Search results for: comprehensive performance index
17676 Sensitivity and Reliability Analysis of Masonry Infilled Frames
Authors: Avadhoot Bhosale, Robin Davis P., Pradip Sarkar
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The seismic performance of buildings with irregular distribution of mass, stiffness and strength along the height may be significantly different from that of regular buildings with masonry infill. Masonry infilled reinforced concrete (RC) frames are very common structural forms used for multi-storey building construction. These structures are found to perform better in past earthquakes owing to additional strength, stiffness and energy dissipation in the infill walls. The seismic performance of a building depends on the variation of material, structural and geometrical properties. The sensitivity of these properties affects the seismic response of the building. The main objective of the sensitivity analysis is to found out the most sensitive parameter that affects the response of the building. This paper presents a sensitivity analysis by considering 5% and 95% probability value of random variable in the infills characteristics, trying to obtain a reasonable range of results representing a wide number of possible situations that can be met in practice by using pushover analysis. The results show that the strength-related variation values of concrete and masonry, with the exception of tensile strength of the concrete, have shown a significant effect on the structural performance and that this effect increases with the progress of damage condition for the concrete. The seismic risk assessments of the selected frames are expressed in terms of reliability index.Keywords: fragility curve, sensitivity analysis, reliability index, RC frames
Procedia PDF Downloads 31917675 Health Risk Assessment According to Exposure with Heavy Metals and Physicochemical Parameters; Water Quality Index and Contamination Degree Evaluation in Bottled Water
Authors: Samaneh Abolli, Mahmood Alimohammadi
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The survey analyzed 71 bottled water brands in Tehran, Iran, examining 10 physicochemical parameters and 16 heavy metals. The water quality index (WQI) approach was used to assess water quality, and methods such as carcinogen risk (CR) and hazard index (HI) were employed to evaluate health risks. The results indicated that the bottled water had good quality overall, but some brands were of poor or very poor quality. The study also revealed significant human health risks, especially for children, due to the presence of minerals and heavy metals in bottled water. Correlation analyses and risk assessments for various substances were conducted, providing valuable insights into the potential health impacts of the analyzed bottled water.Keywords: bottled wate, rwater quality index, health risk assessment, contamination degree, heavy metal evaluation index
Procedia PDF Downloads 4617674 Clustering of Extremes in Financial Returns: A Comparison between Developed and Emerging Markets
Authors: Sara Ali Alokley, Mansour Saleh Albarrak
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This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.Keywords: clustring, extremes, returns, dependency, extermal index
Procedia PDF Downloads 39917673 Behavioral Assessment of the Role of Brain 5-HT4 Receptors on the Memory and Cognitive Performance in a Rat Model of Alzheimer Disease
Authors: Siamak Shahidi, Nasrin Hashemi-Firouzi, Sara Soleimani-Asl, Alireza Komaki
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Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive memory and cognitive performance. Recently, an involvement of the serotonergic system and their receptors are suspected in the AD progression. In the present behavioral study, the effects of BIMU (selective 5-HT4 receptor agonist) on cognition and memory in the rat model of AD was investigated. Material and Methods: The animal model of the AD was induced by intracerebroventricular (Icv) injection of amyloid beta (Aβ) in adult male Wistar rats. Animals were divided into experimental groups included control, sham, Aβ, Aβ +BIMU groups. The treatment substances were icv injected (1 μg/μL) for thirty consecutive days. Then, novel object recognition (NOR) and passive avoidance learning (PAL) tests were applied to investigate memory and cognitive performance. Results: Aβ decrease the discrimination index of NOR test. Also, it increases the time spent in the dark compartment during PAL test, as compared with sham and control groups. In addition, compared to Aβ groups, BIMU significantly increased the discrimination index of NOR test and decreased the time spent in the dark compartment of PAL test. Conclusion: These findings suggest that 5-HT4 receptor activation prevents progression of memory and cognitive impairment in a rat model of AD.Keywords: Alzheimer disease, cognition, memory, serotonin receptors
Procedia PDF Downloads 12817672 Optimization of Bifurcation Performance on Pneumatic Branched Networks in next Generation Soft Robots
Authors: Van-Thanh Ho, Hyoungsoon Lee, Jaiyoung Ryu
