Search results for: geographically weighted principal components analysis

Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

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The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

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Authors: Wangxu Xia

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BACKGROUND BI-RADS 4 lesions raise the possibility of malignancy that warrant further clinical and radiologic work-up. This study aimed to evaluate the predictive performance of diffusion-weighted imaging(DWI) and microcalcifications on mammography for predicting malignancy of BI-RADS 4 lesions. In addition, the predictive performance of DWI combined with microcalcifications was alsocompared with the Kaiser score. METHODS During January 2021 and June 2023, 144 patients with 178 BI-RADS 4 lesions underwent conventional MRI, DWI, and mammography were included. The lesions were dichotomized intobenign or malignant according to the pathological results from core needle biopsy or surgical mastectomy. DWI was performed with a b value of 0 and 800s/mm2 and analyzed using theapparent diffusion coefficient, and a Kaiser score > 4 was considered to suggest malignancy. Thediagnostic performances for various diagnostic tests were evaluated with the receiver-operatingcharacteristic (ROC) curve. RESULTS The area under the curve (AUC) for DWI was significantly higher than that of the of mammography (0.86 vs 0.71, P<0.001), but was comparable with that of the Kaiser score (0.86 vs 0.84, P=0.58). However, the AUC for DWI combined with mammography was significantly highthan that of the Kaiser score (0.93 vs 0.84, P=0.007). The sensitivity for discriminating malignant from benign BI-RADS 4 lesions was highest at 89% for Kaiser score, but the highest specificity of 83% can be achieved with DWI combined with mammography. CONCLUSION DWI combined with microcalcifications on mammography could discriminate malignant BI-RADS4 lesions from benign ones with a high AUC and specificity. However, Kaiser score had a better sensitivity for discrimination.

Keywords: MRI, DWI, mammography, breast disease

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Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus

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Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.

Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.

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Authors: Md. Monjurul Islam, Tofael Ahamed, Ryozo Noguchi

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Progress continues in the fight against hunger, yet an unacceptably large number of people still lack food they need for an active and healthy life. Bangladesh is one of the rising countries in the South-Asia but still lots of people are food insecure. In the last few years, Bangladesh has significant achievements in food grain production but still food security at national to individual levels remain a matter of major concern. Ensuring food security for all is one of the major challenges that Bangladesh faces today, especially production of rice in the flood and poverty prone areas. Northern part is more vulnerable than any other part of Bangladesh. To ensure food security, one of the best way is to increase domestic production. To increase production, it is necessary to secure lands for achieving optimum utilization of resources. One of the measures is to identify the vulnerable and potential areas using Land Suitability Assessment (LSA) to increase rice production in the poverty prone areas. Therefore, the aim of the study was to identify the suitable sites for food grain crop rice production in the poverty prone areas located at the northern part of Bangladesh. Lack of knowledge on the best combination of factors that suit production of rice has contributed to the low production. To fulfill the research objective, a multi-criteria analysis was done and produced a suitable map for crop production with the help of Geographical Information System (GIS) and Analytical Hierarchy Process (AHP). Primary and secondary data were collected from ground truth information and relevant offices. The suitability levels for each factor were ranked based on the structure of FAO land suitability classification as: Currently Not Suitable (N2), Presently Not Suitable (N1), Marginally Suitable (S3), Moderately Suitable (S2) and Highly Suitable (S1). The suitable sites were identified using spatial analysis and compared with the recent raster image from Google Earth Pro® to validate the reliability of suitability analysis. For producing a suitability map for rice farming using GIS and multi-criteria analysis tool, AHP was used to rank the relevant factors, and the resultant weights were used to create the suitability map using weighted sum overlay tool in ArcGIS 10.3®. Then, the suitability map for rice production in the study area was formed. The weighted overly was performed and found that 22.74 % (1337.02 km2) of the study area was highly suitable, while 28.54% (1678.04 km2) was moderately suitable, 14.86% (873.71 km2) was marginally suitable, and 1.19% (69.97 km2) was currently not suitable for rice farming. On the other hand, 32.67% (1920.87 km2) was permanently not suitable which occupied with settlements, rivers, water bodies and forests. This research provided information at local level that could be used by farmers to select suitable fields for rice production, and then it can be applied to other crops. It will also be helpful for the field workers and policy planner who serves in the agricultural sector.

