Search results for: home network
5868 Neural Network Based Path Loss Prediction for Global System for Mobile Communication in an Urban Environment
Authors: Danladi Ali
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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 signalKeywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment and model
Procedia PDF Downloads 3825867 Estimation of Chronic Kidney Disease Using Artificial Neural Network
Authors: Ilker Ali Ozkan
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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 4485866 Distributed Energy Storage as a Potential Solution to Electrical Network Variance
Authors: V. Rao, A. Bedford
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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 3185865 Integrative Analysis of Urban Transportation Network and Land Use Using GIS: A Case Study of Siddipet City
Authors: P. Priya Madhuri, J. Kamini, S. C. Jayanthi
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Assessment of land use and transportation networks is essential for sustainable urban growth, urban planning, efficient public transportation systems, and reducing traffic congestion. The study focuses on land use, population density, and their correlation with the road network for future development. The scope of the study covers inventory and assessment of the road network dataset (line) at the city, zonal, or ward level, which is extracted from very high-resolution satellite data (spatial resolution < 0.5 m) at 1:4000 map scale and ground truth verification. Road network assessment is carried out by computing various indices that measure road coverage and connectivity. In this study, an assessment of the road network is carried out for the study region at the municipal and ward levels. In order to identify gaps, road coverage and connectivity were associated with urban land use, built-up area, and population density in the study area. Ward-wise road connectivity and coverage maps have been prepared. To assess the relationship between road network metrics, correlation analysis is applied. The study's conclusions are extremely beneficial for effective road network planning and detecting gaps in the road network at the ward level in association with urban land use, existing built-up, and population.Keywords: road connectivity, road coverage, road network, urban land use, transportation analysis
Procedia PDF Downloads 355864 A Hybrid Hopfield Neural Network for Dynamic Flexible Job Shop Scheduling Problems
Authors: Aydin Teymourifar, Gurkan Ozturk
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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 4195863 Optimization and Retrofitting for an Egyptian Refinery Water Network
Authors: Mohamed Mousa
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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 2335862 A Self-Directed Home Yoga Program for Women with Breast Cancer during Chemotherapy
Authors: Hiroko Komatsu, Kaori Yagasaki
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Background: Cancer-related cognitive impairment is a common problem seen in cancer patients undergoing chemotherapy. Physical activity may show beneficial effects on the cognitive function in such patients. Therefore, we have developed a self-directed home yoga program for cancer patients with cognitive symptoms during chemotherapy. This program involves a DVD presenting a combination of yoga courses based on patient preferences to be practiced at home. This study was performed to examine the feasibility of this program. In addition, we also examined changes in cognitive function and quality of life (QOL) in these patients participating in the program. Methods: This prospective feasibility study was conducted in a 500-bed general hospital in Tokyo, Japan. The study population consisted of breast cancer patients undergoing chemotherapy as the initial therapy. This feasibility study used a convenience sample with estimation of recruitment rate in a single facility with the availability of trained nurses and physicians to ensure safe yoga intervention. The aim of the intervention program was to improve cognitive function by means of both physical and mental activation via yoga, consisting of physical practice, breathing exercises, and meditation. Information on the yoga program was provided as a booklet, with an instructor-guided group yoga class during the orientation, and a self-directed home yoga program on DVD with yoga logs. Results: The recruitment rate was 44.7%, and the study population consisted of 18 women with a mean age of 43.9 years. This study showed high rates of retention, adherence, and acceptability of the yoga program. Improvements were only observed in the cognitive aspects of fatigue, and there were serious adverse events during the program. Conclusion: The self-directed home yoga program discussed here was both feasible and safe for breast cancer patients showing cognitive symptoms during chemotherapy. The patients also rated the program as useful, interesting, and satisfactory. Participation in the program was associated with improvements in cognitive fatigue but not cognitive function.Keywords: yoga, cognition, breast cancer, chemotherapy, quality of life
Procedia PDF Downloads 2575861 Sensor Network Routing Optimization by Simulating Eurygaster Life in Wheat Farms
Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi
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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 4315860 Identification System for Grading Banana in Food Processing Industry
Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan
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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 4715859 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network
Authors: Li Qingjian, Li Ke, He Chun, Huang Yong
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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 3415858 Prediction Fluid Properties of Iranian Oil Field with Using of Radial Based Neural Network
Authors: Abdolreza Memari
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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 5025857 At Home in This World: Nanyang Painter Georgette Chen
Authors: Christine C. Neal
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A veritable world citizen, Nanyang painter Georgette Chen (1906-1993) melded artistic influences from both the East and West. Much has been written about her contribution to the art of Singapore, her role in the establishment of the Nanyang Style, the lasting influence that she exerted on younger artists, and her considerable artistic achievements. Never before examined is the development of her oeuvre that reflects this mixture, to the best of the author’s knowledge. The works selected for this investigation reveal her artistic development from student to teacher, the range of her thematic interests, and the stimuli that she absorbed from a life ensconced in eastern and western cultures where she felt, as she wrote, “at home in this world.”Keywords: art, China, Georgette Chen, Nanyang, Paris, Singapore
Procedia PDF Downloads 2855856 Effectiveness of Parent Coaching Intervention for Parents of Children with Developmental Disabilities in the Home and Community
Authors: Elnaz Alimi, Keriakoula Andriopoulos, Sam Boyer, Weronika Zuczek
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Occupational therapists can use coaching strategies to guide parents in providing therapy for their children with developmental disabilities. Evidence from various fields has shown increased parental self-efficacy and positive child outcomes as benefits of home and community-based parent coaching models. A literature review was conducted to investigate the effectiveness of parent coaching interventions delivered in home and community settings for children with developmental disabilities ages 0-12, on a variety of parent and child outcomes. CINAHL Plus, PsycINFO, PubMed, OTseeker were used as databases. The inclusion criteria consisted of: children with developmental disabilities ages 0-12 and their parents, parent coaching models conducted in the home and community, and parent and child outcomes. Studies were excluded if they were in a language other than English and published before 2000. Results showed that parent coaching interventions led to more positive therapy outcomes in child behaviors and symptoms related to their diagnosis or disorder. Additionally, coaching strategies had positive effects on parental satisfaction with therapy, parental self-efficacy, and family dynamics. Findings revealed decreased parental stress and improved parent-child relationships. Further research on parent coaching could involve studying the feasibility of coaching within occupational therapy specifically, incorporating cultural elements into coaching, qualitative studies on parental satisfaction with coaching, and measuring the quality of life outcomes for the whole family.Keywords: coaching model, developmental disabilities, occupational therapy, pediatrics
Procedia PDF Downloads 1945855 Advancements in Smart Home Systems: A Comprehensive Exploration in Electronic Engineering
Authors: Chukwuka E. V., Rowling J. K., Rushdie Salman
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The field of electronic engineering encompasses the study and application of electrical systems, circuits, and devices. Engineers in this discipline design, analyze and optimize electronic components to develop innovative solutions for various industries. This abstract provides a brief overview of the diverse areas within electronic engineering, including analog and digital electronics, signal processing, communication systems, and embedded systems. It highlights the importance of staying abreast of advancements in technology and fostering interdisciplinary collaboration to address contemporary challenges in this rapidly evolving field.Keywords: smart home engineering, energy efficiency, user-centric design, security frameworks
Procedia PDF Downloads 885854 Geographical Location and the Global Airline Industry: A Delphi Study into the Future of Home Base Requirements
Authors: Darren J. Ellis
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This paper investigates the key industry-level consequences and future prospects for the global airline industry of the requirement for airlines to have a home base. This industry context results in geographical location playing a central role in determining how and where international airlines can operate, and the extent to which their international networks can develop. Data from a five stage mixed-methods Delphi study into the global airline industry’s likely future trajectory conducted in 2013 and 2014 are utilized to better understand the likelihood and consequences of home base requirements changing in future. Expert views and forecasts were collected to gauge core industry trends over a ten year timeframe. Attempts to change or bypass this industry requirement have not been