Search results for: collaborative network

Authors: Ali A. Hammadi

Abstract:

In this work, a practical study on a commissioned Giga Passive Optical Network (GPON) fiber to the home access network in Kuwait is presented. The work covers the framework of the conceptual design of the deployed Passive Optical Networks (PONs), access network, optical fiber cable network distribution, technologies, and standards. The work also describes methodologies applied by system engineers for design of Optical Network Terminals (ONTs) and Optical Line Terminals (OLTs) transceivers with respect to the distance, operating wavelengths, splitting ratios. The results have demonstrated and justified the limitation of transmission distance of a PON link in Fiber to The Premises (FTTP) to not exceed 20 km. Optical Time Domain Reflector (OTDR) test has been carried for this project to confirm compliance with International Telecommunication Union (ITU) specifications regarding the total length of the deployed optical cable, total loss in dB, and loss per km in dB/km with respect to the operating wavelengths. OTDR test results with traces for segments of implemented fiber network will be provided and discussed.

Keywords: passive optical networks (PONs), fiber to the premises (FTTx), access network, OTDR

Procedia PDF Downloads 254

Authors: Soban Najam, S. M. Jahanzeb, Ahmed Sohail, Faraz Idris Khan

Abstract:

With the recent increase in reliance on Gas as the primary source of energy across the world, there has been a lot of research conducted on gas distribution networks. As the complexity and size of these networks grow, so does the leakage of gas in the distribution network. One of the most crucial factors in the production and distribution of gas is UFG or Unaccounted for Gas. The presence of UFG signifies that there is a difference between the amount of gas distributed, and the amount of gas billed. Our approach is to use information that we acquire from several specified points in the network. This information will be used to calculate the loss occurring in the network using the developed algorithm. The Algorithm can also identify the leakages at any point of the pipeline so we can easily detect faults and rectify them within minimal time, minimal efforts and minimal resources.

Keywords: FLA, fault location analysis, GDN, gas distribution network, GIS, geographic information system, NMS, network Management system, OMS, outage management system, SSGC, Sui Southern gas company, UFG, unaccounted for gas

Procedia PDF Downloads 599

Authors: Ramy Shaaban

Abstract:

The purpose of this study was to examine the difference in clinical reasoning skills of students when using virtual audiology cases with and without collaborative assistance from major learning approaches important to clinical reasoning skills and computer-based learning models: Situated Learning Theory, Social Development Theory, Scaffolding, and Collaborative Learning. A quasi-experimental design was conducted at two United States universities to examine whether there is a significant difference in clinical reasoning skills between three treatment groups using IUP Audiosim software. Two computer-based audiology case simulations were developed, and participants were randomly placed into the three groups: no collaboration, virtual collaboration, and live collaboration. The clinical reasoning data were analyzed using One-Way ANOVA and Tukey posthoc analyses. The results show that there was a significant difference in clinical reasoning skills between the three treatment groups. The score obtained by the no collaboration group was significantly less than the scores obtained by the virtual and live collaboration groups. Collaboration, whether virtual or in person, has a positive effect on students’ clinical reasoning. These results with audiology students indicate that combining collaboration models with scaffolding and embedding situated learning and social development theories into the design of future virtual patients has the potential to improve students’ clinical reasoning skills.

Keywords: clinical reasoning, virtual patients, collaborative learning, scaffolding

Procedia PDF Downloads 175

Authors: Jung-Ho Moon, Myung-Gon Yoon, Tae Kwon Ha

Abstract:

This paper presents a wireless sensor network protocol for a car parking monitoring system. A wireless sensor network for the purpose is composed of multiple sensor nodes, a sink node, a gateway, and a server. Each of the sensor nodes is equipped with a 3-axis AMR sensor and deployed in the center of a parking space. The sensor node reads its sensor values periodically and transmits the data to the sink node if the current and immediate past sensor values show a difference exceeding a threshold value. The operations of the sink and sensor nodes are described in detail along with flow diagrams. The protocol allows a low-duty cycle operation of the sensor nodes and a flexible adjustment of the threshold value used by the sensor nodes.