Keywords: AHP, GIS, spatial analysis, land suitability

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Authors: R. B. Patil, B. S. Kothavale, L. Y. Waghmode

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Today, the CNC turning center becomes an important machine tool for manufacturing industry worldwide. However, as the breakdown of a single CNC turning center may result in the production of an entire plant being halted. For this reason, operations and preventive maintenance have to be minimized to ensure availability of the system. Indeed, improving the availability of the CNC turning center as a whole, objectively leads to a substantial reduction in production loss, operating, maintenance and support cost. In this paper, fault tree analysis (FTA) method is used for reliability analysis of CNC turning center. The major faults associated with the system and the causes for the faults are presented graphically. Boolean algebra is used for evaluating fault tree (FT) diagram and for deriving governing reliability model for CNC turning center. Failure data over a period of six years has been collected and used for evaluating the model. Qualitative and quantitative analysis is also carried out to identify critical sub-systems and components of CNC turning center. It is found that, at the end of the warranty period (one year), the reliability of the CNC turning center as a whole is around 0.61628.

Keywords: fault tree analysis (FTA), reliability analysis, risk assessment, hazard analysis

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Seda Birbilener, Semsettin Kulac, Zeki Severoglu

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In this study, we have performed genetic diversity analysis of Tilia tomentosa genotypes by using randomly amplified polymorphic DNA (RAPD) primers. A total of 28 genotypes, including 25 members from the urban ecosystem and 3 genotypes from forest ecosystem as outgroup were used. 8 RAPD primers produced a total of 53 bands, of which 48 (90.6 %) were polymorphic. Percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), Nei's (1973) gene diversity (h), and Shannon's information index (I) were found as 94.29 %, 1.94, 1.60, 0.34, and 0.50, respectively. The unweighted pair-group method with arithmetic average (UPGMA) cluster analysis revealed that two major groups were observed. The genotypes of urban and forest ecosystems showed a high genetic similarity between 28% and 92% and these genotypes did not separate from each other in UPGMA tree. Also, urban and forest genotypes clustered together in principal component analysis (PCA).

Keywords: Tilia tomentosa, genetic diversity, urban ecosystem, RAPD, UPGMA

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Authors: Thinakar Mani Balusamy, Venkateswaran A. R., Bharat Narasimhan, Ratnakar Kini S., Kani Sheikh M., Prem Kumar K., Pugazhendi Thangavelu, Arun Murugan, Sibi Thooran Karmegam, Radhakrishnan N., Mohammed Noufal, Amit Soni

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Background and Aims: The liver is integral to lipid metabolism, and a compromise in its function leads to perturbations in these pathways. In this study, we hope to determine the correlation between CLD severity and its effect on lipid parameters. We also look at the etiology-specific effects on lipid levels. Materials and Methods: This is a retrospective cross-sectional analysis of 250 patients with cirrhosis compared to 250 healthy age and sex-matched controls. Severity assessment of CLD using MELD and Child-Pugh scores was performed and etiological details collected. A questionnaire was used to obtain patient demographic details and lastly, a fasting lipid profile (Total, LDL, HDL cholesterol, Triglycerides and VLDL) was obtained. Results: All components of the lipid profile declined linearly with increasing severity of CLD as determined by MELD and Child-Pugh scores. Lipid levels were clearly lower in CLD patients as compared to healthy controls. Interestingly, preliminary analysis indicated that CLD of different etiologies had differential effects on Lipid profiles. This aspect is under further analysis. Conclusion: All components of the lipid profile were definitely lower in CLD patients as compared to controls and demonstrated an inverse correlation with increasing severity. The utilization of this parameter as a prognosticating aid requires further study. Additionally, preliminary analysis indicates that various CLD etiologies appear to have specific effects on the lipid profile – a finding under further analysis.

Keywords: CLD, cholesterol, HDL, LDL, lipid profile, triglycerides, VLDL

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: A. Larrousi, M. Elkeurti, K. Amara, M. Zemouli, L. H. Coudert, I. R. Medvedev, F. C. De Lucia, Atsuko Maeda, R. W. C. McKellar, D. Appadoo

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Experimental and theoretical investigations of the microwave and far infrared spectra of CH3COD are reported. Two hundred twelve lines were identified in the far infrared spectrum recorded using the Canadian synchrotron radiation light source. Two thousand one hundred and sixty-eight lines in vt=0,1 and 216 in vt=2 have been measured in the microwave spectrum obtained using the fast scan submillimeter spectroscopic technique. A global analysis of the new data and of already available microwave lines has been carried out and yielded values for rotation–torsion parameters. The unitless weighted standard deviation of the fit is 1.6. 46 parameters and 216 lines were identified.

Keywords: CH3COD, torsion, the microwave spectra, far infrared spectra high resolution

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Authors: Hamed Djalal

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The aim of this paper is to perform a thermal-hydraulic analysis of the IAEA 10 MW benchmark reactor solving analytically and numerically, by mean of the finite volume method, respectively the steady state and transient forced convection in rectangular narrow channel between two parallel MTR-type fuel plates, imposed under a cosine shape heat flux. A comparison between both solutions is presented to determine the minimal coolant velocity which can ensure a safe reactor core cooling, where the cladding temperature should not reach a specific safety limit 90 °C. For this purpose, a computer program is developed to determine the principal parameter related to the nuclear core safety, such as the temperature distribution in the fuel plate and in the coolant (light water) as a function of the inlet coolant velocity. Finally, a good agreement is noticed between the both analytical and numerical solutions, where the obtained results are displayed graphically.

