Search results for: boundary element model

Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

Procedia PDF Downloads 453

Authors: Ensieh Hajeb, Hefzollah Mohammadiyan, Mohamad Baqer Heidari

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In this paper layout plans and determine the best place to install a heat recovery boilers , gas turbines , and simulation models built to evaluate the performance of the design and operating conditions, heat recovery boiler design using model built on the basis of operating conditions , the effect of various parameters on the performance of the designed heat recovery boiler , heat recovery boiler installation was designed to evaluate the technical and economic impact on performance would be Turbo generator. Given the importance of this issue, that is the main goal of economic efficiency and reduces costs; this project has been implemented similar plans in which the target is implementation specific patterns. The project will also help us in the process of gas refineries and the actual efficiency of the process after adding a system to analyze the turbine and predict potential problems and how to fix them and appropriate measures according to the results of simulation analysis and results of the process gain. The results of modeling and the effect of different parameters on this line, the software has been ThermoFlow.

Keywords: boiler, gas turbine, turbo generator, power flow

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

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Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

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Authors: Khaled M.Naguib, Ahmed M.Noureldin

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This paper aims to achieve many goals such as knowing (quantities produced- main properties- characteristics) of sludge produced from Bahr EL-Baqar drains treatment plant. This prediction or projection was made by laboratory analysis and modelling of Model samples from sludge depending on many studies that have previously done, second check the feasibility and do a risk analysis to know the best alternatives for reuse in producing secondary products that add value to sludge. Also, to know alternatives that have no value to add. All recovery methods are relatively very expensive and challenging to be done in this mega plant, so the recommendation from this study is to use the sludge as a coagulant to reduce some compounds or in secondary products. The study utilized sludge-cement replacement percentages of 10%, 20%, 30%, 40% and 50%. Produced tiles were tested for water absorption and breaking (bending) strength. The study showed that all produced tiles exhibited a water absorption ratio of around 10%. The study concluded that produced tiles, except for 50% sludge-cement replacement, comply with the breaking strength requirements of 2.8 MPa for tiles for external use.

Keywords: cement, tiles, water treatment sludge, breaking strength, absorption, heavy metals, risk analysis

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Authors: Ali Khaleel Kareem, Shian Gao, Ahmed Qasim Ahmed

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A numerical investigation of unsteady mixed convection heat transfer in a 3D moving top wall enclosure, which has a central rotating cylinder and uses either artificial roughness on the bottom hot plate or smooth bottom hot plate to study the heat transfer enhancement, is completed for fixed circular cylinder, and anticlockwise and clockwise rotational speeds, -1 ≤ Ω ≤ 1, at Reynolds number of 5000. The top lid-driven wall was cooled, while the other remaining walls that completed obstructed cubic were kept insulated and motionless. A standard k-ε model of Unsteady Reynolds-Averaged Navier-Stokes (URANS) method is involved to deal with turbulent flow. It has been clearly noted that artificial roughness can strongly control the thermal fields and fluid flow patterns. Ultimately, the heat transfer rate has been dramatically increased by involving artificial roughness on the heated bottom wall in the presence of rotating cylinder.

Keywords: artificial roughness, lid-driven cavity, mixed convection heat transfer, rotating cylinder, URANS method

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Authors: Nurul Izzah Ibrahim, Isa Naina Mohamed, Norazlina Mohamed, Ahmad Nazrun Shuid

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Osteoporosis disease delays fracture healing. Statins have shown potential for osteoporosis and to promote fracture healing. The effects of statin can be further potentiated by combining it with a carrier known as poly-(DL-lactide), which would provide persistent release of statin to the fracture site. This study was designed to investigate the effects of direct injection of poly-(DL-lactide)-incorporated lovastatin on fracture healing of postmenopausal osteoporosis rat model. Twenty-four Sprague-Dawley female rats were divided into 3 groups: sham-operated (SO), ovariectomized-control rats (OVxC) and poly-(DL-lactide)-incorporated lovastatin (OVx+Lov) groups. The OVx+Lov group was given a single injection of 750 µg/kg lovastatin particles incorporated with poly-(DL-lactide). After 4 weeks, the fractured tibiae were dissected out for biomechanical assessments of the callus. The OVx+Lov group showed significantly better callus strength than the OVxC group (p<0.05). In conclusion, a single injection of lovastatin-incorporated poly-(DL-lactide) was able to promote better fracture healing of osteoporotic bone.

