Search results for: data interpolating empirical orthogonal function

Authors: Zi Wang, Xinlei He, Jianghua Lv, Yuqing Lan

Abstract:

Kernel though widely used, is complicated. Errors caused by some bugs are often costly. Statically, more than half of the mistakes occur in the design phase. Thus, we introduce a modeling method, KMVM (Linux Kernel Modeling and verification Method), based on type theory for proper designation and correct exploitation of the Kernel. In the model, the Kernel is separated into six levels: subsystem, dentry, file, struct, func, and base. Each level is treated as a type. The types are specified in the structure and relationship. At the same time, we use a demanding path to express the function to be implemented. The correctness of the design is verified by recursively checking the type relationship and type existence. The method has been applied to verify the OPEN business of VFS (virtual file system) in Linux Kernel. Also, we have designed and developed a set of security communication mechanisms in the Kernel with verification.

Keywords: formal approach, type theory, Linux Kernel, software program

Procedia PDF Downloads 116

Authors: Salam Alzubaidi, G. Fantoni, F. Failli, M. Frosolini

Abstract:

The dynamic facility layout problem is a really critical issue in the competitive industrial market; thus, solving this problem requires robust design and effective simulation systems. The sustainable simulation requires inputting reliable and accurate data into the system. So this paper describes an automated system integrated into the real environment to measure the duration of the material handling operations, collect the data in real-time, and determine the variances between the actual and estimated time schedule of the operations in order to update the simulation software and redesign the facility layout periodically. The automated method- time measurement system collects the real data through using Radio Frequency-Identification (RFID) and Internet of Things (IoT) technologies. Hence, attaching RFID- antenna reader and RFID tags enables the system to identify the location of the objects and gathering the time data. The real duration gathered will be manipulated by calculating the moving average duration of the material handling operations, choosing the shortest material handling path, and then updating the simulation software to redesign the facility layout accommodating with the shortest/real operation schedule. The periodic simulation in real-time is more sustainable and reliable than the simulation system relying on an analysis of historical data. The case study of this methodology is in cooperation with a workshop team for producing mechanical parts. Although there are some technical limitations, this methodology is promising, and it can be significantly useful in the redesigning of the manufacturing layout.

Keywords: dynamic facility layout problem, internet of things, method time measurement, radio frequency identification, simulation

Procedia PDF Downloads 112

Authors: Reza Mollapourasl, Majid Haghi

Abstract:

In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.

Keywords: radial basis functions, Hermite finite difference, Helmholtz equation, stability

Procedia PDF Downloads 89

Authors: Mohamed Boualem Salah

Abstract:

The size and shape of soil particles reflect the formation history of the grains. In turn, the macro scale behavior of the soil mass results from particle level interactions which are affected by particle shape. Sphericity, roundness and smoothness characterize different scales associated to particle shape. New experimental data and data from previously published studies are gathered into two databases to explore the effects of particle shape on packing as well as small and large-strain properties of sandy soils. Data analysis shows that increased particle irregularity (angularity and/or eccentricity) leads to: an increase in emax and emin, a decrease in stiffness yet with increased sensitivity to the state of stress, an increase in compressibility under zero-lateral strain loading, and an increase in critical state friction angle φcs and intercept Γ with a weak effect on slope λ. Therefore, particle shape emerges as a significant soil index property that needs to be properly characterized and documented, particularly in clean sands and gravels. The systematic assessment of particle shape will lead to a better understanding of sand behavior.