successful to date outside of the European single air market. Europe remains the only prominent exception to the general rule in this regard. Most of the industry is founded on air space sovereignty, the nationality rule, and the bilateral system of traffic rights. Europe’s exceptionalism has seen it evolve into a single air market with characteristics similar to a nation-state, rather than to become a force for wider industry change and regional multilateralism. Europe has indeed become a key actor in global aviation, but Europe seems to now be part of the industry’s status quo, not a vehicle for substantially wider multilateralism around the world. The findings from this research indicate that the bilateral system is not viewed by most study experts as disappearing or substantially weakening in the foreseeable future. However, regional multilateralism was also viewed as progressively taking hold in the industry in future, demonstrating that for most industry experts the two are not seen as mutually exclusive but rather as being able to co-exist with each other. This reality ensures that geographical location will continue to play an important role in the global airline industry in future and that, home base requirements will not disappear any time soon either. Even moves in some aviation jurisdictions to dilute nationality requirements for airlines, and instead replace ownership and control restrictions with principal place of business tests, do not ultimately free airlines from their home base. Likewise, an expansion of what constitutes home base to include a regional grouping of countries – again, a currently uncommon reality in global aviation – does not fundamentally weaken the continued relevance of geographical location to the global industry’s future growth and development realities and prospects.Keywords: airline industry, air space sovereignty, geographical location, home base
Procedia PDF Downloads 1375853 Performance Analysis of Next Generation OCDM-RoF-Based Hybrid Network under Diverse Conditions
Authors: Anurag Sharma, Rahul Malhotra, Love Kumar, Harjit Pal Singh
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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 6385852 Broadcast Routing in Vehicular Ad hoc Networks (VANETs)
Authors: Muazzam A. Khan, Muhammad Wasim
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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 5355851 Greywater Water Reuse in South Africa
Authors: Onyeka Nkwonta, Christopher Iheukwumere
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It is a waste to irrigate with great quantities of drinking water when plants thrive on used water containing small bits of compost. Unlike a lot of ecological stopgap measures, greywater reuse is a part of the fundamental solution to many ecological problems and will probably remain essentially unchanged in the distant future. Water is abused and wasted by both the wealthy and the poor. Education about water conservation is also needed. This study gives an outline of the sources of grey water in our home and provides a process of creating awareness on the importance of re-using grey water in our home, in order to achieve the 7th aim of the millennium development goals by 2015, which is ensuring environmental sustainability.Keywords: tickling filter, education, grey water, environmental sustainability
Procedia PDF Downloads 3735850 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model
Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li
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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 1495849 Community Re-Integrated Soldiers’ Perceptions of Barriers and Facilitators to A Home-Based Physical Rehabilitation Programme Following Lower-Limb Amputation
Authors: Ashan Wijekoon, Abi Beane, Subashini Jayawardana
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Background: Soldiers' physical rehabilitation and long term health status has been hindered due to limited investment in and access to rehabilitation services. Home-based rehabilitation programmes could offer a potentially feasible alternative to facilitate long-term recovery. Objectives: To explore Sri Lankan soldiers' perceptions of barriers and facilitators to a home-based physical rehabilitation programme.Methods and Materials: We conducted qualitative semi-structured interviews with community re-integrated army veterans who had undergone unilateral lower limb amputation following war related trauma. Veterans were identified from five districts of Sri Lanka, based on a priori knowledge of veteran community settlements (Disabled Category Registry) obtained from Directorate of Rehabilitation, MoD, Sri Lanka. Individuals were stratified for purposive selection. The interview guide was developed from existing methods and adapted for context. Verbatim transcripts of interviews were analyzed for emerging themes using an inductive approach. Following consent, participants met the researcher (AW- a trained physiotherapist fluent in Sinhalese). Results: Twenty-five Interviews were conducted, totaling 7.2 hours of new data (Mean±SD: 0.28±0.11). All participants were male, aged 30-55 years (Mean±SD: 46.1±7.4), and had experienced traumatic amputation as a result of conflict. Twenty-four sub themes were identified. Inadequate space for exercises, absence of equipment and assistance to conduct the exercises at home, alongside absence of community healthcare services were all barriers. Burden of comorbidities, including chronic pain and disability level, were also barriers. Social support systems, including soldier societies, family, and kinship with other amputees, were seen as facilitators to an at-home programme. Motivation for independence was a strong indicator of engagement. Conclusion: Environment, chronic pain, and absence of well-established community health services were key barriers. Family and soldier support was a facilitator. Engagement with community healthcare providers (physiotherapist and primary care physicians) will be essential to the success of an at-home rehabilitation program.Keywords: physical rehabilitation, home-based, soldiers, disability, lower-limb amputation, qualitative