Keywords: forced convection, pressure drop, thermal hydraulic analysis, vertical heated rectangular channel

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Mehranoosh Gholipoor

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The effects of planting date on performance and yield components of maize single cross 704 was carried out in 2003.this experiment was designed in randomized complete block pattern with 3 replications in the field of College campus of Agricultural Sciences and Natural Resources in Gorgan. Treatments consisted of four planting dates (May5, May19, June4 and June19) respectively. The results showed that the planting on June4 were the best time for planting date in the field of seed performance and many other measurement qualities while planting date on June19 had the lowest seed performance in corn, due to a severe reduction in seed numbers had the highest In 1000 seed weight. Between the planting date on May 5 and May19 were observed no significant differences

Keywords: corn, planting date, performance and yield components

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Authors: Mai M. Farid, Mona El-Shabrawy, Sameh R. Hussein, Ahmed Elkhateeb, El-Said S. Abdel-Hameed, Mona M. Marzouk

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Asphodelus aestivus Brot. Is a wild plant distributed in Egypt and is considered one of the five Asphodelus spp. from the family Asphodelaceae; it grows in dry grasslands and on rocky or sandy soil. The chemical components of A. aestivus flowers extract were analyzed using different chromatographic and spectral techniques and led to the isolation of two anthraquinones identified as emodin and emodin-O-glucoside. In addition to, five flavonoid compounds;kaempferol,Kaempferol-3-O-glucoside,Apigenin-6-C-glucoside-7-O-glucoside (Saponarine), luteolin 7-O-β-glucopyranoside, Isoorientin-O-malic acid which is a new compound in nature. The LC-ESI-MS/MS analysis of the flower extract of A. aestivus led to the identification of twenty- two compounds characterized by the presence of flavones, flavonols, and flavone C-glycosides. While GC/MS analysis led to the identification of 24 compounds comprising 98.32% of the oil, the major components of the oil were 9, 12, 15-Octadecatrieoic acid methyl ester 28.72%, and 9, 12-Octadecadieroic acid (Z, Z)-methyl ester 19.96%. In vitro cytotoxic activity of the aqueous methanol extract of A. aestivus flowers against HEPG2, HCT-116, MCF-7, and A549 culture was examined and showed moderate inhibition (62.3±1.1)% on HEPG2 cell line followed by (36.8±0.2)% inhibition on HCT-116 and a weak inhibition (5.7± 0.0.2) on MCF-7 cell line followed by (4.5± 0.4) % inhibition on A549 cell line and this is considered the first cytotoxic report of A. aestivus flowers.

Keywords: Anthraquinones, Asphodelus aestivus, Cytotoxic activity, Flavonoids, LC-ESI-MS/MS

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Authors: Jaime E. Fernandez, Pablo J. Valverde

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This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.

Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games

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Authors: Vilma Zydziunaite, Simona Kersiene

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The concept of focused leadership means that the leader gathers the entire community in various ways to communicate and cooperate with each other, to share their knowledge and responsibility, to get involved in problem-solving, to create a safe and trusting environment and to satisfy the needs and interests of each community member. The study's aim is to analyze the teamwork of teachers working in kindergartens and schools and its CEOs by implementing confused leadership. A mixed research design was used for the research study. Quantitative research used the teamwork test "Team-Puls" (2003). Data is processed by the IBM SPSS version 29.0 software package. Semi-structured interviews were used for data collection, and qualitative content analysis was applied for data analysis. The results of quantitative research show that there is no statistically significant difference between the evaluation averages of kindergarten and school teachers. Likewise, the effectiveness and evaluation of teacher teamwork in educational institutions depend on different characteristics and processes, such as the number of participating teachers, the involvement of the institution's administration or the stages of team formation. In the qualitative research, the components of the focused leadership categories applied by the kindergarten and school CEOs emerged. The categories reflect the components of shared leadership. In the study, the sharing of responsibilities and cooperation among teachers and the sharing of knowledge among themselves is distinguished. This shows that the action takes place between the teachers when they participate in the processes voluntarily, according to their wishes or for certain reasons. Distributed leadership components occurs when leadership responsibility is extended beyond the school CEO. The components of servant leadership are expressed when the CEO achieves organizational goals in the service of others. Servant leadership is helping and striving for others, creating a safe environment. The level of the educational institution does not affect working teachers in the evaluation of working in a team. Giving freedom to teachers, the role of the CEO is dividing responsibilities and creating cooperation between teachers as well as ensuring teachers' interests, needs, emotional well-being and professional development.