Keywords: angularity, eccentricity, shape particle, behavior of soil

Procedia PDF Downloads 401

Authors: M. D. Antoine

Abstract:

When a child is diagnosed with an illness, condition, or developmental disorder, the process involved in understanding and accepting this diagnosis can be a very stressful and isolating experience for parents and families. The healthcare providers’ ability to effectively communicate in such situations represents a vital lifeline for parents. In this context, communication becomes a crucial element not only for getting through the period of grief but also for the future. We mobilized the five stages of grief model to summarize existing literature regarding the ways in which the experience ofan autism spectrum disorder diagnosis disclosurealigns with the experience of grief to explore how this can inform best practices for effective communication with parents through the diagnosis disclosure. Fifteen publications met inclusion criteria. Findings from the scoping review of empirical studies show that parents/families experience grief-like emotions during the diagnosis disclosure. However, grief is not an outcome of the encounter itself. In fact, the experience of the encounter can help mitigate the grief experience. The way parents/families receive and react to the ‘news’ depends on their preparedness, knowledge, and the support received through the experience. Individual communication skills, as well as policies and regulations, should be examined to alleviate adverse reactions in this context. These findings highlight the importance of further research into effective parent-provider communication strategies and their place in supporting quality autism care.

Keywords: autism spectrum disorder, autism spectrum disorder diagnosis, diagnosis disclosure, parent-provider communication, parental grief

Procedia PDF Downloads 163

Authors: Marcia Figueira

Abstract:

Context: Positivist transformations in agriculture were responsible for top-down – often coercive – mechanisms of uniformed modernization that weathered local diversities and agency. New development pathways need to now shift according to comprehensive integrations of knowledge - scientific, indigenous, and local, and to be sustained on political interventions, bottom-up change, and social learning if climate goals are to be met – both in mitigation and adaptation. Objectives The objectives of this research are to understand how social-ecological and socio-technical systems characterisation can be nested to bridge scientific research/knowledge into a local context and knowledge system; and, with it, stem sustainable innovation. Methods To do so, we conducted a scoping review to explore theoretical and empirical works linked to Ostrom’s Social-Ecological Systems framework and Geels’ multi-level perspective of socio-technical systems transformations in the context of agriculture. Results As a result, we were able to identify key variables and connections to 1- understand the rules in use and the community attributes influencing resource management; and 2- how they are and have been shaped and shaping systems innovations. Conclusion Based on these results, we discuss how to leverage action research for mutual learning toward a replicable but highly place-based agriculture transformation frame.

Keywords: agriculture systems innovations, social-ecological systems, socio-technical systems, action research

Procedia PDF Downloads 84

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

Abstract:

Predicting the risk of diabetic retinopathy (DR) in Indian type 2 diabetes patients is immensely necessary. India, being the second largest country after China in terms of a number of diabetic patients, to the best of our knowledge not a single risk score for complications has ever been investigated. Diabetic retinopathy is a serious complication and is the topmost reason for visual impairment across countries. Any type or form of DR has been taken as the event of interest, be it mild, back, grade I, II, III, and IV DR. A sample was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of DR. Cox proportional hazard regression is used to design risk scores for the prediction of retinopathy. Model calibration and discrimination are assessed from Hosmer Lemeshow and area under receiver operating characteristic curve (ROC). Overfitting and underfitting of the model are checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Optimal cut off point is chosen by Youden’s index. Five-year probability of DR is predicted by both survival function, and Markov chain two state model and the better technique is concluded. The risk scores developed can be applied by doctors and patients themselves for self evaluation. Furthermore, the five-year probabilities can be applied as well to forecast and maintain the condition of patients. This provides immense benefit in real application of DR prediction in T2DM.

Keywords: Cox proportional hazard regression, diabetic retinopathy, ROC curve, type 2 diabetes mellitus

Procedia PDF Downloads 170

Authors: Jaeseo Lim, Jooyong Park

Abstract:

Although there is ample evidence that student involvement enhances learning, college education is still mainly centered on lectures. However, in recent years, the effectiveness of discussions and the use of collective intelligence have attracted considerable attention. This study intends to examine the empirical effects of discussions on learning outcomes in various conditions. Eighty eight college students participated in the study and were randomly assigned to three groups. Group 1 was told to review material after a lecture, as in a traditional lecture-centered class. Students were given time to review the material for themselves after watching the lecture in a video clip. Group 2 participated in a discussion in groups of three or four after watching the lecture. Group 3 participated in a discussion after studying on their own. Unlike the previous two groups, students in Group 3 did not watch the lecture. The participants in the three groups were tested after studying. The test questions consisted of memorization problems, comprehension problems, and application problems. The results showed that the groups where students participated in discussions had significantly higher test scores. Moreover, the group where students studied on their own did better than that where students watched a lecture. Thus discussions are shown to be effective for enhancing learning. In particular, discussions seem to play a role in preparing students to solve application problems. This is a preliminary study and other age groups and various academic subjects need to be examined in order to generalize these findings. We also plan to investigate what kind of support is needed to facilitate discussions.

Keywords: discussions, education, learning, lecture, test

Procedia PDF Downloads 169

Authors: Fatma Tezel Sahin, Zeynep Nur Aydin Kilic, Aysegul Akinci Cosgun

Abstract:

Family involvement activities are a significant place in increasing the success in preschool education and maintaining the education. It is necessary that both of the parents be in the family involvement activities. However, while mother involvement is obtained in the family involvement activities, father involvement is neglected. For that reason, the current study aims at determining the views of teachers with regard to father involvement in the preschool education programs. The working group of the study consisted of 23 preschool teachers. The study is a descriptive survey. The data were obtained through individual interviews. As a data collection instrument, “Teacher Interview Form” was used. The data were analysed through content analysis method. The data regarding the views of the teachers were given as frequency and percentage values. At the end of the research, a great majority of the teachers stated that they were proficient in applying family involvement studies. They also pointed out that they held more family meetings in order to obtain family involvement and then they implemented involvement activities both in the class and out of the class for parents. They expressed that they observed more mother involvement in these activities that fathers. Parents expressed that the reasons why fathers involved in these activities less compared to mothers were the working conditions of fathers and that it was regarded as a task of mothers. Depending on the results of the research, it is likely to recommend that fathers should be informed about the involvement in family activities and that some applications and opportunities should be supplied for the fathers in preschool education institutions in order to encourage them.

Keywords: preschool education, parent involvement, father involvement, teacher views

Procedia PDF Downloads 311

Authors: Sunny Ewankhiwimen Aigbomian

Abstract:

Time, is a scarce resource and in everything we do, time is required to accomplish any given task. The need for this presentation is predicated on the way majority of Nigerian especially in the public sector operators see “Time Management”. Time as resources cannot be regained if lost or managed badly. As a significant aspect of human life it should be handled with diligence and utmost seriousness if the public sector is to function as a coordinated entity. In our homes, private life and offices, we schedule different things to ensure that some things do not go the unexpected. When it comes to service delivery on the part of government, it ought to be more serious because government is all about effect and efficient service delivery and “Time” is a significant variable necessary to successful accomplishment. The need for Nigerian government to re-examine time management in her public sector with a view of repositioning the sector to be able to compete well with other public sectors in the world. The peculiarity of Time management in Public Sector in Nigerian context as examined and some useful recommendations of immerse assistance proffered.

Keywords: Nigeria, public sector, time management, task

Procedia PDF Downloads 83

Authors: Pejman Daryabor, Kamal Mohammadi

Abstract:

In the present work, the study of vibration characteristics of a functionally graded thick hollow cylinder is investigated. The cylinder natural frequencies are obtained using Galerkin finite element method. The functionally graded cylinder is assumed to be made from many subcylinders. Each subcylinder is considered as an isotropic layer. Material’s properties in each layer are constant and functionally graded properties result by exponential function of layer radius in multilayer cylinder. To validate the FE results code, plane strain model of functionally graded cylinder are also modeled in ABAQUS. Analytical results are validated for both models. Also, a good agreement is found between the present results and those reported in the literature.