Keywords: statins, fracture healing, osteoporosis, poly-(DL-lactide)

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Authors: G. Lei, P. C. Dong, X. Q. Cen, S. Y. Mo

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One of the most significant parameters, describing the effect of water flooding in porous media, is flood-response time, and it is an important index in oilfield development. The responding time in low permeability reservoir is usually calculated by the method of stable state successive substitution neglecting the effect of medium deformation. Numerous studies show that the media deformation has an important impact on the development for low permeability reservoirs and can not be neglected. On the base of streamline tube model, we developed a method to interpret responding time with medium deformation factor. The results show that: the media deformation factor, threshold pressure gradient and well spacing have a significant effect on the flood response time. The greater the media deformation factor, threshold pressure gradient or well spacing is, the lower the flood response time is. The responding time of different streamlines varies. As the angle with the main streamline increases, the water flooding response time delays as a "parabola" shape.

Keywords: low permeability, flood-response time, threshold pressure gradient, medium deformation

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Authors: Javier Menéndez, Jorge Loredo

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Large scale energy storage systems (LSESS) such as pumped-storage hydro-power (PSH) are required in the current energy transition towards a low carbon economy by using green energies that produce low levels of greenhouse gas (GHG) emissions. Coal mines are currently being closed in the European Union and their underground facilities may be used to build PSH plants. However, the development of this projects requires the excavation of a network of tunnels and a large cavern that would be used as a powerhouse to install the Francis turbine and motor-generator. The technical feasibility to excavate the powerhouse cavern has been analyzed in the North of Spain. Three-dimensional numerical models have been conducted to analyze the stability considering shale and sandstone rock mass. Total displacements and thickness of plastic zones were examined considering different support systems. Systematic grouted rock bolts and fibre reinforced shotcrete were applied at the cavern walls and roof. The results obtained show that the construction of the powerhouse is feasible applying proper support systems.

Keywords: closed mines, mine water, numerical model, pumped-storage, renewable energies

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Authors: John Onyima, Ikechukwu Ezepue

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Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

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Authors: Xinyi Xu

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This study conducts a detailed examination of Asian stock markets over the period from 2008 to 2023, with a focus on the dynamics of cointegration and their relevance for long-term investment strategies. Specifically, we assess the co-movement and potential for pairs trading—a strategy where investors take opposing positions on two stocks, indices, or financial instruments that historically move together. For example, we explore the relationship between the Nikkei 225 (N225), Japan’s benchmark stock index, and the Straits Times Index (STI) of Singapore, as well as the relationship between the Korea Composite Stock Price Index (KS11) and the STI. The methodology includes tests for normality, stationarity, cointegration, and the application of Vector Error Correction Modeling (VECM). Our findings reveal significant long-term relationships between these pairs, indicating opportunities for pairs trading strategies. Furthermore, the research underscores the challenges posed by model instability and the influence of major global incidents, which are identified as structural breaks. These findings pave the way for further exploration into the intricacies of financial market dynamics.

Keywords: normality tests, stationarity, cointegration, VECM, pairs trading

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Authors: Fekadu L. Bayisa, Elvan Ceyhan, Todd D. Steury

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Interaction between individuals within the same species is an important component of population dynamics. An interaction can be either static (based on spatial overlap) or dynamic (based on movement interactions). Using GPS collar data, we can quantify both static and dynamic interactions between black bears. The goal of this work is to determine the level of black bear interactions using the 95% and 50% home ranges, as well as to model black bear spatial interactions, which could be attraction, avoidance/repulsion, or a lack of interaction at all, to gain new insights and improve our understanding of ecological processes. Recent methodological developments in home range estimation, inhomogeneous multitype/cross-type summary statistics, and envelope testing methods are explored to study the nature of black bear interactions. Our findings, in general, indicate that the black bears of one type in our data set tend to cluster around another type.

