utmost residual flexural strength, after 28 and 56 days of curing, was marked by UHPFRCC– CP and UHPFRCC– CB2 (1 kg/m3 of PP fibres + 1% of basalt fibres) i.e. 39% and 48.5% respectively.

Keywords: fibre reinforced polymer materials (FRP), ground granulated blast furnace slag (GGBS), high-alumina cement, hybrid, fibres

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24776 Open and Distance Learning (ODL) Education in Nigeria: Challenge of Academic Quality

Authors: Edu Marcelina, Sule Sheidu A., Nsor Eunice

Abstract:

As open and distance education is gradually becoming an acceptable means of solving the problem of access in higher education, quality has now become one of the main concerns among institutions and stakeholders of open and distance learning (ODL) and the education sector in general. This study assessed the challenges of academic quality in the open and distance learning (ODL) education in Nigeria using Distance Learning Institute (DLI), University of Lagos and National Open University of Nigeria as a case. In carrying out the study, a descriptive survey research design was employed. A researcher-designed and validated questionnaire was used to elicit responses that translated to the quantitative data for this study. The sample comprised 665 students of the Distance Learning Institute (DLI), and National Open University of Nigeria (NOUN), carefully selected through the method of simple random sampling. Data collected from the study were analyzed using Chi-Square (X2) at 0.05 Level of significance. The results of the analysis revealed that; the use of ICT tools is a factor in ensuring quality in the Open and Distance Learning (ODL) operations; the quality of the materials made available to ODL students will determine the quality of education that will be received by the students; and the time scheduled for students for self-study, online lecturing/interaction and face to face study and the quality of education in Open and Distance Learning Institutions has a lot of impact on the quality of education the students receive. Based on the findings, a number of recommendations were made.

Keywords: open and distance learning, quality, ICT, face-to-face interaction

Procedia PDF Downloads 378
24775 Surface Modified Core–Shell Type Lipid–Polymer Hybrid Nanoparticles of Trans-Resveratrol, an Anticancer Agent, for Long Circulation and Improved Efficacy against MCF-7 Cells

Authors: M. R. Vijayakumar, K. Priyanka, Ramoji Kosuru, Lakshmi, Sanjay Singh

Abstract:

Trans resveratrol (RES) is a non-flavonoid poly-phenolic compound proved for its therapeutic and preventive effect against various types of cancer. However, the practical application of RES in cancer treatment is limited because of its higher dose (up to 7.5 g/day in humans), low biological half life, rapid metabolism and faster elimination in mammals. PEGylated core-shell type lipid polymer hybrid nanoparticles are the novel drug delivery systems for long circulation and improved anti cancer effect of its therapeutic payloads. Therefore, the main objective of this study is to extend the biological half life (long circulation) and improve the therapeutic efficacy of RES through core shell type of nanoparticles. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS), a novel surfactant is applied for the preparation of PEGylated lipid polymer hybrid nanoparticles. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Entrapment efficiency and invitro drug release were determined by ultracentrifugation method and dialysis bag method, respectively. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies after i.v administration were performed in sprague dawley rats. The prepared NPs were found to be spherical in shape with smooth surfaces. Particle size and zeta potential of prepared NPs were found to be in the range of 179.2±7.45 to 266.8±9.61 nm and -0.63 to -48.35 mV, respectively. DSC revealed absence of potential interaction. XRD study revealed presence of amorphous form in nanoparticles. Entrapment efficiency was found to be 83.7 % and drug release was found to be in controlled manner. MTT assay showed low MEC and pharmacokinetic studies showed higher AUC of nanoformulaition than its pristine drug. All these studies revealed that the RES loaded PEG modified core-shell type lipid polymer hybrid nanoparticles can be an alternative tool for chemopreventive and therapeutic application of RES in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating nanoparticles, bioavailability enhancement, core shell nanoparticles, lipid polymer hybrid nanoparticles

Procedia PDF Downloads 472
24774 Different Response of Pure Arctic Char Salvelinus alpinus and Hybrid (Salvelinus alpinus vs. Salvelinus fontinalis Mitchill) to Various Hyperoxic Regimes

Authors: V. Stejskal, K. Lundova, R. Sebesta, T. Vanina, S. Roje

Abstract:

Pure strain of Arctic char (AC) Salvelinus alpinus and hybrid (HB) Salvelinus alpinus vs. Salvelinus fontinalis Mitchill belong to fish, which with great potential for culture in recirculating aquaculture systems (RAS). Aquaculture of these fish currently use flow-through systems (FTS), especially in Nordic countries such as Iceland (biggest producer), Norway, Sweden, and Canada. Four different water saturation regimes included normoxia (NOR), permanent hyperoxia (HYP), intermittent hyperoxia (HYP ± ) and regimes where one day of normoxia was followed by one day of hyperoxia (HYP1/1) were tested during 63 days of experiment in both species in two parallel experiments. Fish were reared in two identical RAS system consisted of 24 plastic round tanks (300 L each), drum filter, biological filter with moving beads and submerged biofilter. The temperature was maintained using flow-through cooler during at level of 13.6 ± 0.8 °C. Different water saturation regimes were achieved by mixing of pure oxygen (O₂) with water in three (one for each hyperoxic regime) mixing tower equipped with flowmeter for regulation of gas inflow. The water in groups HYP, HYP1/1 and HYP± was enriched with oxygen up to saturation of 120-130%. In HYP group was this level kept during whole day. In HYP ± group was hyperoxia kept for daylight phase (08:00-20:00) only and during night time was applied normoxia in this group. The oxygen saturation of 80-90% in NOR group was created using intensive aeration in header tank. The fish were fed with commercial feed to slight excess at 2 h intervals within the light phase of the day. Water quality parameters like pH, temperature and level of oxygen was monitoring three times (7 am, 10 am and 6 pm) per day using handy multimeter. Ammonium, nitrite and nitrate were measured in two day interval using spectrophotometry. Initial body weight (BW) was 40.9 ± 8.7 g and 70.6 ± 14.8 in AC and HB group, respectively. Final survival of AC ranged from 96.3 ± 4.6 (HYP) to 100 ± 0.0% in all other groups without significant differences among these groups. Similarly very high survival was reached in trial with HB with levels from 99.2 ± 1.3 (HYP, HYP1/1 and NOR) to 100 ± 0.0% (HYP ± ). HB fish showed best growth performance in NOR group reached final body weight (BW) 180.4 ± 2.3 g. Fish growth under different hyperoxic regimes was significantly reduced and final BW was 164.4 ± 7.6, 162.1 ± 12.2 and 151.7 ± 6.8 g in groups HY1/1, HYP ± and HYP, respectively. AC showed different preference for hyperoxic regimes as there were no significant difference in BW among NOR, HY1/1 and HYP± group with final values of 72.3 ± 11.3, 68.3 ± 8.4 and 77.1 ± 6.1g. Significantly reduced growth (BW 61.8 ± 6.8 g) was observed in HYP group. It is evident from present study that there are differences between pure bred Arctic char and hybrid in relation to hyperoxic regimes. The study was supported by projects 'CENAKVA' (No. CZ.1.05/2.1.00/01.0024), 'CENAKVA II' (No. LO1205 under the NPU I program), NAZV (QJ1510077) and GAJU (No. 060/2016/Z).

Keywords: recirculating aquaculture systems, Salmonidae, hyperoxia, abiotic factors

Procedia PDF Downloads 182
24773 Decision Quality as an Antecedent to Export Performance. Empirical Evidence under a Contingency Theory Lens

Authors: Evagelos Korobilis-Magas, Adekunle Oke

Abstract:

The constantly increasing tendency towards a global economy and the subsequent increase in exporting, as a result, has inevitably led to a growing interest in the topic of export success as well. Numerous studies, particularly in the past three decades, have examined a plethora of determinants to export performance. However, to the authors' best knowledge, no study up to date has ever considered decision quality as a potential antecedent to export success by attempting to test the relationship between decision quality and export performance. This is a surprising deficiency given that the export marketing literature has long ago suggested that quality decisions are regarded as the crucial intervening variable between sound decision–making and export performance. This study integrates the different definitions of decision quality proposed in the literature and the key themes incorporated therein and adapts it to an export context. Apart from laying the conceptual foundations for the delineation of this elusive but very important construct, this study is the first ever to test the relationship between decision quality and export performance. Based on survey data from a sample of 189 British export decision-makers and within a contingency theory framework, the results reveal that there is a direct, positive link between decision quality and export performance. This finding opens significant future research avenues and has very important implications for both theory and practice.