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Efficient pressure distribution within soft robotic systems, specifically to the pneumatic artificial muscle (PAM) regions, is essential to minimize energy consumption. This optimization involves adjusting reservoir pressure, pipe diameter, and branching network layout to reduce flow speed and pressure drop while enhancing flow efficiency. The outcome of this optimization is a lightweight power source and reduced mechanical impedance, enabling extended wear and movement. To achieve this, a branching network system was created by combining pipe components and intricate cross-sectional area variations, employing the principle of minimal work based on a complete virtual human exosuit. The results indicate that modifying the cross-sectional area of the branching network, gradually decreasing it, reduces velocity and enhances momentum compensation, preventing flow disturbances at separation regions. These optimized designs achieve uniform velocity distribution (uniformity index > 94%) prior to entering the connection pipe, with a pressure drop of less than 5%. The design must also consider the length-to-diameter ratio for fluid dynamic performance and production cost. This approach can be utilized to create a comprehensive PAM system, integrating well-designed tube networks and complex pneumatic models.Keywords: pneumatic artificial muscles, pipe networks, pressure drop, compressible turbulent flow, uniformity flow, murray's law
Procedia PDF Downloads 7117671 An Improved Parallel Algorithm of Decision Tree
Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng
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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.Keywords: classification, Gini index, parallel data mining, pruning ahead
Procedia PDF Downloads 11617670 Formulating Model of Green Supply Chain Impact on Chain Operational Performance, Case Study: Rahbaran Foolad Aria, Steel Industry
Authors: Seyedeh Mersedeh Banijamali, Ali Rajabzadeh
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Industrial development in recent centuries has been replaced by a sustainable development. The industry executives, particularly in the development countries are looking for procedures to protect the environment, improve their organization's performance. One of these approaches is the green supply chain management. Green supply chain management approach as a comprehensive approach to environmental management that contains all flows from suppliers to producers and ultimately to consumers, in many industries, particularly in the Steel industry, which has a strategic role in the country's industrial and economic development, has been receiving significant attention. The purpose of this study is examining the impact of green supply chain on chain operational performance in the Steel industry and formulating model for it. In this way, first the components of green supply chain (in 5 dimensions, planning, sourcing, making, delivery and return) have been prioritized through TOPSIS decision technique and then impact of these components on operational performance has been modeled with model dynamic systems and Vensim software. This research shows that green supply chain has a positive impact on operational performance and improve it.Keywords: green supply chain, the dimensions of the green supply chain, operational performance, steel industry, dynamical systems
Procedia PDF Downloads 56617669 The Efficacy of Open Educational Resources in Students’ Performance and Engagement
Authors: Huda Al-Shuaily, E. M. Lacap
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Higher Education is one of the most essential fundamentals for the advancement and progress of a country. It demands to be as accessible as possible and as comprehensive as it can be reached. In this paper, we succeeded to expand the accessibility and delivery of higher education using an Open Educational Resources (OER), a freely accessible, openly licensed documents, and media for teaching and learning. This study creates a comparative design of student’s academic performance on the course Introduction to Database and student engagement to the virtual learning environment (VLE). The study was done in two successive semesters - one without using the OER and the other is using OER. In the study, we established that there is a significant increase in student’s engagement in VLE in the latter semester compared to the former. By using the latter semester’s data, we manage to show that the student’s engagement has a positive impact on students’ academic performance. Moreso, after clustering their academic performance, the impact is seen higher for students who are low performing. The results show that these engagements can be used to potentially predict the learning styles of the student with a high degree of precision.Keywords: EDM, learning analytics, moodle, OER, student-engagement
Procedia PDF Downloads 33417668 Pavement Roughness Prediction Systems: A Bump Integrator Approach
Authors: Manish Pal, Rumi Sutradhar