Keywords: autocorrelated kernel density estimator, cross-type summary function, inhomogeneous multitype Poisson process, kernel density estimator, minimum convex polygon, pointwise and global envelope tests

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Authors: Felix U. Asoiro, Meshack I. Simeon, Chinenye E. Azuka, Harami Solomon, Chukwuemeka J. Ohagwu

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The drying kinetics, specific energy consumed (SEC), effective moisture diffusivity (EMD), flavonoid, phenolic, and vitamin C contents of onion slices dried under convective oven drying (COD) were compared with microwave drying (MD). Drying was performed with onion slice thicknesses of 2, 4, 6, and 8 mm; air drying temperatures of 60, 80, and 100°C for COD, and microwave power of 450 W for MD. A decrease in slice thickness and an increase in drying air temperature led to a drop in the drying time. As thickness increased from 2 – 8 mm, EMD rose from 1.1-4.35 x 10⁻⁸ at 60°C, 1.1-5.6 x 10⁻⁸ at 80°C, and 1.25-6.12 x 10⁻⁸ at 100°C with MD treatments yielding the highest mean value (6.65 x 10⁻⁸ m² s⁻¹) at 8 mm. Maximum SEC for onion slices in COD was 238.27 kWh/kg H₂O (2 mm thickness), and the minimum was 39.4 kWh/kg H₂O (8 mm thickness) whereas maximum during MD was 25.33 kWh/kg H₂O (8 mm thickness) and minimum, 18.7 kWh/kg H₂O (2 mm thickness). MD treatment gave a significant (p 0.05) increase in the flavonoid (39.42 – 64.4%), phenolic (38.0 – 46.84%), and vitamin C (3.7 – 4.23 mg 100 g⁻¹) contents, while COD treatment at 60°C and 100°C had positive effects on only vitamin C and phenolic contents, respectively. In comparison, the Weibull model gave the overall best fit (highest R²=0.999; lowest SSE=0.0002, RSME=0.0123, and χ²= 0.0004) when drying 2 mm onion slices at 100°C.

Keywords: allium cepa, drying kinetics, specific energy consumption, flavonoid, vitamin C, microwave oven drying

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Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

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Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

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Authors: Tianchen Dai

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Shantytowns are special historical products in china, possessing strong particularity and typicality, the theoretical value and the practical significance of which are deemed to hold great importance in the modern development of residential areas in China. The renovation planning of shantytowns can be very challenging in terms of cultural inheritance. The traditional lifestyle, one of the key elements building up residents’ perception of affiliation, should be carried forward in the renovation planning of shantytowns. Mobile vending can be considered as a rare business model survived within modern commercial environment, thanks to the unique spatial characteristics of Chinese shantytowns. This article mainly investigates the unique phenomenon of mobile vending in shantytowns, discussing the operating mechanism and rationality behind this commercial phenomenon. For humanistic concern, the innovative conservation of mobile vending, as a means to preserve the vivacious traditional lifestyle of local residents, can be realized through substantial urban design strategies, including spatial design of public space, height control of the facades, and traffic management around and inside shantytowns.

Keywords: cultural inheritance, mobile vending, renovation planning, shantytowns

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Authors: Mi Ok Kang

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This study explores the factors that motivate urban high school students from racially/ethnically diverse backgrounds to choose teaching as a future career. It draws on in-depth interviews with high school students of color living in an urban downtown located in an intermountain area in the U.S. Using the factors influencing teaching choice (FIT-Choice) model, this study examines the motivations, mobility experiences, and aspirations of participating high school students who self-identified as Latino/a, Tongan, and Chinese. The study identifies influential factors -both challenges and strengthening effects- that high school students of color experience in their career decision making. The study concludes that self-perceptions of teaching abilities, parental support, social connections, job security, and prior work with children during the internship in K-12 classroom motivated them to be a teacher. Limitations such as financial struggles of parents, the low social status of teaching career, and the low salary and benefit packages in the U.S. are among the factors that cause students to waver in or doubt their career choice.