Keywords: car parking monitoring, sensor node, wireless sensor network, network protocol

Procedia PDF Downloads 497

Authors: Danladi Ali

Abstract:

In this paper, we measured GSM signal strength in the Dnepropetrovsk city in order to predict path loss in study area using nonlinear autoregressive neural network prediction and we also, used neural network clustering to determine average GSM signal strength receive at the study area. The nonlinear auto-regressive neural network predicted that the GSM signal is attenuated with the mean square error (MSE) of 2.6748dB, this attenuation value is used to modify the COST 231 Hata and the Okumura-Hata models. The neural network clustering revealed that -75dB to -95dB is received more frequently. This means that the signal strength received at the study is mostly weak signal

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment and model

Procedia PDF Downloads 353

Authors: Ilker Ali Ozkan

Abstract:

In this study, an artificial neural network model has been developed to estimate chronic kidney failure which is a common disease. The patients’ age, their blood and biochemical values, and 24 input data which consists of various chronic diseases are used for the estimation process. The input data have been subjected to preprocessing because they contain both missing values and nominal values. 147 patient data which was obtained from the preprocessing have been divided into as 70% training and 30% testing data. As a result of the study, artificial neural network model with 25 neurons in the hidden layer has been found as the model with the lowest error value. Chronic kidney failure disease has been able to be estimated accurately at the rate of 99.3% using this artificial neural network model. The developed artificial neural network has been found successful for the estimation of chronic kidney failure disease using clinical data.

Keywords: estimation, artificial neural network, chronic kidney failure disease, disease diagnosis

Procedia PDF Downloads 413

Authors: Jacky Hau

Abstract:

The prevalence of emerging technologies disrupts various industries as well as consumer behavior. Data collection has been in the fingertip and inherited through enabled Internet-of-things (IOT) devices. Big data analytics (BDA) becomes possible and allows real-time demand network management (DNM) through leagile supply chain. To enhance further on its resilience and predictability, governance is going to be examined to promote supply chain transparency and trust in an efficient manner. Leagility combines lean thinking and agile techniques in supply chain management. It aims at reducing costs and waste, as well as maintaining responsiveness to any volatile consumer demand by means of adjusting the decoupling point where the product flow changes from push to pull. Leagility would only be successful when collaborative planning, forecasting, and replenishment (CPFR) process or alike is in place throughout the supply chain business entities. Governance and procurement of the supply chain, however, is crucial and challenging for the execution of CPFR as every entity has to walk-the-talk generously for the sake of overall benefits of supply chain performance, not to mention the complexity of exercising the polices at both of within across various supply chain business entities on account of organizational behavior and mutual trust. Empirical survey results showed that the effective timespan on demand forecasting had been drastically shortening in the magnitude of months to weeks planning horizon, thus agility shall come first and preferably following by lean approach in a timely manner.

Keywords: governance, leagility, procure-to-pay, source-to-contract

Procedia PDF Downloads 87

Authors: V. Rao, A. Bedford

Abstract:

As the efficient performance of national grid becomes increasingly important to maintain the electrical network stability, the balance between the generation and the demand must be effectively maintained. To do this, any losses that occur in the power network must be reduced by compensating for it. In this paper, one of the main cause for the losses in the network is identified as the variance, which hinders the grid’s power carrying capacity. The reason for the variance in the grid is investigated and identified as the rise in the integration of renewable energy sources (RES) such as wind and solar power. The intermittent nature of these RES along with fluctuating demands gives rise to variance in the electrical network. The losses that occur during this process is estimated by analyzing the network’s power profiles. Whilst researchers have identified different ways to tackle this problem, little consideration is given to energy storage. This paper seeks to redress this by considering the role of energy storage systems as potential solutions to reduce variance in the network. The implementation of suitable energy storage systems based on different applications is presented in this paper as part of variance reduction method and thus contribute towards maintaining a stable and efficient grid operation.

Keywords: energy storage, electrical losses, national grid, renewable energy, variance

Procedia PDF Downloads 285

Authors: A. Bayle, F. Plouraboué

Abstract:

Water Distribution Network (WDN) still suffers from a lack of knowledge about fast pressure transient events prediction, although the latter may considerably impact their durability. Accidental or planned operating activities indeed give rise to complex pressure interactions and may drastically modified the local pressure value generating leaks and, in rare cases, pipe’s break. In this context, a numerical predictive analysis is conducted to prevent such event and optimize network management. A couple of Python/FORTRAN 90, home-made software, has been developed using Method Of Characteristic (MOC) solving for water-hammer equations. The solver is validated by direct comparison with theoretical and experimental measurement in simple configurations whilst afterward extended to network analysis. The algorithm's most costly steps are designed for parallel computation. A various set of boundary conditions and energetic losses models are considered for the network simulations. The results are analyzed in both real and frequencies domain and provide crucial information on the pressure distribution behavior within the network.

