Search results for: accuracy of payment time

Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

Procedia PDF Downloads 171

Authors: Irfan Anjum Manarvi, Fawzi Aljassir

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Human bones have been a keen area of research over a long time in the field of biomechanical engineering. Medical professionals, as well as engineering academics and researchers, have investigated various bones by using medical, mechanical, and materials approaches to discover the available body of knowledge. Their major focus has been to establish properties of these and ultimately develop processes and tools either to prevent fracture or recover its damage. Literature shows that mechanical professionals conducted a variety of tests for hardness, deformation, and strain field measurement to arrive at their findings. However, they considered these results accuracy to be insufficient due to various limitations of tools, test equipment, difficulties in the availability of human bones. They proposed the need for further studies to first overcome inaccuracies in measurement methods, testing machines, and experimental errors and then carry out experimental or theoretical studies. Finite Element analysis is a technique which was developed for the aerospace industry due to the complexity of design and materials. But over a period of time, it has found its applications in many other industries due to accuracy and flexibility in selection of materials and types of loading that could be theoretically applied to an object under study. In the past few decades, the field of biomechanical engineering has also started to see its applicability. However, the work done in the area of Tarsals, metatarsals and phalanges using this technique is very limited. Therefore, present research has been focused on using this technique for analysis of these critical bones of the human body. This technique requires a 3-dimensional geometric computer model of the object to be analyzed. In the present research, a 3d laser scanner was used for accurate geometric scans of individual tarsals, metatarsals, and phalanges from a typical human foot to make these computer geometric models. These were then imported into a Finite Element Analysis software and a length refining process was carried out prior to analysis to ensure the computer models were true representatives of actual bone. This was followed by analysis of each bone individually. A number of constraints and load conditions were applied to observe the stress and strain distributions in these bones under the conditions of compression and tensile loads or their combination. Results were collected for deformations in various axis, and stress and strain distributions were observed to identify critical locations where fracture could occur. A comparative analysis of failure properties of all the three types of bones was carried out to establish which of these could fail earlier which is presented in this research. Results of this investigation could be used for further experimental studies by the academics and researchers, as well as industrial engineers, for development of various foot protection devices or tools for surgical operations and recovery treatment of these bones. Researchers could build up on these models to carryout analysis of a complete human foot through Finite Element analysis under various loading conditions such as walking, marching, running, and landing after a jump etc.

Keywords: tarsals, metatarsals, phalanges, 3D scanning, finite element analysis

Procedia PDF Downloads 314

Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

Procedia PDF Downloads 109

Authors: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

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In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: parameterization, response surface, structure optimization, pressure hull

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Authors: Solmaz Jahed Shiran, Elizabeth Taylor, John Hearne

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Over the past decade a growing body of research, known as mobility biography approach has emerged that focuses on changes in travel behaviour over the life course of individuals. Mobility biographies suggest that changes in travel behaviour have a certain relation to important key events in life courses such as residential relocation, workplace changes, marriage and the birth of children. Taking this approach as the theoretical background, this study uses data from the Household, Income and Labor Dynamics Survey in Australia (HILDA) to model a set of life course events and their interaction with the commute time. By analysing longitudinal data, it is possible to assign different key events during the life course to change a person’s travel behaviour. Changes in the journey-to-work travel time is used as an indication of travel behaviour change in this study. Results of a linear regression model for change in commute time show a significant influence from socio-demographic factors like income and age, the previous home-to-work commute time and remoteness of the residence. Residential relocation and job change have significant influences on commute time. Other life events such as birth of a child, marriage and divorce or separation have also a strong impact on commute time change. Overall, the research confirms previous studies of links between life course events and travel behaviour.