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Pavement surface unevenness plays a pivotal role on roughness index of road which affects on riding comfort ability. Comfort ability refers to the degree of protection offered to vehicle occupants from uneven elements in the road surface. So, it is preferable to have a lower roughness index value for a better riding quality of road users. Roughness is generally defined as an expression of irregularities in the pavement surface which can be measured using different equipment like MERLIN, Bump integrator, Profilometer etc. Among them Bump Integrator is quite simple and less time consuming in case of long road sections. A case study is conducted on low volume roads in West District in Tripura to determine roughness index (RI) using Bump Integrator at the standard speed of 32 km/h. But it becomes too tough to maintain the requisite standard speed throughout the road section. The speed of Bump Integrator (BI) has to lower or higher in some distinctive situations. So, it becomes necessary to convert these roughness index values of other speeds to the standard speed of 32 km/h. This paper highlights on that roughness index conversional model. Using SPSS (Statistical Package of Social Sciences) software a generalized equation is derived among the RI value at standard speed of 32 km/h and RI value at other speed conditions.Keywords: bump integrator, pavement distresses, roughness index, SPSS
Procedia PDF Downloads 24217667 Efficiency and Equity in Italian Secondary School
Authors: Giorgia Zotti
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This research comprehensively investigates the multifaceted interplay determining school performance, individual backgrounds, and regional disparities within the landscape of Italian secondary education. Leveraging data gleaned from the INVALSI 2021-2022 database, the analysis meticulously scrutinizes two fundamental distributions of educational achievements: the standardized Invalsi test scores and official grades in Italian and Mathematics, focusing specifically on final-year secondary school students in Italy. Applying a comprehensive methodology, the study initially employs Data Envelopment Analysis (DEA) to assess school performances. This methodology involves constructing a production function encompassing inputs (hours spent at school) and outputs (Invalsi scores in Italian and Mathematics, along with official grades in Italian and Math). The DEA approach is applied in both of its versions: traditional and conditional. The latter incorporates environmental variables such as school type, size, demographics, technological resources, and socio-economic indicators. Additionally, the analysis delves into regional disparities by leveraging the Theil Index, providing insights into disparities within and between regions. Moreover, in the frame of the inequality of opportunity theory, the study quantifies the inequality of opportunity in students' educational achievements. The methodology applied is the Parametric Approach in the ex-ante version, considering diverse circumstances like parental education and occupation, gender, school region, birthplace, and language spoken at home. Consequently, a Shapley decomposition is applied to understand how much each circumstance affects the outcomes. The outcomes of this comprehensive investigation unveil pivotal determinants of school performance, notably highlighting the influence of school type (Liceo) and socioeconomic status. The research unveils regional disparities, elucidating instances where specific schools outperform others in official grades compared to Invalsi scores, shedding light on the intricate nature of regional educational inequalities. Furthermore, it emphasizes a heightened inequality of opportunity within the distribution of Invalsi test scores in contrast to official grades, underscoring pronounced disparities at the student level. This analysis provides insights for policymakers, educators, and stakeholders, fostering a nuanced understanding of the complexities within Italian secondary education.Keywords: inequality, education, efficiency, DEA approach
Procedia PDF Downloads 7117666 Structural Reliability of Existing Structures: A Case Study
Authors: Z. Sakka, I. Assakkaf, T. Al-Yaqoub, J. Parol
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A reliability-based methodology for the analysis assessment and evaluation of reinforced concrete structural elements of concrete structures is presented herein. The results of the reliability analysis and assessment for structural elements are verified by the results obtained from the deterministic methods. The analysis outcomes of reliability-based analysis are compared against the safety limits of the required reliability index β according to international standards and codes. The methodology is based on probabilistic analysis using reliability concepts and statistics of the main random variables that are relevant to the subject matter, and for which they are to be used in the performance-function equation(s) related to the structural elements under study. These methodology techniques can result in reliability index β, which is commonly known as the reliability index or reliability measure value that can be utilized to assess and evaluate the safety, human risk, and functionality of the structural component. Also, these methods can result in revised partial safety factor values for certain target reliability indices that can be used for the purpose of redesigning the reinforced concrete elements of the building and in which they could assist in considering some other remedial actions to improve the safety and functionality of the member.Keywords: structural reliability, concrete structures, FORM, Monte Carlo simulation
Procedia PDF Downloads 51117665 An Experimental Study on Service Life Prediction of Self: Compacting Concrete Using Sorptivity as a Durability Index