Keywords: career development, diversifying teaching force, FIT-Choice, high school students of color

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Authors: Yuri V. Kim

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This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.

Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing

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Authors: Vahid Saatchian, Seyyed Farideh Hadavi

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The main aim of this study was developing the collaboration model of physical education and sport sciences faculties with service section of sport industrial.The research methods of this study was a qualitative. So researcher with of identifying the priority list of collaboration between colleges and service section of sport industry and according to sampling based of subjective and snowball approach, conducted deep interviews with 22 elites that study around the field of research topic. indeed interviews were analyzed through qualitative coding (open, axial and selective) with 5 category such as causal condition, basic condition, intervening conditions, action/ interaction and strategy. Findings exposed that in causal condition 10 labels appeared. So because of heterogeneity of labes, researcher categorized in total subject. In basic condition 59 labels in open coding identified this categorized in 14 general concepts. Furthermore with composition of the declared category and relationship between them, 5 final and internal categories (culture, intelligence, marketing, environment and ultra-powers) were appeared. Also an intervening condition in the study includes 5 overall scopes of social factors, economic, cultural factors, and the management of the legal and political factors that totally named macro environment. Indeed for identifying strategies, 8 areas that covered with internal and external challenges relationship management were appeared. These are including, understanding, outside awareness, manpower, culture, integrated management, the rules and regulations and marketing. Findings exposed 8 labels in open coding which covered the internal and external of challenges of relation management of two sides and these concepts were knowledge and awareness, external view, human source, madding organizational culture, parties’ thoughts, unit responsible for/integrated management, laws and regulations and marketing. Eventually the consequences categorized in line of strategies and were at scope of the cultural development, general development, educational development, scientific development, under development, international development, social development, economic development, technology development and political development that consistent with strategies. The research findings could help the sport managers witch use to scientific collaboration management and the consequences of this in those sport institutions. Finally, the consequences that identified as a result of the devopmental strategies include: cultural, governmental, educational, scientific, infrastructure, international, social, economic, technological and political that is largely consistent with strategies. With regard to the above results, enduring and systematic relation with long term cooperation between the two sides requires strategic planning were based on cooperation of all stakeholders. Through this, in the turbulent constantly changing current sustainable environment, competitive advantage for university and industry obtained. No doubt that lack of vision and strategic thinking for cooperation in the planning of the university and industry from its capability and instead of using the opportunity, lead the opportunities to problems.

Keywords: university and industry collaboration, sport industry, physical education and sport science college, service section of sport industry

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Authors: Igwenagu Chinelo Mercy

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This study is on the concept of Neurostatistics in relation to neuroscience. Neuroscience also known as neurobiology is the scientific study of the nervous system. In the study of neuroscience, it has been noted that brain function and its relations to the process of acquiring knowledge and behaviour can be better explained by the use of various interrelated methods. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales. On the other hand, Neurostatistics based on this study is viewed as a statistical concept that uses similar techniques of neuron mechanisms to solve some problems especially in the field of life science. This study is imperative in this era of Artificial intelligence/Machine leaning in the sense that clear understanding of the technique and its proper application could assist in solving some medical disorder that are mainly associated with the nervous system. This will also help in layman’s understanding of the technique of the nervous system in order to overcome some of the health challenges associated with it. For this concept to be well understood, an illustrative example using a brain associated disorder was used for demonstration. Structural equation modelling was adopted in the analysis. The results clearly show the link between the techniques of statistical model and nervous system. Hence, based on this study, the appropriateness of Neurostatistics application in relation to neuroscience could be based on the understanding of the behavioural pattern of both concepts.