Keywords: natural frequency, functionally graded material, finite element method, thick cylinder

Procedia PDF Downloads 459

Authors: Perpetual Nwakaego Ibe

Abstract:

The Millennium Development Goals (MDGs), were an integrated project formed to eradicate many unnatural situations the citizens of the third world country may found themselves in. The MDGs, to be a sustainable project for the future depends 100% on the actions of governments, multilateral institutions and civil society. This paper first looks at the political views on the MDGs and relates it to the current electoral situations around the country by underlining the drastic changes over the few months. The second part of the paper presents ICT in tertiary institutions as one of the solutions in terms of the success of the MDGs. ICT is vital in all phases of educational process and development of the cloud connectivity is an added advantage of Information and Communication Technology (ICT) for sharing a common data bank for research purposes among UNICEF, RED CROSS, NPS, INEC, NMIC, and WHO. Finally, the paper concludes with areas that needs twigging and recommendations for the tertiary institutions committed to delivering an ambitious set of goals. A combination of observation, and document materials for data gathering was employed as the methodology for carrying out this research.

Keywords: MDG, ICT, data bank, database

Procedia PDF Downloads 189

Authors: Philip Friedlander, John Rutledge, Jason Suh

Abstract:

Inhibition of programmed death-1 (PD-1) or its ligand PD-L1 confers therapeutic efficacy in a wide range of solid tumor malignancies. Primary or acquired resistance can develop through activation of immunosuppressive immune cells such as tumor-associated macrophages. The renin angiotensin system (RAS) systemically regulates fluid and sodium hemodynamics, but components are expressed on and regulate the activity of immune cells, particularly of myeloid lineage. We hypothesized that inhibition of RAS would improve the efficacy of PD-1/PD-L-1 treatment. A retrospective analysis was performed through a chart review of patients with solid metastatic malignancies treated with a PD-1/PD-L1 inhibitor between 1/2013 and 6/2019 at Valley Hospital, a community hospital in New Jersey, USA. Efficacy was determined by medical oncologist documentation of clinical benefit in visit notes and by the duration of time on immunotherapy treatment. The primary endpoint was the determination of efficacy differences in patients treated with an inhibitor of RAS ( ace inhibitor, ACEi, or angiotensin blocker, ARB) compared to patients not treated with these inhibitors. To control for broader antihypertensive effects, efficacy as a function of treatment with beta blockers was assessed. 173 patients treated with PD-1/PD-L-1 inhibitors were identified of whom 52 were also treated with an ACEi or ARB. Chi-square testing revealed a statistically significant relationship between being on an ACEi or ARB and efficacy to PD-1/PD-L-1 therapy (p=0.001). No statistically significant relationship was seen between patients taking or not taking beta blocker antihypertensives (p= 0.33). Kaplan-Meier analysis showed statistically significant improvement in the duration of therapy favoring patients concomitantly treated with ACEi or ARB compared to patients not exposed to antihypertensives and to those treated with beta blockers. Logistic regression analysis revealed that age, gender, and cancer type did not have significant effects on the odds of experiencing clinical benefit (p=0.74, p=0.75, and p=0.81, respectively). We conclude that retrospective analysis of the treatment of patients with solid metastatic tumors with anti-PD-1/PD-L1 in a community setting demonstrates greater clinical benefit in the context of concomitant ACEi or ARB inhibition, irrespective of gender or age. This data supports the development of prospective assessment through randomized clinical trials.