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Permeation properties have been widely used to quantify durability characteristics of concrete for assessing long term performance and sustainability. The processes of deterioration in concrete are mediated largely by water. There is a strong interest in finding a better way of assessing the material properties of concrete in terms of durability. Water sorptivity is a useful single material property which can be one of the measures of durability useful in service life planning and prediction, especially in severe environmental conditions. This paper presents the results of the comparative study of sorptivity of Self-Compacting Concrete (SCC) with conventionally vibrated concrete. SCC is a new, special type of concrete mixture, characterized by high resistance to segregation that can flow through intricate geometrical configuration in the presence of reinforcement, under its own mass, without vibration and compaction. SCC mixes were developed for the paste contents of 0.38, 0.41 and 0.43 with fly ash as the filler for different cement contents ranging from 300 to 450 kg/m3. The study shows better performance by SCC in terms of capillary absorption. The sorptivity value decreased as the volume of paste increased. The use of higher paste content in SCC can make the concrete robust with better densification of the micro-structure, improving the durability and making the concrete more sustainable with improved long term performance. The sorptivity based on secondary absorption can be effectively used as a durability index to predict the time duration required for the ingress of water to penetrate the concrete, which has practical significance.Keywords: self-compacting concrete, service life prediction, sorptivity, volume of paste
Procedia PDF Downloads 31517664 Characterization of CuO Incorporated CMOS Dielectric for Fast Switching System
Authors: Nissar Mohammad Karim, Norhayati Soin
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To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.Keywords: refractive index, Sol-Gel, precursor aging, aging
Procedia PDF Downloads 46717663 Phytoplankton Community and Saprobic Pollution Index of Warm Water Fishes Ponds at East of Golestan Province: Case Study: Gonbade Kavous City
Authors: Mehrdad Kamali-Sanzighi, Maziar Kamali-Sanzighi
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The aim of this investigation is to study the phytoplankton and saprobic index at warm water fish ponds in the East of Golestan province, Gonbade Kavous city. Phytoplankton and ciliate sampling were done monthly during one season of culture. Finally, 39 genera from 7 classes of phytoplankton and 4 genera from the ciliate group were identified. Although, among different classes, Chlorophyceae, Cyanophyceae, Bacillariophyceae, Charophyceae, Chrysophyceae, Dinophyceae, and Euglenophyceae had the highest and lowest frequency percent of phytoplankton community with 23, 21, 20, 14, 11, 6 and 5 percent respectively. The results show that there are no significant differences between the saprobic index of different ponds (P > 0.05). But there are significant differences between the saprobic index value of different months and seasons during season culture (P < 0.05). Also, in current research, the saprobic index indicated the ß-mesosaprob water quality level. There was a general tends of decrease in the saprobic index value from the beginning to the end of the culture season. Parameters such as biomass increase of grower fishes, an increase of introduced chemical fertilizer and manure sedimentation, uneaten fish feed, fish fecal, and no regular exchangeable water resources are some of these changes' reasons.Keywords: fish pond, Golestan Province, saprobi index, phytoplankton, water quality
Procedia PDF Downloads 13217662 Psychometrics of the Farsi Version of the Newcastle Nursing Care Satisfaction Scale in Patients Admitted to the Internal and General Surgery Departments of Hospitals Affiliated with Ardabil University of Medical Sciences in 2017
Authors: Mansoureh Karimollahi, Mehriar Adrmohammadi, Mohsen Mohammadi
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Introduction: Patient satisfaction with nursing care is considered as an important indicator of the quality and effectiveness of the health care system, and improving the quality of care is not possible without paying attention to the opinions and expectations of patients. Considering that the scales for assessing satisfaction with nursing care in our country are not comprehensive and measure very few areas, therefore, in this study, psychometrically, the Persian version of the Newcastle Nursing Care Satisfaction Scale was used in patients hospitalized in the wards. Internal medicine and general surgery were discussed. Methods: This cross-sectional study was conducted on 200 patients admitted to the surgery and internal departments of hospitals affiliated to Ardabil University of Medical Sciences. The Newcastle nursing care satisfaction scale was used for the first time in Iran in comparison with the good nursing care scale from the patients' point of view to evaluate the criterion validity. The Newcastle nursing care satisfaction scale was used after translation, validity, and reliability. Results: The level of satisfaction of patients and the experience of patients with nursing care was at a favorable level, respectively, with an average of 111.8 ± 14.2 and 69.07 ± 14.8. Total CVI was estimated at 0.96 for the experience section, 0.95 for the satisfaction section, and 