Keywords: brain, neurons, neuroscience, neurostatistics, structural equation modeling

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Abderafi Charki, David Bigaud

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The aim of this oral speach is to present the PVMODREL© (PhotoVoltaic MODule RELiability) new software developed in the University of Angers. This new tool permits us to evaluate the lifetime and reliability of a PV module whatever its geographical location and environmental conditions. The electrical power output of a PV module decreases with time mainly as a result of the effects of corrosion, encapsulation discoloration, and solder bond failure. The failure of a PV module is defined as the point where the electrical power degradation reaches a given threshold value. Accelerated life tests (ALTs) are commonly used to assess the reliability of a PV module. However, ALTs provide limited data on the failure of a module and these tests are expensive to carry out. One possible solution is to conduct accelerated degradation tests. The Wiener process in conjunction with the accelerated failure time model makes it possible to carry out numerous simulations and thus to determine the failure time distribution based on the aforementioned threshold value. By this means, the failure time distribution and the lifetime (mean and uncertainty) can be evaluated. An example using the damp heat test is shown to demonstrate the usefulness PVMODREL.

Keywords: lifetime, reliability, PV Module, accelerated life testing, accelerated degradation testing

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Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

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Authors: S. Rashidi, L. C. Abdullah, R. Walvekar, K. Mohammad, F-R. Ahmadun, M. Y. Faizah

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In this research, stability and rheology behavior of Multi-walled carbon nanotube (MWCNT) nanofluids by using Xanthan Gum as a dispersant were measured. This paper addresses the effects of Xanthan Gum (XG) concentration and nanoparticle loading on stability and viscosity of nanofluids. The stability of nanofluids is measured by Zeta Sizer Nano-ZS (Malvern Instruments, ZEN 3600). The zeta potential of the stable samples was analyzed. The rheological behavior of carbon nanotube CNT nanofluids was analyzed using rheometer (Model AR G2, TA Instrument). Both stability and viscosity of the nanofluids increased with increasing CNT and XG concentration. The experimental results indicated that the zeta potential of nanofluid samples is stable. The results demonstrated that the zeta potential was affected by the CNT concentration and is augmented in parallel with increasing CNT concentration. The rheology results showed that the viscosity of CNT/XG nanofluid was increased. The escalated viscosity of CNT/XG nanofluid is owing to the higher van der Waals interaction between the CNT nanoparticles. On the other hand, the viscosity of the CNT/XG nanofluid decreases with increasing temperature. In summary, this research provides useful insight into the behavior of CNT nanofluids.

Keywords: nanofluid, carbon nanotube, stability, rheology

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Authors: Panagiotis Kosmas

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The advent of new technologies in education inspires practitioners to approach teaching from a different angle with the aim to professionally develop and improve teaching practices. Online communities of practice among teachers seem to be a trend associated with the integration efforts for a modern and pioneering educational system and training program. This study attempted to explore the participation in online communities of practice and the sharing of knowledge between teachers with aims to explore teachers' incentives to participate in such a community of practice. The study aims to contribute to international research, bringing in global debate new concerns and issues related to the professional learning of current educators. One official online community was used as a case study for the purposes of research. The data collection was conducted from the content analysis of online portal, by questionnaire in 184 community members and interviews with ten active users of the portal. The findings revealed that sharing of knowledge is a key motivation of members of a community. Also, the active learning and community participation seem to be essential factors for the success of an online community of practice.

Keywords: communities of practice, teachers, sharing knowledge, professional development

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Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid

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Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.

Keywords: energy transition, energy modeling, uncertainty, sustainability

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Authors: Babar Khan, Wang Zhijie

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Machine Vision has been playing a significant role in Industrial Automation, to imitate the wide variety of human functions, providing improved safety, reduced labour cost, the elimination of human error and/or subjective judgments, and the creation of timely statistical product data. Despite the intensive research, there have not been any attempts to classify fabric prints based on printed texture and colour, most of the researches so far encompasses only black and white or grey scale images. We proposed a biologically inspired processing architecture to classify fabrics w.r.t. the fabric print texture and colour. We created a texture descriptor based on the HMAX model for machine vision, and incorporated colour descriptor based on opponent colour channels simulating the single opponent and double opponent neuronal function of the brain. We found that our algorithm not only outperformed the original HMAX algorithm on classification of fabric print texture and colour, but we also achieved a recognition accuracy of 85-100% on different colour and different texture fabric.