Procedia PDF Downloads 1705848 Research on Reservoir Lithology Prediction Based on Residual Neural Network and Squeeze-and- Excitation Neural Network
Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing
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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 1785847 Implementation of a Culturally Responsive Home Visiting Framework in Head Start Teacher Professional Development
Authors: Meilan Jin, Mary Jane Moran
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This study aims to introduce the framework of culturally responsive home visiting (CRHV) to head start teacher professional sessions in the Southeastern of the US and investigate its influence on the evolving beliefs of teachers about their roles and relationships with families in-home visits. The framework orients teachers to an effective way of taking on the role of learner to listen for spoken and unspoken needs and look for family strengths. In addition, it challenges the deficit model that is grounded on 'cultural deprivation,' and it stresses the value of family cultures and advocates equal, collaborative parent-teacher relationships. The home visit reflection papers and focus group transcriptions of eight teachers have been collected since 2010 throughout a five-year longitudinal collaboration with them. Reflection papers were written by the teachers before and after introducing the CRHV framework, including the details of visit purposes and actions and their plans for later home visits. Particularly, the CRHV framework guided the teachers to listen and look for information about family-living environments; parent-child interactions; child-rearing practices; and parental beliefs, values, and needs. Two focus groups were organized in 2014 by asking the teachers to read their written reflection papers and then discussing their shared beliefs and experiences of home visits in recent years. The average length of the discussions was one hour, and the discussions were audio-recorded and transcribed verbatim. Moreover, the data were analyzed using constant comparative analysis, and the analysis was verified through (a) the uses of multiple data sources, (b) the involvement of multiple researchers, (c) coding checks, and (d) the provisions of the thick descriptions of the findings. The study findings corroborate that the teachers become to reposition themselves as 'knowledge seekers' through reorienting their cynosure toward 'setting stones' to learn, grow, and change rather than framing their home visits. The teachers also continually engage in careful listening, observing, questioning, and dialoguing, and these actions reflect their care toward parents. The value of teamwork with parents is advocated, and the teachers recognize that when parents feel empowered, they are active and committed to doing more for their children, which can further advantage proactive long-term parent-teacher collaborations. The study findings also validate that the framework is influential for educators to provide the experiences of home visiting that is culturally responsive and to share collaborative relationships with caregivers. The long-term impact of the framework further implies that teachers continue to put themselves in the position of evolving, including beliefs and actions, to better work with children and families who are culturally, ethnically, and linguistically different from them. This framework can be applicable to educators and professionals who are looking for avenues to bridge the relationship between home and school and parents and teachers.Keywords: culturally responsive home visit, early childhood education, parent–teacher collaboration, teacher professional development
Procedia PDF Downloads 975846 Prediction of the Transmittance of Various Bended Angles Lightpipe by Using Neural Network under Different Sky Clearness Condition
Authors: Li Zhang, Yuehong Su
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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 1535845 Trusted Neural Network: Reversibility in Neural Networks for Network Integrity Verification
Authors: Malgorzata Schwab, Ashis Kumer Biswas
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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 1495844 Nonlinear Adaptive PID Control for a Semi-Batch Reactor Based on an RBF Network
Authors: Magdi. M. Nabi, Ding-Li Yu
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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 7045843 Home Garden: A Food-Based Strategy to Achieve Sustainable Impact on Household Nutrition of Resource-Poor Families in Nepal
Authors: Purushottam P. Khatiwada, Bikash Paudel, Ram B. Rana, Parshuram Biswakarma, Roshan Pudasaini