Keywords: energetic losses models, method of characteristic, numerical predictive analysis, water distribution network, water hammer

Procedia PDF Downloads 190

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a new hybrid Hopfield neural network is proposed for the dynamic, flexible job shop scheduling problem. A new heuristic based and easy to implement energy function is designed for the Hopfield neural network, which penalizes the constraints violation and decreases makespan. Moreover, for enhancing the performance, several heuristics are integrated to it that achieve active, and non-delay schedules also, prevent early convergence of the neural network. The suggested algorithm that is designed as a generalization of the previous studies for the flexible and dynamic scheduling problems can be used for solving real scheduling problems. Comparison of the presented hybrid method results with the previous studies results proves its efficiency.

Keywords: dynamic flexible job shop scheduling, neural network, heuristics, constrained optimization

Procedia PDF Downloads 390

Authors: Mohamed Mousa

Abstract:

Sacristies in the supply of freshwater, strict regulations on discharging wastewater and the support to encourage sustainable development by water minimization techniques leads to raise the interest of water reusing, regeneration, and recycling. Water is considered a vital element in chemical industries. In this study, an optimization model will be developed to determine the optimal design of refinery’s water network system via source interceptor sink that involves several network alternatives, then a Mixed-Integer Non-Linear programming (MINLP) was used to obtain the optimal network superstructure based on flowrates, the concentration of contaminants, etc. The main objective of the model is to reduce the fixed cost of piping installation interconnections, reducing the operating cots of all streams within the refiner’s water network, and minimize the concentration of pollutants to comply with the environmental regulations. A real case study for one of the Egyptian refineries was studied by GAMS / BARON global optimization platform, and the water network had been retrofitted and optimized, leading to saving around 195 m³/ hr. of freshwater with a total reduction reaches to 26 %.

Keywords: freshwater minimization, modelling, GAMS, BARON, water network design, wastewater reudction

Procedia PDF Downloads 197

Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

Abstract:

A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

Procedia PDF Downloads 393

Authors: Ulriikka Savela-Huovinen, Hanni Muukkonen, Auli Toom

Abstract:

The development of workplace as a learning environment has been emphasized in research field of workplace learning. The prior literature on sensory performance emphasized the individual’s competences as assessor, while the competences in the collaborative interactional and knowledge creation practices as workplace learning method are not often mentioned. In the present study aims to find out what kinds of competences and contexts are central when assessor conducts food sensory evaluation in authentic professional context. The aim was to answer the following questions: first, what kinds of competences does sensory evaluation require according to assessors? And second, what kinds of contexts for sensory evaluation do assessors report? Altogether thirteen assessors from three Finnish food companies were interviewed by using semi-structural thematic interviews to map practices and development intentions as well as to explicate already established practices. The qualitative data were analyzed by following the principles of abductive and inductive content analysis. Analysis phases were combined and their results were considered together as a cross-analysis. When evaluated independently required competences were perception, knowledge of specific domains and methods and cognitive skills e.g. memory. Altogether, 42% of analysis units described individual evaluation contexts, 53% of analysis units described collaborative interactional contexts, and 5% of analysis units described collaborative knowledge creation contexts. Related to collaboration, analysis reviewed learning, sharing and reviewing both external and in-house consumer feedback, developing methods to moderate small-panel evaluation and developing product vocabulary collectively between the assessors. Knowledge creation contexts individualized from daily practices especially in cases product defects were sought and discussed. The study findings contribute to the explanation that sensory assessors learn extensively from one another in the collaborative interactional and knowledge creation context. Assessors learning and abilities to work collaboratively in the interactional and knowledge creation contexts need to be ensured in the development of the expertise.