Keywords: export performance, decision quality, mixed methods, contingency theory

Procedia PDF Downloads 95
24772 Seismic Analysis of Vertical Expansion Hybrid Structure by Response Spectrum Method Concern with Disaster Management and Solving the Problems of Urbanization

Authors: Gautam, Gurcharan Singh, Mandeep Kaur, Yogesh Aggarwal, Sanjeev Naval

Abstract:

The present ground reality scenario of suffering of humanity shows the evidence of failure to take wrong decisions to shape the civilization with Irresponsibilities in the history. A strong positive will of right responsibilities make the right civilization structure which affects itself and the whole world. Present suffering of humanity shows and reflect the failure of past decisions taken to shape the true culture with right social structure of society, due to unplanned system of Indian civilization and its rapid disaster of population make the failure to face all kind of problems which make the society sufferer. Our India is still suffering from disaster like earthquake, floods, droughts, tsunamis etc. and we face the uncountable disaster of deaths from the beginning of humanity at the present time. In this research paper our focus is to make a Disaster Resistance Structure having the solution of dense populated urban cities area by high vertical expansion HYBRID STRUCTURE. Our efforts are to analyse the Reinforced Concrete Hybrid Structure at different seismic zones, these concrete frames were analyzed using the response spectrum method to calculate and compare the different seismic displacement and drift. Seismic analysis by this method generally is based on dynamic analysis of building. Analysis results shows that the Reinforced Concrete Building at seismic Zone V having maximum peak story shear, base shear, drift and node displacement as compare to the analytical results of Reinforced Concrete Building at seismic Zone III and Zone IV. This analysis results indicating to focus on structural drawings strictly at construction site to make a HYBRID STRUCTURE. The study case is deal with the 10 story height of a vertical expansion Hybrid frame structure at different zones i.e. zone III, zone IV and zone V having the column 0.45x0.36mt and beam 0.6x0.36mt. with total height of 30mt, to make the structure more stable bracing techniques shell be applied like mage bracing and V shape bracing. If this kind of efforts or structure drawings are followed by the builders and contractors then we save the lives during earthquake disaster at Bhuj (Gujarat State, India) on 26th January, 2001 which resulted in more than 19,000 deaths. This kind of Disaster Resistance Structure having the capabilities to solve the problems of densely populated area of cities by the utilization of area in vertical expansion hybrid structure. We request to Government of India to make new plans and implementing it to save the lives from future disasters instead of unnecessary wants of development plans like Bullet Trains.

Keywords: history, irresponsibilities, unplanned social structure, humanity, hybrid structure, response spectrum analysis, DRIFT, and NODE displacement

Procedia PDF Downloads 211
24771 Evaluation and Selection of Elite Jatropha Genotypes for Biofuel

Authors: Bambang Heliyanto, Rully Dyah Purwati, Hasnam, Fadjry Djufry

Abstract:

Jatropha curcas L., a drought tolerant and monoecious perennial shrub, has received attention worldwide during the past decade. Realizing the facts, the Indonesian government has decided to option for Jatropha and palm oil for in country biofuel production. To support the program development of high yielding jatropha varieties is necessary. This paper reviews Jatropha improvement program in Indonesia using mass selection and hybrid development. To start with, at the end of 2005, in-country germplasm collection was mobilized to Lampung and Nusa Tenggara Barat (NTB) provinces and successfully collected 15 provenances/sub-provenances which serves as a base population for selection. A significant improvement has been achieved through a simple recurrent breeding selection during 2006 to 2007. Seed yield productivity increased more than double, from 0.36 to 0.97 ton dry seed per hectare during the first selection cycle (IP-1), and then increased to 2.2 ton per hectare during the second cycles (IP-2) in Lampung provenance. Similar result was also observed in NTB provenance. Seed yield productivity increased from 0.43 ton to 1 ton dry seed per hectare in the first cycle (IP-1), and then 1.9 ton in the second cycle (IP-2). In 2008, the population IP-3 resulted from the third cycle of selection have been identified which were capable of producing 2.2 to 2.4 ton seed yield per hectare. To improve the seed yield per hectare, jatropha hybrid varieties was developed involving superior provenances. As a result a Jatropha Energy Terbarukan (JET) variety-2 was released in 2017 with seed yield potential of 2.6 ton per hectare. The use of this high yielding genotypes for biofuel is discussed.

Keywords: Jatropha curcas, provenance, biofuel, improve population, hybrid

Procedia PDF Downloads 171
24770 Model Driven Architecture Methodologies: A Review

Authors: Arslan Murtaza

Abstract:

Model Driven Architecture (MDA) is technique presented by OMG (Object Management Group) for software development in which different models are proposed and converted them into code. The main plan is to identify task by using PIM (Platform Independent Model) and transform it into PSM (Platform Specific Model) and then converted into code. In this review paper describes some challenges and issues that are faced in MDA, type and transformation of models (e.g. CIM, PIM and PSM), and evaluation of MDA-based methodologies.