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Nepal has been putting its efforts into securing food and nutrition security for its citizens adopting different models and approaches. Home Garden approach, that integrates vegetables, fruits, small livestock, poultry along with other components like fish, honeybee, mushroom, spices for the promotion of nutritional security of resource-poor and disadvantaged groups was implemented during March 2009 to July 2013 spreading over 16 districts of Nepal covering 115 farmers groups, directly working with 3500 households. Sustained long-term impact of development interventions targeted to the resource-poor and disadvantaged groups has been a recurrent issue for donors, policymakers and practitioners alike. Considering the issue, a post-project evaluation was carried out in a selected project group (Dangibari of Jhapa) after four years of project completion in 2017 in order to evaluate the impact and understand the factors associated with its success. Qualitative information was collected through focus group discussion with group members and associated local institutions. For quantitative information, a quick survey was carried out to the same group members only selecting few indicators. The results are compared with the data obtained from the baseline study conducted by the project in March 2009. The impact of project intervention was evident as compared to the benchmarks established during the baseline, even after four years of project completion. The area under home garden is increased to 729 m² from 386 m² and average food self-sufficiency months increased to 10.22 from 8.11. Seven to eleven fruit species are maintained in the home gardens. An average number of vegetable species grown increased to 15.85 from 9.86. It has resulted in an increase in vegetables self-sufficient month to 8.74 from 4.74 and a huge increase in cash income NPR 6142.8 (USD 59.6) from NPR 385.7 (USD 3.9) from the sale of surplus vegetables. Coaching and mentoring including nutrition sensitization by the project staff at the beginning, inputs and technical support during the project implementation phase and projects effort on the institutional building of disadvantaged farmers were the key drivers of home garden sustainability and expansion. Specifically, package of home garden management trainings provided by the project staff, availability of group funds for buying inputs even after the project, uniting home garden group members in a cooperative, resource leveraging by local institutions through group lobbying, farmers innovations for maintaining home garden diversity and continuous backstopping support by few active members as local resource persons to other members are some additional factors contributing to sustain and/or improve the home garden status by the resource-poor and disadvantaged group.Keywords: food-based nutrition, home garden, resource-poor and disadvantaged group, sustained impact
Procedia PDF Downloads 1465842 Tourism Potential Investment Opportunities in Pakistan: A Critical Analysis
Authors: Khalil Ahmad Khosa
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Pakistan is such a diverse region, it is the center of various religions and settlements long before the creation of the nation that exists today. The country's attraction range from the ruin of the Indus Valley Civilization such as Mohenjo-daro, Harappa and Taxila, to the Himalayan hill stations, which attract those interested in winter sports. Pakistan is home to several mountain peaks over 7000 m, which attracts adventurers and mountaineers from around the world, especially K2.[4] The north part of Pakistan has many old fortresses, ancient architecture and the Hunza and Chitral valley, home to small pre-Islamic Animist Kalash people community. The romance of the historic Khyber Pakhtunkhwa province is timeless and legendary, Punjab province has the site of Alexander's battle on the Jhelum River and the historic city Lahore, Pakistan's cultural capital, with many examples of Mughal architecture such as Badshahi Masjid, Shalimar Gardens, Tomb of Jahangir and the Lahore Fort. Tourism is a growing industry in Pakistan. However, till this date, the government has not be able to take the tourism market seriously within Pakistan. Pakistan is home to a diverse number of tourist attractions which have not been funded or protected due to the government giving the tourism market a low priority.Keywords: architecture, Pakistan, tourism, turist
Procedia PDF Downloads 2795841 Home Range and Spatial Interaction Modelling of Black Bears
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
Procedia PDF Downloads 825840 Construction Project Planning Using Fuzzy Critical Path Approach
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 1445839 Parallel Hybrid Honeypot and IDS Architecture to Detect Network Attacks
Authors: Hafiz Gulfam Ahmad, Chuangdong Li, Zeeshan Ahmad
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In this paper, we proposed a parallel IDS and honeypot based approach to detect and analyze the unknown and known attack taxonomy for improving the IDS performance and protecting the network from intruders. The main theme of our approach is to record and analyze the intruder activities by using both the low and high interaction honeypots. Our architecture aims to achieve the required goals by combing signature based IDS, honeypots and generate the new signatures. The paper describes the basic component, design and implementation of this approach and also demonstrates the effectiveness of this approach reducing the probability of network attacks.Keywords: network security, intrusion detection, honeypot, snort, nmap
Procedia PDF Downloads 569