Keywords: life course events, residential mobility, travel behaviour, commute time, job change

Procedia PDF Downloads 188

Authors: Bara' Al-Mistarehi

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Documentation and assessment of conservation state of an archaeological structure is a significant procedure in any management plan. However, it has always been a challenge to apply this with a low coast and safe methodology. It is also a time-demanding procedure. Therefore, a low cost, efficient methodology for documenting the state of a structure is needed. In the scope of this research, this paper will employ digital photogrammetry and laser scanner to one of highly significant structures in Germany, The Old Castle (German: Altes Schloss). The site is well known for its unique features. However, the castle suffers from serious deterioration threats because of the environmental conditions and the absence of continuous monitoring, maintenance and repair plans. Digital photogrammetry is a generally accepted technique for the collection of 3D representations of the environment. For this reason, this image-based technique has been extensively used to produce high quality 3D models of heritage sites and historical buildings for documentation and presentation purposes. Additionally, terrestrial laser scanners are used, which directly measure 3D surface coordinates based on the run-time of reflected light pulses. These systems feature high data acquisition rates, good accuracy and high spatial data density. Despite the potential of each single approach, in this research work maximum benefit is to be expected by a combination of data from both digital cameras and terrestrial laser scanners. Within the paper, the usage, application and advantages of the technique will be investigated in terms of building high realistic 3D textured model for some parts of the old castle. The model will be used as diagnosing tool of the conservation state of the castle and monitoring mean for future changes.

Keywords: Digital photogrammetry, Terrestrial laser scanners, 3D textured model, archaeological structure

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Authors: Abdul Hakim Chikho

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Calculating the ultimate load of a column in a sway framed structure involves, in the currently used design method, the calculation of the column effective length and utilizing the interaction formulas or tables. Therefore, no allowance is usually made for the effects of the presence of semi rigid connections or the presence of infill panels. In this paper, a new and simple design procedure is recommend to calculate the ultimate load of a framed Column allowing for the presence of rotational end restraints, semi rigid connections, the column end moments resulted from the applied vertical and horizontal loading and infill panels in real steel structure. In order to verify the accuracy of the recommended method to predict good and safe estimations of framed column ultimate loads, several examples have been solved utilizing the recommended procedure, and the results were compared to those obtained using a second order computer program, and good correlation had been obtained. Therefore, the accuracy of the proposed method to predict the Behaviour of practical steel columns in framed structures has been verified.

Keywords: column ultimate load, semi rigid connections, steel column, infill panel, steel structure

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Authors: Hilary Rutto, Mbali Chiliza, Tumisang Seodigeng

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The study on reactivity of calcined calcium-based material is very important in dry flue gas desulphurisation (FGD) process, so as to produce absorbent with high sulphur dioxide capture capacity during the hydration process. The effect of calcining temperature and time on the reactivity of calcined limestone material were investigated. In this study, the reactivity was measured using a pH stat apparatus and also confirming the result by performing citric acid reactivity test. The reactivity was calculated using the shrinking core model. Based on the experiments, a mathematical model is developed to correlate the effect of time and temperature to the reactivity of absorbent. The calcination process variables were temperature (700 -1000°C) and time (1-6 hrs). It was found that reactivity increases with an increase in time and temperature.

Keywords: reactivity, citric acid, calcination, time

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Authors: Satyanarayana Engu, Ahmed Mohd, V. Murugan

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We study the large time asymptotics of solutions to the Cauchy problem for a forced Burgers equation (FBE) with the initial data, which is continuous and summable on R. For which, we first derive explicit solutions of FBE assuming a different class of initial data in terms of Hermite polynomials. Later, by violating this assumption we prove the existence of a solution to the considered Cauchy problem. Finally, we give an asymptotic approximate solution and establish that the error will be of order O(t^(-1/2)) with respect to L^p -norm, where 1≤p≤∞, for large time.

Keywords: Burgers equation, Cole-Hopf transformation, Hermite polynomials, large time asymptotics

Procedia PDF Downloads 317

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Heungsu Lee, Youngseok Kim, Jonghwa Yi, Chul Park

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A landing pier is subjected to safety assessment by visual inspection and design data, but it is difficult to check the damage in real-time. In this study, real - time damage detection and safety evaluation methods were studied. As a result of structural analysis of the arbitrary landing pier structure, the inflection point of deformation and moment occurred at 10%, 50%, and 90% of pile length. The critical value of Fiber Bragg Grating (FBG) sensor was set according to the safety factor, and the FBG sensor application method for real - time safety evaluation was derived.