Keywords: angiotensin, cancer, immunotherapy, PD-1, efficacy

Procedia PDF Downloads 61

Authors: Vinod Kumar, Surjit Angra

Abstract:

The objective of this theoretical study is to develop simple design formulas for the prediction of minimum film thickness and maximum mean film temperature rise in lightly loaded high-speed rolling/sliding lubricated elliptical contacts incorporating starvation effect. Herein, the reported numerical analysis focuses on thermoelastohydrodynamically lubricated rolling/sliding elliptical contacts, considering the Newtonian rheology of lubricant for wide range of operating parameters, namely load characterized by Hertzian pressure (PH = 0.01 GPa to 0.10 GPa), rolling speed (>10 m/s), slip parameter (S varies up to 1.0), and ellipticity ratio (k = 1 to 5). Starvation is simulated by systematically reducing the inlet supply. This analysis reveals that influences of load, rolling speed, and level of starvation are significant on the minimum film thickness. However, the maximum mean film temperature rise is strongly influenced by slip in addition to load, rolling speed, and level of starvation. In the presence of starvation, reduction in minimum film thickness and increase in maximum mean film temperature are observed. Based on the results of this study, empirical relations are developed for the prediction of dimensionless minimum film thickness and dimensionless maximum mean film temperature rise at the contacts in terms of various operating parameters.

Keywords: starvation, lubrication, elliptical contact, traction, minimum film thickness

Procedia PDF Downloads 380

Authors: Matthew Baucum

Abstract:

With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

Procedia PDF Downloads 435

Authors: Habtamu Ayenew Asegie

Abstract:

Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

Procedia PDF Downloads 28

Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

Abstract:

Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

Procedia PDF Downloads 77

Authors: Kun Huang

Abstract:

This paper investigates whether the combination of local and stochastic volatility models can be calibrated exactly to any arbitrage-free implied volatility surface of European option. The risk neutral Brownian Bridge density is applied for calibration of the leverage function of our Hybrid model. Furthermore, the tails of marginal risk neutral density are generated by Generalized Extreme Value distribution in order to capture the properties of asset returns. The local volatility is generated from the arbitrage-free implied volatility surface using stochastic volatility inspired parameterization.

Keywords: arbitrage free implied volatility, calibration, extreme value distribution, hybrid model, local volatility, risk-neutral density, stochastic volatility

Procedia PDF Downloads 255

Authors: L. Alejandro Cárdenas, Fernando Herrera, David Nova, Juan Ballesteros

Abstract:

This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic systems, considering the cleaning and module replacement periods based on an asset management strategy. The methodology is based on the analysis of the energy production of the PV plant, the energy feed-in tariff, and the cost of cleaning and replacement of the PV modules, with the overall revenue received being the optimization variable. The methodology is evaluated as a case study of a 5.6 kWp solar PV plant located on the Bogotá campus of the Universidad Nacional de Colombia. The asset management strategy implemented consists of assessing the PV modules through visual inspection, energy performance analysis, pollution, and degradation. Within the visual inspection of the plant, the general condition of the modules and the structure is assessed, identifying dust deposition, visible fractures, and water accumulation on the bottom. The energy performance analysis is performed with the energy production reported by the monitoring systems and compared with the values estimated in the simulation. The pollution analysis is performed using the soiling rate due to dust accumulation, which can be modelled by a black box with an exponential function dependent on historical pollution values. The pollution rate is calculated with data collected from the energy generated during two years in a photovoltaic plant on the campus of the National University of Colombia. Additionally, the alternative of assessing the temperature degradation of the PV modules is evaluated by estimating the cell temperature with parameters such as ambient temperature and wind speed. The medium-term energy decrease of the PV modules is assessed with the asset management strategy by calculating the health index to determine the replacement period of the modules due to degradation. This study proposes a tool for decision making related to the maintenance of photovoltaic systems. The above, projecting the increase in the installation of solar photovoltaic systems in power systems associated with the commitments made in the Paris Agreement for the reduction of CO2 emissions. In the Colombian context, it is estimated that by 2030, 12% of the installed power capacity will be solar PV.