0.96 for the whole scale. The index (CVR) was also 0.95 for the experience section, 0.95 for the satisfaction section, and 0.95 for the whole scale. Criterion validity was also estimated using 0.725 correlation. The validity of the construct was also confirmed using the goodness of fit index (X2=1932/05, p=0.013, KMO=0.913). Convergent validity was estimated at 0.99 in the experience subscale and 0.98 in the satisfaction subscale. . The overall reliability in the experience subscale and satisfaction subscale was 94%, 92%, and 98%, respectively, which indicated the acceptable reliability of the questionnaire. Conclusion: The Persian version of the Newcastle nursing care satisfaction scale as a comprehensive tool that can be easily completed by patients and is easy to interpret, has good validity and reliability and can be used in patient care centers, in departments Surgery, and internal medicine are recommended.Keywords: psychometrics, Newcastle nursing care satisfaction scale, nursing care satisfaction, general surgery department
Procedia PDF Downloads 9017661 Genome-Wide Analysis of BES1/BZR1 Gene Family in Five Plant Species
Authors: Jafar Ahmadi, Zhohreh Asiaban, Sedigheh Fabriki Ourang
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Brassinosteroids (BRs) regulate cell elongation, vascular differentiation, senescence and stress responses. BRs signal through the BES1/BZR1 family of transcription factors, which regulate hundreds of target genes involved in this pathway. In this research a comprehensive genome-wide analysis was carried out in BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus, Vitis vinifera, Glycin max, and Brachypodium distachyon. Specifications of the desired sequences, dot plot and hydropathy plot were analyzed in the protein and genome sequences of five plant species. The maximum amino acid length was attributed to protein sequence Brdic3g with 374aa and the minimum amino acid length was attributed to protein sequence Gm7g with 163aa. The maximum Instability index was attributed to protein sequence AT1G19350 equal with 79.99 and the minimum Instability index was attributed to protein sequence Gm5g equal with 33.22. Aliphatic index of these protein sequences ranged from 47.82 to 78.79 in Arabidopsis thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in Cucumis sativus. Overall, data obtained from our investigation contributes a better understanding of the complexity of the BES1/BZR1 gene family and provides the first step towards directing future experimental designs to perform systematic analysis of the functions of the BES1/BZR1 gene family.Keywords: BES1/BZR1, brassinosteroids, phylogenetic analysis, transcription factor
Procedia PDF Downloads 33317660 Gradient Index Metalens for WLAN Applications
Authors: Akram Boubakri, Fethi Choubeni, Tan Hoa Vuong, Jacques David
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The control of electromagnetic waves is a key aim of several researches over the past decade. In this regard, Metamaterials have shown a strong ability to manipulate the electromagnetic waves on a subwavelength scales thanks to its unconventional properties that are not available in natural materials such as negative refraction index, super imaging and invisibility cloaking. Metalenses were used to avoid some drawbacks presented by conventional lenses since focusing with conventional lenses suffered from the limited resolution because they were only able to focus the propagating wave component. Nevertheless, Metalenses were able to go beyond the diffraction limit and enhance the resolution not only by collecting the propagating waves but also by restoring the amplitude of evanescent waves that decay rapidly when going far from the source and that contains the finest details of the image. Metasurfaces have many mechanical advantages over three-dimensional metamaterial structures especially the ease of fabrication and a smaller required volume. Those structures have been widely used for antenna performance improvement and to build flat metalenses. In this work, we showed that a well-designed metasurface lens operating at the frequency of 5.9GHz, has efficiently enhanced the radiation characteristics of a patch antenna and can be used for WLAN applications (IEEE 802.11 a). The proposed metasurface lens is built with a geometrically modified unit cells which lead to a change in the response of the lens at different position and allow the control of the wavefront beam of the incident wave thanks to the gradient refractive index.Keywords: focusing, gradient index, metasurface, metalens, WLAN Applications
Procedia PDF Downloads 25217659 Data-Driven Performance Evaluation of Surgical Doctors Based on Fuzzy Analytic Hierarchy Processes
Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng
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To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation
Procedia PDF Downloads 4917658 Remote Assessment and Change Detection of GreenLAI of Cotton Crop Using Different Vegetation Indices
Authors: Ganesh B. Shinde, Vijaya B. Musande
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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices
Procedia PDF Downloads 31217657 Using Support Vector Machines for Measuring Democracy
Authors: Tommy Krieger, Klaus Gruendler
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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.Keywords: democracy, democracy index, machine learning, support vector machines