Keywords: FBG sensor, harbor structure, maintenance, safety evaluation system

Procedia PDF Downloads 195

Authors: Ting (Grace) Lin, Jianhong (Cecilia) Xia, Todd Robinson

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Accessibility analysis, examining people’s ability to access facilities and destinations, is a fundamental assessment for transport planning, policy making, and social exclusion research. Dynamic accessibility which measures accessibility in real-time traffic environment has been an advanced accessibility indicator in transport research. It is also a useful indicator to help travelers to understand travel time daily variability, assists traffic engineers to monitor traffic congestions, and finally develop effective strategies in order to mitigate traffic congestions. This research involved real-time traffic information by collecting travel time data with 15-minute interval via the TomTom^® API. A framework for measuring dynamic accessibility was then developed based on the gravity theory and accessibility dichotomy theory through space and time interpolation. Finally, the dynamic accessibility can be derived at any given time and location under dynamic accessibility spatial analysis framework.

Keywords: dynamic accessibility, hot spot, transport research, TomTom® API

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Authors: Aydin Azizi, Poorya Ghafoorpoor Yazdi

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This paper presents the review of the studies on the ergonomics, virtual reality, and work measurement (time study) at the industrial workstations because each of these three individual techniques can be used to improve the design of workstations and task position. The objective of this paper is to give an overall literature review that if there is any relation between these three different techniques. Therefore, it is so important to review the scientific studies to find a better and effective way for improving design of workstations. On the other hand, manufacturers found that instead of using one of the approaches, utilizing the combination of these individual techniques are more effective to reduce the cost and production time.

Keywords: ergonomics, time study, virtual reality, workplace

Procedia PDF Downloads 107

Authors: Hasan Al Bashar Abul Ulayee, AKM Saifun Nabi, MD Mesbah-Ul-Awal

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Alert system for disaster management is common now a day and can play a vital role reducing devastation and saves lives and costs. An alert in right time can save thousands of human life, help to take shelter, manage other assets including live stocks and above all, a right time alert will help to take preparation to face and early recovery of the situation. In a country like Bangladesh where populations is more than 170 million and always facing different types of natural calamities and disasters, an early right time alert is very effective and implementation of alert system is challenging. The challenge comes from the time constraint of alerting the huge number of population. The other method of existing disaster management pre alert is traditional, sequential and non-selective so efficiency is not good enough. This paper describes a way by which alert can be provided to maximum number of people within the short time bound using parallel processing as well as random selection of selective target audience.

Keywords: alert system, Bangladesh, disaster management, parallel processing, SMS

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

Procedia PDF Downloads 142

Authors: Mariana Roberta Ribeiro, Isabela de Cássia Caramello, Roberto Saverio Souza Costa

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Currently, one of the most important environmental problems is soil degradation. This wear is the result of inadequate agricultural practices, with water erosion as the main agent. As the runoff water is concentrated in certain points, it can reach a more advanced stage, which are the gullies. In view of this, the objective of this work was to evaluate which methodology is most suitable for the purpose of elaborating a project for the recovery of a gully, relating work time, data reliability, and the final cost. The work was carried out on a rural road in Monte Alto - SP, where there is 0.30 hectares of area under the influence of a gully. For the evaluation, an aerophotogrammetric survey was used with RPA, with georeferenced points, and with a GNSS L1/L2 receiver. To assess the importance of georeferenced points, there was a comparison of altimetric data using the support points with altimetric data using only the aircraft's internal GPS. Another method used was the survey by conventional topography, where coordinates were collected by total station and L1/L2 Geodetic GPS receiver. Statistical analysis was performed using analysis of variance (ANOVA) using the F test (p<0.05), and the means between treatments were compared using the Tukey test (p<0.05). The results showed that the surveys carried out by aerial photogrammetry and by conventional topography showed no significant difference for the analyzed parameters. Considering the data presented, it is possible to conclude that, when comparing the parameters of accuracy, the final volume of the gully, and cost, for the purpose of elaborating a project for the recovery of a gully, the methodologies of aerial photogrammetric survey and conventional topography do not differ significantly. However, when working time, use of labor, and project detail are compared, the aerial photogrammetric survey proves to be more viable.