Keywords: asset management, PV module, optimization, maintenance

Procedia PDF Downloads 25

Authors: P. Zamani, A. Taleshi Anbouhi, M. R. Ashory, S. Mohajerzadeh, M. M. Khatibi

Abstract:

Modal analysis is a developing science in the experimental evaluation of dynamic properties of the structures. Mechanical devices such as accelerometers are one of the sources of lack of quality in measuring modal testing parameters. In this paper, eliminating the accelerometer’s mass effect of the frequency response of the structure is studied. So, a strategy is used for eliminating the mass effect by using sensitivity analysis. In this method, the amount of mass change and the place to measure the structure’s response with least error in frequency correction is chosen. Experimental modal testing is carried out on a steel plate and the effect of accelerometer’s mass is omitted using this strategy. Finally, a good agreement is achieved between numerical and experimental results.

Keywords: accelerometer mass, frequency response function, modal analysis, sensitivity analysis

Procedia PDF Downloads 433

Authors: Sultan Ghaleb Aldaihani

Abstract:

- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

Procedia PDF Downloads 17

Authors: Rehab Mahmoud El Sayed, Toka Fahmy Nasr, Dalia M. Rasmi

Abstract:

Environmental psychology studies the interaction between the user and the environment. This field is crucial in understanding how the built environment affects human behaviour, moods and feelings. Studying and understanding the aspects and influences of environmental psychology is a crucial key to investigating how the design can influence human behaviour to be environmentally friendly. This is known as pro-environmental behaviour where human actions are sustainable and impacts the environment positively. Accordingly, this paper aims to explore the impact of built environment design on environmental psychology to foster pro-environmental behaviour in university campus open spaces. In order to achieve this, an exploratory research method was conducted where a detailed study of the influences of environmental psychology was done and clarified its elements. Moreover, investigating the impact of design elements on human psychology took place. Besides, an empirical study of the outdoor spaces of the British University in Egypt occurred and a survey for students and staff was distributed. The research concluded that the four main psychological aspects are mostly influenced by the following design elements colours, lighting and thermal comfort respectively. Additionally, focusing on these design elements in the design process will create a sustainable environment. As a consequence, the pro-environmental behaviour of the user will be fostered.

Keywords: environmental psychology, pro-environmental behavior, sustainable environment, psychological influences

Procedia PDF Downloads 73

Authors: Riktesh Srivastava

Abstract:

Online Shopping have established an astonishing evolution in the last few years. And it is now apparent that B2C architecture is becoming progressively imperative channel for even traditional brick and mortar type traders as well. In this completion knowing customers and predicting behavior are extremely important. More important, when any customer logs onto the B2C architecture, the traces of their buying patterns can be stored and used for future predictions. Such a prediction is called Customer Lifetime Value (CLV). Earlier, we used Net Present Value to do so, however, it ignores two important aspects of B2C architecture, “market risks” and “big amount of customer data”. Now, we use RFM- Recency, Frequency and Monetary Value to estimate the CLV, and as the term exemplifies, market risks, is well sheltered. Big Data Analysis is also roofed in RFM, which gives real exploration of the Big Data and lead to a better estimation for future cash flow from customers. In the present paper, 6 factors (collected from varied sources) are used to determine as to what attracts the customers to the B2C architecture. For these 6 factors, RFM is computed for 3 years (2013, 2014 and 2015) respectively. CLV and Revenue are the two parameters defined using RFM analysis, which gives the clear picture of the future predictions.

Keywords: CLV, RFM, revenue, recency, frequency, monetary value

Procedia PDF Downloads 211

Authors: Mohammed Kachtali, Imad Fenjiro, Jamal Alkarkouri

Abstract:

Wind erosion is a serious environmental problem in arid and semi-arid regions. Indeed, wind erosion easily removes the finest particles of the soil surface, which also contribute to losing soil fertility. The siltation of infrastructures and cultivated areas and the negative impact on health are additional consequences of wind erosion. In Morocco, wind erosion constitutes the main factor of silting up in coast and Sahara. The aim of our study is to use an equation of wind erosion in order to estimate the soil loses by wind erosion in the coast of Gharb (North of Morocco). The used equation in our model includes the geographic data, climatic data of 30 years and edaphic data collected from area study which contained 11 crossing of 4 stations. Our results have shown that the values of wind erosion are higher and very different between some crossings (p < 0.001). This difference is explained by topography, soil texture, and climate. In conclusion, wind erosion is higher in Gharb coast and varies from station to another; this problem required several methods of control and mitigation.