Keywords: assessor, collaboration, competences, contexts, learning and practices, sensory evaluation

Procedia PDF Downloads 213

Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

Abstract:

In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

Procedia PDF Downloads 439

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

Procedia PDF Downloads 312

Authors: Abdolreza Memari

Abstract:

In this article in order to estimate the viscosity of crude oil,a numerical method has been used. We use this method to measure the crude oil's viscosity for 3 states: Saturated oil's viscosity, viscosity above the bubble point and viscosity under the saturation pressure. Then the crude oil's viscosity is estimated by using KHAN model and roller ball method. After that using these data that include efficient conditions in measuring viscosity, the estimated viscosity by the presented method, a radial based neural method, is taught. This network is a kind of two layered artificial neural network that its stimulation function of hidden layer is Gaussian function and teaching algorithms are used to teach them. After teaching radial based neural network, results of experimental method and artificial intelligence are compared all together. Teaching this network, we are able to estimate crude oil's viscosity without using KHAN model and experimental conditions and under any other condition with acceptable accuracy. Results show that radial neural network has high capability of estimating crude oil saving in time and cost is another advantage of this investigation.

Keywords: viscosity, Iranian crude oil, radial based, neural network, roller ball method, KHAN model

Procedia PDF Downloads 459

Authors: Sweta Das

Abstract:

This case report highlights the atypical clinical manifestation of ipsilateral head, neck, shoulder, and eye pain with erythema and edema of right eyelid and conjunctiva, along with typical presentation of right sided Horner’s syndrome in a 37-year-old female, who was correctly diagnosed with Wallenberg syndrome due to collaborative effort from optometry, primary care, emergency, and neurology specialties in medicine. Horner’s syndrome is present in 75% of patients with Wallenberg syndrome. Given that patients with Wallenberg syndrome often first present to the Emergency Department with a vast variety of non-specific symptoms, and a normal MRI, a delayed diagnosis is common. Therefore, a collaborative effort between emergency department, optometry, primary care, and neurology is essential in correctly diagnosing Wallenberg’s syndrome in a timely manner.

Keywords: horner's syndrome, stroke, wallenberg syndrome, lateropulsion of eyes

Procedia PDF Downloads 32

Authors: Bindu Shrestha, Sudarshan R. Tiwari, Sushil B. Bajracharya

Abstract:

Urban household cooking fuel choice is highly influenced by human behavior and energy culture parameters such as cognitive norms, material culture and practices. Although these parameters have a leading role in Kathmandu for cleaner households, they are not incorporated in the city’s energy policy. This paper aims to identify trade-offs to transform resident behavior in cooking pattern towards cleaner technology from the questionnaire survey, observation, mapping, interview, and quantitative analysis. The analysis recommends implementing a Collaborative Cultural Model (CCM) for changing impact on the neighborhood from the policy level. The results showed that each household produces 439.56 kg of carbon emission each year and 20 percent used unclean technology due to low-income level. Residents who used liquefied petroleum gas (LPG) as their cooking fuel suffered from an energy crisis every year that has created fuel hoarding, which ultimately creates more energy demand and carbon exposure. In conclusion, the carbon emission can be reduced by improving the residents’ energy consumption culture. It recommended the city to use holistic action of changing habits as soft power of collaboration in two-way participation approach within residents, private sectors, and government to change their energy culture and behavior in policy level.

Keywords: energy consumption pattern, collaborative cultural model, energy culture, fuel stacking

Procedia PDF Downloads 111

Authors: Anurag Sharma, Rahul Malhotra, Love Kumar, Harjit Pal Singh

Abstract:

This paper demonstrates OCDM-ROF based hybrid architecture where data/voice communication is enabled via a permutation of Optical Code Division Multiplexing (OCDM) and Radio-over-Fiber (RoF) techniques under various diverse conditions. OCDM-RoF hybrid network of 16 users with DPSK modulation format has been designed and performance of proposed network is analyzed for 100, 150, and 200 km fiber span length under the influence of linear and nonlinear effect. It has been reported that Polarization Mode Dispersion (PMD) has the least effect while other nonlinearity affects the performance of proposed network.