Keywords: drones, erosion, soil conservation, technology in agriculture

Procedia PDF Downloads 93

Authors: Hee-Jae Suh, Kyung-Su Kim, Min-Ji Kim, Yeon-Seong Jeong, Ok-Hwan Lee, Jae-Wook Shin, Hyang-Sook Chun, Chan Lee

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Canthaxanthin is keto-carotenoid produced from beta-carotene and it has been approved to be used in many countries as a food coloring agent. Canthaxanthin has been analyzed using High Performance Liquid Chromatography (HPLC) system with various ways of pretreatment methods. Four official methods for verification of canthaxanthin at FSA (UK), AOAC (US), EFSA (EU) and MHLW (Japan) were compared to improve its analytical and the pretreatment method. The Linearity, the limit of detection (LOD), the limit of quantification (LOQ), the accuracy, the precision and the recovery ratio were determined from each method with modification in pretreatment method. All HPLC methods exhibited correlation coefficients of calibration curves for canthaxanthin as 0.9999. The analysis methods from FSA, AOAC, and MLHW showed the LOD of 0.395 ppm, 0.105 ppm, and 0.084 ppm, and the LOQ of 1.196 ppm, 0.318 ppm, 0.254 ppm, respectively. Among tested methods, HPLC method of MHLW with modification in pretreatments was finally selected for the analysis of canthaxanthin in lab, because it exhibited the resolution factor of 4.0 and the selectivity of 1.30. This analysis method showed a correlation coefficients value of 0.9999 and the lowest LOD and LOQ. Furthermore, the precision ratio was lower than 1 and the accuracy was almost 100%. The method presented the recovery ratio of 90-110% with modification in pretreatment method. The cross-validation of coefficient variation was 5 or less among tested three institutions in Korea.

Keywords: analytic method, canthaxanthin, food colorants, pretreatment method

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Authors: Kazım Kaba, Erdem Erdi, M. Akif Erdoğan, H. Mustafa Kandırmaz

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Rainfall is crucial data source for very different discipline such as agriculture, hydrology and climate. Therefore rain rate should be known well both spatial and temporal for any area. Rainfall is measured by using rain-gauge at meteorological ground stations traditionally for many years. At the present time, rainfall products are acquired from radar and satellite images with a temporal and spatial continuity. In this study, we investigated the accuracy of these rainfall data according to rain-gauge data. For this purpose, we used Adana-Hatay radar hourly total precipitation product (RN1) and Meteosat convective rainfall rate (CRR) product over Seyhan plain. We calculated daily rainfall values from RN1 and CRR hourly precipitation products. We used the data of rainy days of four stations located within range of the radar from October 2013 to November 2015. In the study, we examined two rainfall data over Seyhan plain and the correlation between the rain-gauge data and two raster rainfall data was observed lowly.

Keywords: meteosat, radar, rainfall, rain-gauge, Turkey

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Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

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Authors: Qian Yi Ooi

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At present, airfoil parameters are still designed and optimized according to the scale of conventional aircraft, and there are still some slight deviations in terms of scale differences. However, insufficient parameters or poor surface mesh quality is likely to occur if these small deviations are embedded in a future civil aircraft with a size that is quite different from conventional aircraft, such as a blended-wing-body (BWB) aircraft with future potential, resulting in large deviations in geometric similarity in computational fluid dynamics (CFD) simulations. To avoid this situation, the study on the CFD calculation on the geometric similarity of airfoil parameters and the quality of the surface mesh is conducted to obtain the ability of different parameterization methods applied on different airfoil scales. The research objects are three airfoil scales, including the wing root and wingtip of conventional civil aircraft and the wing root of the giant hybrid wing, used by three parameterization methods to compare the calculation differences between different sizes of airfoils. In this study, the constants including NACA 0012, a Reynolds number of 10 million, an angle of attack of zero, a C-grid for meshing, and the k-epsilon (k-ε) turbulence model are used. The experimental variables include three airfoil parameterization methods: point cloud method, B-spline curve method, and class function/shape function transformation (CST) method. The airfoil dimensions are set to 3.98 meters, 17.67 meters, and 48 meters, respectively. In addition, this study also uses different numbers of edge meshing and the same bias factor in the CFD simulation. Studies have shown that with the change of airfoil scales, different parameterization methods, the number of control points, and the meshing number of divisions should be used to improve the accuracy of the aerodynamic performance of the wing. When the airfoil ratio increases, the most basic point cloud parameterization method will require more and larger data to support the accuracy of the airfoil’s aerodynamic performance, which will face the severe test of insufficient computer capacity. On the other hand, when using the B-spline curve method, average number of control points and meshing number of divisions should be set appropriately to obtain higher accuracy; however, the quantitative balance cannot be directly defined, but the decisions should be made repeatedly by adding and subtracting. Lastly, when using the CST method, it is found that limited control points are enough to accurately parameterize the larger-sized wing; a higher degree of accuracy and stability can be obtained by using a lower-performance computer.