Keywords: Gharb coast, modeling, silting, wind erosion

Procedia PDF Downloads 127

Authors: Ghunchq Khan

Abstract:

The increase in greenhouse gas (GHGs) emissions is a main environmental problem. Diverse human activities and inappropriate economic growth have stimulated a trade-off between economic growth and environmental deterioration all over the world. The impact of economic growth on the environment has received attention as global warming and environmental problems have become more serious. The focus of this study is on carbon footprints (production and consumption) and analyses the impact of GDP per capita on carbon footprints. A balanced panel of 99 countries from 2000 to 2016 is estimated by employing autoregressive distributed lags (ARDL) model – mean group (MG) and pooled mean group (PMG) estimators. The empirical results indicate that GDP per capita has a significant and positive impact in the short run but a negative effect in the long run on the carbon footprint of production in high-income countries by controlling trade openness, industry share, biological capacity, and population density. At the same time, GDP per capita has a significant and positive impact in both the short and long run on the carbon footprint of the production of non-high-income countries. The results also indicate that GDP per capita negatively impacts the carbon footprint of consumption for high-income countries; on the other hand, the carbon footprint of consumption increases as GDP per capita grows in non-high-income countries.

Keywords: ARDL, carbon footprint, economic growth, industry share, trade openness

Procedia PDF Downloads 85

Authors: Martina Perinkova, Lenka Kolarcikova, Marketa Twrda

Abstract:

In Ostrava there are a lot of former post-industrial areas and areas that have gradually through conversions and their subsequent reuse. One of the largest is the national cultural monument Lower Vítkovice area where there is a large complex transformation of the former iron production. Industrial heritage today visited by tourists for entertainment, culture, history, sports and other activities. This is a unique example of reuse of technical monuments and introduction of new life into the historic area. The main task of not only find the right function and use, in terms of re integration into city life and finding a balance between history and current lifestyle, looking at the history of the area and its technical condition before reconstruction. It is not only very expensive but also time consuming. Transformations industrial monument is the result of a dialogue architect, the idea of the investor and expert opinion heritage institute.

Keywords: post-industrial area, cultural monument, conversions

Procedia PDF Downloads 328

Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

Abstract:

In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

Procedia PDF Downloads 358

Authors: Zainuddin Zakaria, Sun Woh Lye

Abstract:

Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers.

Keywords: air traffic control strategies, conflict resolution, simulator data, strategy classification system

Procedia PDF Downloads 135

Authors: Emberga Terhemb Opara Alexander, Selemo Alexader, Onyekwuru Samuel

Abstract:

The aeromagnetic data have been used to re-evaluate parts of the Upper Benue Trough Nigeria using spectral analysis technique in order to appraise the mineral accumulation potential of the area. The regional field was separated with a first order polynomial using polyfit program. The residual data was subdivided into 24 spectral blocks using OASIS MONTAJ software program. Two prominent magnetic depth source layers were identified. The deeper source depth values obtained ranges from 1.56km to 2.92km with an average depth of 2.37km as the magnetic basement depth while for the shallower sources, the depth values ranges from -1.17km to 0.98km with an average depth of 0.55km. The shallow depth source is attributed to the volcanic rocks that intruded the sedimentary formation and this could possibly be responsible for the mineralization found in parts of the study area.

Keywords: spectral analysis, Upper Benue Trough, magnetic basement depth, aeromagnetic

Procedia PDF Downloads 438

Authors: Nadine Yehya, Chantal Maatouk

Abstract:

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

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

Procedia PDF Downloads 209