Keywords: OCDM, RoF, DPSK, PMD, eye diagram, BER, Q factor

Procedia PDF Downloads 606

Authors: Muazzam A. Khan, Muhammad Wasim

Abstract:

Vehicular adhoc network (VANET) Cars for network (VANET) allowing vehicles to talk to each other, which is committed to building a strong network of mobile vehicles is technical. In VANETs vehicles are equipped with special devices that can get and share info with the atmosphere and other vehicles in the network. Depending on this data security and safety of the vehicles can be enhanced. Broadcast routing is dispersion of any audio or visual medium of mass communication scattered audience distribute audio and video content, but usually using electromagnetic radiation (waves). The lack of server or fixed infrastructure media messages in VANETs plays an important role for every individual application. Broadcast Message VANETs still open research challenge and requires some effort to come to good solutions. This paper starts with a brief introduction of VANET, its applications, and the law of the message-trends in this network starts. This work provides an important and comprehensive study of reliable broadcast routing in VANET scenario.

Keywords: vehicular ad-hoc network , broadcasting, networking protocols, traffic pattern, low intensity conflict

Procedia PDF Downloads 492

Authors: Rowena R. De Guzman

Abstract:

Association of Southeast Asian Nations (ASEAN) integration requires that higher education institutions (HEIs) must adjust the quality of their educational services and develop a global mindset, through various quality assurance (QA) activities to a level producing global graduates and encouraging human resource mobility. For Philippine HEIs, QA involves enormous tasks and responsibilities, whereby the implementation of which involves various parties, agencies and stakeholders; and in that case innovations have to be installed to engage the whole system in the QA process. In this study, collaborative governance (CG), a concept from the field of public administration, is introduced in educational management, particularly in the area of QA management. The paper suggests that the exercise of and attitude toward CG in QA is relevant to the practice of activities across QA indicators in higher educational services among stakeholders from participating HEIs. Participants representing different interests are collectively empowered, and this compelled them to participate and support the QA activities of the HEIs. It is recommended to embed CG model in the system for HEIs undergoing or intending to undergo QA achieve their desired QA outcomes. The study supports the commitment of the Philippine government to the evolving policy and efforts to achieve comparable qualifications across the Asia-Pacific region under the auspices of the UNESCO.

Keywords: ASEAN integration, collaborative governance, global education, government policy, higher education, international demands, quality assurance

Procedia PDF Downloads 231

Authors: Fadoua Ouamani, Narjès Bellamine Ben Saoud, Henda Hajjami Ben Ghézala

Abstract:

In the last few years and over the last decades, there was a growing interest in the development of Computer Supported Collaborative Learning (CSCL) environments. However, the existing systems ignore the variety of learners and their socio-cultural differences, especially in the case of distant and networked learning. In fact, within such collaborative learning environments, learners from different socio-cultural backgrounds may interact together. These learners evolve within various cultures and social contexts and acquire different socio-cultural values and behaviors. Thus, they should be assisted while communicating and collaborating especially in an intercultural group. Besides, the communication and collaboration tools provided to each learner must depend on and be adapted to her/his socio-cultural profile. The main goal of this paper is to present the proposed socio-cultural adaptation approach based on and guided by ontologies to adapt CSCL environments to the socio-cultural profiles of its users (learners or others).

Keywords: CSCL, socio-cultural profile, adaptation, ontology

Procedia PDF Downloads 335

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

Procedia PDF Downloads 110

Authors: Lonna Mabandla, Godfrey Musvoto

Abstract:

Transportation is a catalytic feature in cities. Transport and land use activity are interdependent and have a feedback loop between how land is developed and how transportation systems are designed and used. This recursive relationship between land use and transportation is reflected in how public transportation routes internal to the inner-city enhance accessibility, therefore creating spaces that are conducive to business activity, while the business activity also informs public transportation routes. It is for this reason that the focus of this research is on public transportation within inner-city areas where the dynamic is evident. Durban is the chosen case study where the dominating form of public transportation within the central business district (CBD) is minibus taxis. The paradox here is that minibus taxis still form part of the informal economy even though they are the leading form of public transportation in South Africa. There have been many attempts to formalise this industry to follow more regulatory practices, but minibus taxis are privately owned, therefore complicating any proposed intervention. The argument of this study is that the application of collaborative planning through a sustainable partnership between the public and private sectors will improve the social and environmental sustainability of public transportation. One of the major challenges that exist within such collaborative endeavors is power dynamics. As a result, a key focus of the study is on power relations. Practically, power relations should be observed over an extended period, specifically when the different stakeholders engage with each other, to reflect valid data. However, a lengthy data collection process was not possible to observe during the data collection phase of this research. Instead, interviews were conducted focusing on existing procedural planning practices between the inner-city minibus taxi association (South and North Beach Taxi Association), the eThekwini Transport Authority (ETA), and the eThekwini Town Planning Department. Conclusions and recommendations were then generated based on these data.