Procedia PDF Downloads 37017656 Modified Clusterwise Regression for Pavement Management
Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella
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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.Keywords: clusterwise regression, pavement management system, performance model, optimization
Procedia PDF Downloads 24417655 Assessing the Vulnerability Level in Coastal Communities in the Caribbean: A Case Study of San Pedro, Belize
Authors: Sherry Ann Ganase, Sandra Sookram
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In this paper, the vulnerability level to climate change is analysed using a comprehensive index, consisting of five pillars: human, social, natural, physical, and financial. A structural equation model is also applied to determine the indicators and relationships that exist between the observed environmental changes and the quality of life. Using survey data to model the results, a value of 0.382 is derived as the vulnerability level for San Pedro, where values closer to zero indicates lower vulnerability and values closer to one indicates higher vulnerability. The results showed the social pillar to be most vulnerable, with the indicator ‘participation’ ranked the highest in its cohort. Although, the environmental pillar is ranked as least vulnerable, the indicators ‘hazard’ and ‘biodiversity’ obtained scores closer to 0.4, suggesting that changes in the environment are occurring from natural and anthropogenic activities. These changes can negatively influence the quality of life as illustrated in the structural equation modelling. The study concludes by reporting on the need for collective action and participation by households in lowering vulnerability to ensure sustainable development and livelihood.Keywords: climate change, participation, San Pedro, structural equation model, vulnerability index
Procedia PDF Downloads 62417654 Evaluation of Three Digital Graphical Methods of Baseflow Separation Techniques in the Tekeze Water Basin in Ethiopia
Authors: Alebachew Halefom, Navsal Kumar, Arunava Poddar
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The purpose of this work is to specify the parameter values, the base flow index (BFI), and to rank the methods that should be used for base flow separation. Three different digital graphical approaches are chosen and used in this study for the purpose of comparison. The daily time series discharge data were collected from the site for a period of 30 years (1986 up to 2015) and were used to evaluate the algorithms. In order to separate the base flow and the surface runoff, daily recorded streamflow (m³/s) data were used to calibrate procedures and get parameter values for the basin. Additionally, the performance of the model was assessed by the use of the standard error (SE), the coefficient of determination (R²), and the flow duration curve (FDC) and baseflow indexes. The findings indicate that, in general, each strategy can be used worldwide to differentiate base flow; however, the Sliding Interval Method (SIM) performs significantly better than the other two techniques in this basin. The average base flow index was calculated to be 0.72 using the local minimum method, 0.76 using the fixed interval method, and 0.78 using the sliding interval method, respectively.Keywords: baseflow index, digital graphical methods, streamflow, Emba Madre Watershed
Procedia PDF Downloads 7217653 Characterizing of CuO Incorporated CMOS Dielectric for Fast Switching System
Authors: Nissar Mohammad Karim, Norhayati Soin
Abstract:
To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.Keywords: refractive index, sol-gel, precursor ageing, metallurgical and materials engineering
Procedia PDF Downloads 37817652 Development of Map of Gridded Basin Flash Flood Potential Index: GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue Provinces
Authors: Le Xuan Cau
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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map
Procedia PDF Downloads 37617651 Effects of China's Urban Form on Urban Carbon Emission
Authors: Lu Lin
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Urbanization has reshaped physical environment, energy consumption and carbon emission of the urban area. China is a typical developing country under a rapid urbanization process and is the world largest carbon emission country. This study aims to explore the correlation between urban form and carbon emission caused by urban energy consumption in China. 287 provincial-level and prefecture-level cities are studied in 2000, 2005, and 2010. Compact ratio index, shape index, and fractal dimension index are used to quantify urban form. Geographically weighted regression (GWR) model is employed to explore the relationship between urban form, energy consumption, and related carbon emission. The results show the average compact ratio index decreased from 2000 to 2010 which indicates urban in China sprawled. The average fractal dimension index increases by 3%, indicating the spatial layouts of China's cities were more complicated. The results by the GWR model show that shape index and fractal dimension index had a non-significant relationship with carbon emission by urban energy consumption. However, compact urban form reduced carbon emission. The findings of this study will help policy-makers make sustainable urban planning and reduce urban carbon emission.Keywords: carbon emission, GWR model, urban energy consumption, urban form