Keywords: airfoil, computational fluid dynamics, geometric similarity, surface mesh quality

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Authors: Rogelio Luck, Yucheng Liu

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This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

Procedia PDF Downloads 141

Authors: Mahdiyeh Zafaranchi, Ethan S. Cantor, William T. Riddell, Jess W. Everett

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The New Jersey Department of Military and Veteran’s Affairs (NJ DMAVA) operates over 50 facilities throughout the state of New Jersey, U.S. NJDMAVA is under a mandate to move toward decarbonization, which will eventually include eliminating the use of natural gas and other fossil fuels for heating. At the same time, the organization requires increased resiliency regarding electric grid disruption. These competing goals necessitate adopting the use of on-site renewables such as photovoltaic and geothermal power, as well as implementing power control strategies through microgrids. Planning for these changes requires a detailed understanding of current and future electricity use on yearly, monthly, and shorter time scales, as well as a breakdown of consumption by heating, ventilation, and air conditioning (HVAC) equipment. This paper discusses case studies of two buildings that were simulated using the QUick Energy Simulation Tool (eQUEST). Both buildings use electricity from the grid and photovoltaics. One building also uses natural gas. While electricity use data are available in hourly intervals and natural gas data are available in monthly intervals, the simulations were developed using monthly and yearly totals. This approach was chosen to reflect the information available for most NJ DMAVA facilities. Once completed, simulation results are compared to metrics recommended by several organizations to validate energy use simulations. In addition to yearly and monthly totals, the simulated peak demands are compared to actual monthly peak demand values. The simulations resulted in monthly peak demand values that were within 30% of the measured values. These benchmarks will help to assess future energy planning efforts for NJ DMAVA.

Keywords: building energy modeling, eQUEST, peak demand, smart meters

Procedia PDF Downloads 52

Authors: Gert Van Schalkwyk, Chris Cloete

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South Africa is experiencing a massive housing backlog in urban low-cost housing. A backlog in the transfer of low-cost housing units is exacerbated by various impediments and delays that exist in the current legal framework. Structured interviews were conducted with forty-five practicing conveyancers and fifteen deeds office examiners at the Deeds Office in Pretoria, South Africa. One of the largest, the Deeds Office in Pretoria implements a uniform registration process and can be regarded as representative of other deeds offices in South Africa. It was established that a low percentage of low-cost properties are freely transferable. The main economic impediments are the absence of financing and the affordability or payment of rates and taxes to local government. Encroachment of buildings on neighboring stands caused by the enlargement of existing small units on small stands also causes long-term unresolved legal disputes. In addition, as the transfer of properties is dependent on the proper functioning of administrative functions of various government departments, the adverse service delivery of government departments hampers transfer. Addressing the identified problems will contribute to a more sustainable process for the transfer of low-cost housing units in South Africa.

Keywords: conveyancing, low-cost housing, South Africa, tenure, titling, transfer

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Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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Authors: Valeria Bondarenko

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We proposed algorithms for: estimation of parameters fBm (volatility and Hurst exponent) and for the approximation of random time series by functional of fBm. We proved the consistency of the estimators, which constitute the above algorithms, and proved the optimal forecast of approximated time series. The adequacy of estimation algorithms, approximation, and forecasting is proved by numerical experiment. During the process of creating software, the system has been created, which is displayed by the hierarchical structure. The comparative analysis of proposed algorithms with the other methods gives evidence of the advantage of approximation method. The results can be used to develop methods for the analysis and modeling of time series describing the economic, physical, biological and other processes.

Keywords: mathematical model, random process, Wiener process, fractional Brownian motion

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Authors: Vinesh Thiruchelvam, Umar Mumtaz Chowdry, Sathish Kumar Selvaperumal

Abstract:

The prime purpose of the project is to provide a sophisticated system for surveillance specialized for the Port Authorities in the Maritime Industry. The current aerial surveillance does not have a wide dimensioning view. The channels of communication is shared and not exclusive allowing for communications errors or disturbance mainly due to traffic. The scope is to analyze the various aspects as real-time aerial and marine surveillance is one of the most important methods which could ensure the domain security of the sailors. The system will improve real time data as obtained for the controller base station. The key implementation will be based on camera speed, angle and adherence to a sustainable power utilization module.