Keywords: automatic classification, texture descriptor, colour descriptor, opponent colour channel

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Authors: Mohiuddin Sakib, Fatin Nihal, Anisul Haque, Munsur Rahman, Mansur Ali

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Sundarban, the largest mangrove forest in the world, is known to act as a buffer against the cyclone and storm surge. Theoretically, Sundarban absorbs the initial thrust of the wind and acts to ‘resist’ the storm surge flooding. The role of Sundarban was evident during the cyclone Sidr when the Sundarban solely defended the initial thrust of the cyclonic wind and the resulting storm surge inundation. In doing this, Sundarban sacrificed 30% of its plant habitats. Although no scientific study has yet been conducted, it is generally believed that Sundarban will continuously play its role as a buffer against the cyclone when landfall of the cyclone is at or close to the Sundarban. Considering these facts, the present study mainly focused on a scientific insight into the role of Sundarban as a buffer against the present-day cyclone and storm surge and also its probable role on the impacts of future storms of similar nature but with different landfall locations. The Delft 3D dashboard and flow model are applied to compute the resulting inundation due to cyclone induced storm surge. The results show that Sundarban indeed acts as a buffer against the storm surge inundation when cyclone landfall is at or close to Sundarban.

Keywords: buffer, Mangrove forest, Sidr, landfall, roughness

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Authors: M. Afshin, A. Sohankar, M. Dehghan Manshadi, M. R. Daneshgar, G. R. Dehghan Kamaragi

Abstract:

In this paper, the influence of an upstream structure on the flow pattern within and around the wind-catcher is experimentally investigated by smoke flow visualization techniques. Wind-catchers are an important part of natural ventilation in residential buildings or public places such as shopping centers, libraries, etc. Wind-catchers might be also used in places of high urban densities; hence their potential to provide natural ventilation in this case is dependent on the presence of upstream objects. In this study, the two-sided wind-catcher model was based on a real wind-catcher observed in the city of Yazd, Iran. The present study focuses on the flow patterns inside and outside the isolated two-sided wind-catcher, and on a two-sided wind-catcher in the presence of an upstream structure. The results show that the presence of an upstream structure influences the airflow pattern force and direction. Placing a high upstream object reverses the airflow direction inside the wind-catcher.

Keywords: natural ventilation, smoke flow visualization, two-sided wind-catcher, flow patterns

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Authors: Jiin-Yuh Jang, Yu-Feng Gan

Abstract:

In order to improve the comprehensive mechanical properties of the steel, the cooling rate, and the temperature distribution must be controlled in the cooling process. A three-dimensional numerical model for the prediction of the heat transfer coefficient distribution of H-beam in the controlled cooling process was performed in order to obtain the uniform temperature distribution and minimize the maximum stress and the maximum deformation after the controlled cooling. An algorithm developed with a simplified conjugated-gradient method was used as an optimizer to optimize the heat transfer coefficient distribution. The numerical results showed that, for the case of air cooling 5 seconds followed by water cooling 6 seconds with uniform the heat transfer coefficient, the cooling rate is 15.5 (℃/s), the maximum temperature difference is 85℃, the maximum the stress is 125 MPa, and the maximum deformation is 1.280 mm. After optimize the heat transfer coefficient distribution in control cooling process with the same cooling time, the cooling rate is increased to 20.5 (℃/s), the maximum temperature difference is decreased to 52℃, the maximum stress is decreased to 82MPa and the maximum deformation is decreased to 1.167mm.

Keywords: controlled cooling, H-Beam, optimization, thermal stress

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

Abstract:

Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

Procedia PDF Downloads 451