Keywords: OMG, model driven rrchitecture (MDA), computation independent model (CIM), platform independent model (PIM), platform specific model(PSM), MDA-based methodologies

Procedia PDF Downloads 459
24769 Evaluating the Performance of Existing Full-Reference Quality Metrics on High Dynamic Range (HDR) Video Content

Authors: Maryam Azimi, Amin Banitalebi-Dehkordi, Yuanyuan Dong, Mahsa T. Pourazad, Panos Nasiopoulos

Abstract:

While there exists a wide variety of Low Dynamic Range (LDR) quality metrics, only a limited number of metrics are designed specifically for the High Dynamic Range (HDR) content. With the introduction of HDR video compression standardization effort by international standardization bodies, the need for an efficient video quality metric for HDR applications has become more pronounced. The objective of this study is to compare the performance of the existing full-reference LDR and HDR video quality metrics on HDR content and identify the most effective one for HDR applications. To this end, a new HDR video data set is created, which consists of representative indoor and outdoor video sequences with different brightness, motion levels and different representing types of distortions. The quality of each distorted video in this data set is evaluated both subjectively and objectively. The correlation between the subjective and objective results confirm that VIF quality metric outperforms all to their tested metrics in the presence of the tested types of distortions.

Keywords: HDR, dynamic range, LDR, subjective evaluation, video compression, HEVC, video quality metrics

Procedia PDF Downloads 525
24768 Development of the Internal Educational Quality Assurance System of Suan Sunandha Rajabhat University

Authors: Nipawan Tharasak, Sajeewan Darbavasu

Abstract:

This research aims 1) to study the opinion, problems and obstacles to internal educational quality assurance system for individual and the university levels, 2) to propose an approach to the development of quality assurance system of Suan Sunandha Rajabhat University. A study of problems and obstacles to internal educational quality assurance system of the university conducted with sample group consisting of staff and quality assurance committee members of the year 2010. There were 152 respondents. 5 executives were interviewed. Tool used in the research was document analysis. The structure of the interview questions and questionnaires with 5-rate scale. Reliability was 0.981. Data analysis were percentage, mean and standard deviation with content analysis. Results can be divided into 3 main points: (1) The implementation of the internal quality assurance system of the university. It was found that in overall, input, process and output factors received high scores. Each item is considered, the preparation, planning, monitoring and evaluation. The results of evaluation to improve the reporting and improvement according to an evaluation received high scores. However, the process received an average score. (2) Problems and obstacles. It was found that the personnel responsible for the duty still lack understanding of indicators and criteria of the quality assurance. (3) Development approach: -Staff should be encouraged to develop a better understanding of the quality assurance system. -Database system for quality assurance should be developed. -The results and suggestions should be applied in the next year development planning.

Keywords: development system, internal quality assurance, education, educational quality assurance

Procedia PDF Downloads 298
24767 Dynamic Modeling of Energy Systems Adapted to Low Energy Buildings in Lebanon

Authors: Nadine Yehya, Chantal Maatouk

Abstract:

Low energy buildings have been developed to achieve global climate commitments in reducing energy consumption. They comprise energy efficient buildings, zero energy buildings, positive buildings and passive house buildings. The reduced energy demands in Low Energy buildings call for advanced building energy modeling that focuses on studying active building systems such as heating, cooling and ventilation, improvement of systems performances, and development of control systems. Modeling and building simulation have expanded to cover different modeling approach i.e.: detailed physical model, dynamic empirical models, and hybrid approaches, which are adopted by various simulation tools. This paper uses DesignBuilder with EnergyPlus simulation engine in order to; First, study the impact of efficiency measures on building energy behavior by comparing Low energy residential model to a conventional one in Beirut-Lebanon. Second, choose the appropriate energy systems for the studied case characterized by an important cooling demand. Third, study dynamic modeling of Variable Refrigerant Flow (VRF) system in EnergyPlus that is chosen due to its advantages over other systems and its availability in the Lebanese market. Finally, simulation of different energy systems models with different modeling approaches is necessary to confront the different modeling approaches and to investigate the interaction between energy systems and building envelope that affects the total energy consumption of Low Energy buildings.

Keywords: physical model, variable refrigerant flow heat pump, dynamic modeling, EnergyPlus, the modeling approach

Procedia PDF Downloads 222