Keywords: collaborative planning, sustainability, public transport, minibus taxis

Procedia PDF Downloads 30

Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

Abstract:

Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: convolutional neural network, lithology, prediction of reservoir, seismic attributes

Procedia PDF Downloads 145

Authors: Li Zhang, Yuehong Su

Abstract:

Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

Procedia PDF Downloads 123

Authors: Malgorzata Schwab, Ashis Kumer Biswas

Abstract:

In this concept paper, we explore the topic of Reversibility in Neural Networks leveraged for Network Integrity Verification and crafted the term ''Trusted Neural Network'' (TNN), paired with the API abstraction around it, to embrace the idea formally. This newly proposed high-level generalizable TNN model builds upon the Invertible Neural Network architecture, trained simultaneously in both forward and reverse directions. This allows for the original system inputs to be compared with the ones reconstructed from the outputs in the reversed flow to assess the integrity of the end-to-end inference flow. The outcome of that assessment is captured as an Integrity Score. Concrete implementation reflecting the needs of specific problem domains can be derived from this general approach and is demonstrated in the experiments. The model aspires to become a useful practice in drafting high-level systems architectures which incorporate AI capabilities.

Keywords: trusted, neural, invertible, API

Procedia PDF Downloads 114

Authors: Magdi. M. Nabi, Ding-Li Yu

Abstract:

Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

Procedia PDF Downloads 670

Authors: Norah Alosayl

Abstract:

English is considered the most important foreign language in the Kingdom of Saudi Arabia (KSA) because of the usefulness of English as a global language compared to Arabic. As students’ desire to improve their English language skills has grown, English writing has been identified as the most difficult problem for Saudi students in their language learning. Although the English language in Saudi Arabia is taught beginning in the seventh grade, many students have problems at the university level, especially in writing, due to a gap between what is taught in secondary and high schools and university expectations- pupils generally study English at school, based on one book with few exercises in vocabulary and grammar exercises, and there are no specific writing lessons. Moreover, from personal teaching experience at King Saud bin Abdulaziz University, students face real problems with their writing. This paper revolves around the blackboard-based collaborative writing to help the undergraduate Saudi EFL students, in their first year enrolled in two sections of ENGL 101 in the first semester of 2021 at King Saud bin Abdulaziz University, practice the most difficult skill they found in their writing through a small group. Therefore, a sequential mixed methods design will be suited. The first phase of the study aims to highlight the most difficult skill experienced by students from an official writing exam that is evaluated by their teachers through an official rubric used in King Saud bin Abdulaziz University. In the second phase, this study will intend to investigate the benefits of social interaction on the process of learning writing. Students will be provided with five collaborative writing tasks via discussion feature on Blackboard to practice a skill that they found difficult in writing. the tasks will be formed based on social constructivist theory and pedagogic frameworks. The interaction will take place between peers and their teachers. The frequencies of students’ participation and the quality of their interaction will be observed through manual counting, screenshotting. This will help the researcher understand how students actively work on the task through the amount of their participation and will also distinguish the type of interaction (on task, about task, or off-task). Semi-structured interviews will be conducted with students to understand their perceptions about the blackboard-based collaborative writing tasks, and questionnaires will be distributed to identify students’ attitudes with the tasks.

Keywords: writing difficulties, blackboard-based collaborative writing, process of learning writing, interaction, participations

Procedia PDF Downloads 164

Authors: Omar M. Aldenali

Abstract:

Planning is one of the most important phases of the management science and network planning, which represents the project activities relationship. Critical path is one of the project management techniques used to plan and control the execution of a project activities. The objective of this paper is to implement a fuzzy logic approach to arrange network planning on construction projects. This method is used to finding out critical path in the fuzzy construction project network. The trapezoidal fuzzy numbers are used to represent the activity construction project times. A numerical example that represents a house construction project is introduced. The critical path method is implemented on the fuzzy construction network activities, and the results showed that this method significantly affects the completion time of the construction projects.

Keywords: construction project, critical path, fuzzy network project, planning

Procedia PDF Downloads 109