Procedia PDF Downloads 33517650 Uncovering the Role of Crystal Phase in Determining Nonvolatile Flash Memory Device Performance Based on 2D Van Der Waals Heterostructures
Authors: Yunpeng Xia, Jiajia Zha, Haoxin Huang, Hau Ping Chan, Chaoliang Tan
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Although the crystal phase of two-dimensional (2D) transition metal dichalcogenides (TMDs) has been proven to play an essential role in fabricating high-performance electronic devices in the past decade, its effect on the performance of 2D material-based flash memory devices still remains unclear. Here, we report the exploration of the effect of MoTe₂ in different phases as the charge trapping layer on the performance of 2D van der Waals (vdW) heterostructure-based flash memory devices, where the metallic 1T′-MoTe₂ or semiconducting 2H-MoTe₂ nanoflake is used as the floating gate. By conducting comprehensive measurements on the two kinds of vdW heterostructure-based devices, the memory device based on MoS2/h-BN/1T′-MoTe₂ presents much better performance, including a larger memory window, faster switching speed (100 ns) and higher extinction ratio (107), than that of the device based on MoS₂/h-BN/2H-MoTe₂ heterostructure. Moreover, the device based on MoS₂/h-BN/1T′-MoTe₂ heterostructure also shows a long cycle (>1200 cycles) and retention (>3000 s) stability. Our study clearly demonstrates that the crystal phase of 2D TMDs has a significant impact on the performance of nonvolatile flash memory devices based on 2D vdW heterostructures, which paves the way for the fabrication of future high-performance memory devices based on 2D materials.Keywords: crystal Phase, 2D van der Waals heretostructure, flash memory device, floating gate
Procedia PDF Downloads 4417649 Biomechanical Analysis and Interpretation of Pitching Sequences for Enhanced Performance Programming
Authors: Corey F. Fitzgerald
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This study provides a comprehensive examination of the biomechanical sequencing inherent in pitching motions, coupled with an advanced methodology for interpreting gathered data to inform programming strategies. The analysis is conducted utilizing state-of-the-art biomechanical laboratory equipment capable of detecting subtle changes and deviations, facilitating highly informed decision-making processes. Through this presentation, the intricate dynamics of pitching sequences are meticulously discussed to highlight the complex movement patterns accessible and actionable for performance enhancement purposes in the weight room.Keywords: sport science, applied biomechanics, strength and conditioning, applied research
Procedia PDF Downloads 5517648 Financial Markets Performance: From COVID-19 Crisis to Hopes of Recovery with the Containment Polices
Authors: Engy Eissa, Dina M. Yousri
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COVID-19 has hit massively the world economy, financial markets and even societies’ livelihood. The infectious disease caused by the most recently discovered coronavirus was claimed responsible for a shrink in the global economy by 4.4% in 2020. Shortly after the first case in Wuhan was identified, a quick surge in the number of confirmed cases in China was evident and a vast spread worldwide is recorded with cases surpassing the 500,000 cases. Irrespective of the disease’s trajectory in each country, a call for immediate action and prompt government intervention was needed. Given that there is no one-size-fits-all approach across the world, a number of containment and adoption policies were embraced. It was starting by enforcing complete lockdown like China to even stricter policies targeted containing the spread of the virus, augmenting the efficiency of health systems, and controlling the economic outcomes arising from this crisis. Hence, this paper has three folds; first, it examines the impact of containment policies taken by governments on controlling the number of cases and deaths in the given countries. Second, to assess the ramifications of COVID-19 on financial markets measured by stock returns. Third, to study the impact of containment policies measured by the government response index, the stringency index, the containment health index, and the economic support index on financial markets performance. Using a sample of daily data covering the period 31st of January 2020 to 15th of April 2021 for the 10 most hit countries in wave one by COVID-19 namely; Brazil, India, Turkey, Russia, UK, USA, France, Germany, Spain, and Italy. The aforementioned relationships were tested using Panel VAR Regression. The preliminary results showed that the number of daily deaths had an impact on the stock returns; moreover, the health containment policies and the economic support provided by the governments had a significant effect on lowering the impact of COVID-19 on stock returns.Keywords: COVID-19, government policies, stock returns, VAR
Procedia PDF Downloads 17817647 Deep Learning Approach for Chronic Kidney Disease Complications
Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia
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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis
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