Keywords: SMS, real time, GUI, maritime industry

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Authors: Jin A Ryu, Hee Sun Kim

Abstract:

As the number of fire accidents is gradually raising, many studies have been reported on evacuation. Previous studies have mostly focused on evaluating the safety of evacuation and the risk of fire in particular buildings. However, studies on effects of various parameters on evacuation have not been nearly done. Therefore, this paper aims at observing evacuation time under the effect of fire initiated location. In this study, evacuation simulations are performed on a 5-floor building located in Seoul, South Korea using the commercial program, Fire Dynamics Simulator with Evacuation (FDS+EVAC). Only the fourth and fifth floors are modeled with an assumption that fire starts in a room located on the fourth floor. The parameter for evacuation simulations is location of fire initiation to observe the evacuation time and safety. Results show that the location of fire initiation is closer to exit, the more time is taken to evacuate. The case having the nearest location of fire initiation to exit has the lowest ratio of successful occupants to the total occupants. In addition, for safety evaluation, the evacuation time calculated from computer simulation model is compared with the tolerable evacuation time according to code in Japan. As a result, all cases are completed within the tolerable evacuation time. This study allows predicting evacuation time under various conditions of fire and can be used to evaluate evacuation appropriateness and fire safety of building.

Keywords: fire simulation, evacuation simulation, temperature, evacuation safety

Procedia PDF Downloads 325

Authors: V. S. S. Kumar, B. Vikram

Abstract:

The development of effective decision support tools that adopted in the construction industry is vital in the world we live in today, since it can lead to substantial cost reduction and efficient resource consumption. Solving the time-cost trade off problems and its related variants is at the heart of scientific research for optimizing construction planning problems. In general, the classical optimization techniques have difficulties in dealing with TCT problems. One of the main reasons of their failure is that they can easily be entrapped in local minima. This paper presents an investigation on the application of meta-heuristic techniques to two particular variants of the time-cost trade of analysis, the time-cost trade off problem (TCT), and time-cost trade off optimization problem (TCO). In first problem, the total project cost should be minimized, and in the second problem, the total project cost and total project duration should be minimized simultaneously. Finally it is expected that, the optimization models developed in this paper will contribute significantly for efficient planning and management of construction project.

Keywords: fuzzy sets, uncertainty, optimization, time cost trade off problems

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Authors: Fatema Akram, Mohammad Golam Rasul, Mohammad Masud Kamal Khan, Md. Sharif Imam Ibne Amir

Abstract:

A variety of routing techniques are available to develop surface runoff hydrographs from rainfall. The selection of runoff routing method is very vital as it is directly related to the type of watershed and the required degree of accuracy. There are different modelling softwares available to explore the rainfall-runoff process in urban areas. XPSTORM, a link-node based, integrated storm-water modelling software, has been used in this study for developing surface runoff hydrograph for a Golf course area located in Rockhampton in Central Queensland in Australia. Four commonly used methods, namely SWMM runoff, Kinematic wave, Laurenson, and Time-Area are employed to generate runoff hydrograph for design storm of this study area. In runoff mode of XPSTORM, the rainfall, infiltration, evaporation and depression storage for sub-catchments were simulated and the runoff from the sub-catchment to collection node was calculated. The simulation results are presented, discussed and compared. The total surface runoff generated by SWMM runoff, Kinematic wave and Time-Area methods are found to be reasonably close, which indicates any of these methods can be used for developing runoff hydrograph of the study area. Laurenson method produces a comparatively less amount of surface runoff, however, it creates highest peak of surface runoff among all which may be suitable for hilly region. Although the Laurenson hydrograph technique is widely acceptable surface runoff routing technique in Queensland (Australia), extensive investigation is recommended with detailed topographic and hydrologic data in order to assess its suitability for use in the case study area.

Keywords: ARI, design storm, IFD, rainfall temporal pattern, routing techniques, surface runoff, XPSTORM

Procedia PDF Downloads 441