Keywords: teamwork, school, teacher, school CEO, school environment, mixed research, Team-Puls test, semi-structured interview, questioning survey, qualitative content analysis, focused leadership, teacher leadership

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Authors: Raheela Akhtar, Zafar Iqbal Chaudhary, Yongqun Oliver He, Muhammad Younus, Aftab Ahmad Anjum

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Brucella abortus is an intracellular pathogen affecting macrophages. Macrophages release some components such as lysozymes (LZ), reactive oxygen species (ROS) and reactive nitrite intermediates (RNI) which are important tools against intracellular survival of Brucella. The antibrucella activity of bovine and murine macrophages was compared following stimulation with Brucella abortus lipopolysaccharides. Our results revealed that murine macrophages were ten times more potent to produce antibrucella components than bovine macrophages. The differential production of these components explained the differential Brucella killing ability of these species that was measured in terms of intramacrophagic survival of Brucella in murine and bovine macrophages.

Keywords: bovine macrophages, Brucella abortus, cell stimulation, cytokines, Murine macrophages

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Authors: Abdolamir Gatezadeh, Jamal Daghaleh

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The lifestyle of individuals is important and determinant for the status of psychological and social health. Recently, especially in developed countries, the relationship between lifestyle and mental illnesses, including depression, has attracted the attention of many people. In order to test the causal model of depression based on lifestyle with mediation of social health in the study, basic and applied methods were used in terms of objective and descriptive-field as well as the data collection. Methods: This study is a basic research type and is in the framework of correlational plans. In this study, the population includes all adults in Ahwaz city. A randomized, multistage sampling of 384 subjects was selected as the subjects. Accordingly, the data was collected and analyzed using structural equation modeling. Results: In data analysis, path analysis indicated the confirmation of the assumed model fit of research. This means that subscales lifestyle has a direct effect on depression and subscales lifestyle through the mediation of social health which in turn has an indirect effect on depression. Discussion and conclusion: According to the results of the research, the depression can be used to explain the components of the lifestyle and social health.

Keywords: depression, subscales lifestyle, social health, causal model

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Authors: L. Chevez, A. Apaza, J. Rodriguez, R. Puga, H. Loro, Juan Z. Davalos

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Virtual Dimension (VD) procedure is used to analyze Hyperspectral Image (HIS) treatment-data in order to estimate the abundance of mineral components of a mining sample. Hyperspectral images coming from reflectance spectra (NIR region) are pre-treated using Standard Normal Variance (SNV) and Minimum Noise Fraction (MNF) methodologies. The endmember components are identified by the Simplex Growing Algorithm (SVG) and after adjusted to the reflectance spectra of reference-databases using Simulated Annealing (SA) methodology. The obtained abundance of minerals of the sample studied is very near to the ones obtained using XRD with a total relative error of 2%.

Keywords: hyperspectral imaging, minimum noise fraction, MNF, simplex growing algorithm, SGA, standard normal variance, SNV, virtual dimension, XRD

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Authors: K. Jarmkom, P. Eakwaropas, W. Khobjai, S. Techaeoi

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Ancient Thai perfumed powder was used as a fragrance for clothing, food, and the body. Plant-based natural Thai perfume products are known as Pang-Rum. The objective of this study was to evaluate the stability of essential oils after six months of incubation. The chemical compositions were determined by gas chromatography-mass spectrometry (GC-MS), in terms of the qualitative composition of the isolated essential oil. The isolation of the essential oil of natural products by incubate sample for 5 min at 40 ºC is described. The volatile components were identified by percentage of total peak areas comparing their retention times of GC chromatograph with NIST mass spectral library. The results show no significant difference in the seven chromatograms of perfumed powder (Pang-Rum) both with binder and without binder. Further identification was done by GC-MS. Some components of Pang-Rum with/without binder were changed by temperature and time.

Keywords: GC-MS analysis, essential oils, stability, Pang-Rum

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Authors: Cuong D. Dao, Rob J.I. Basten, Andreas Hartmann

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This paper studies the optimal maintenance planning of preventive maintenance and renewal activities for components in a single railway track when the available time for maintenance is limited. The rail-track system consists of several types of components, such as rail, ballast, and switches with different preventive maintenance and renewal intervals. To perform maintenance or renewal on the track, a train free period for maintenance, called a possession, is required. Since a major possession directly affects the regular train schedule, maintenance and renewal activities are clustered as much as possible. In a highly dense and utilized railway network, the possession time on the track is critical since the demand for train operations is very high and a long possession has a severe impact on the regular train schedule. We present an optimization model and investigate the maintenance schedules with and without the possession capacity constraint. In addition, we also integrate the social-economic cost related to the effects of the maintenance time to the variable possession cost into the optimization model. A numerical example is provided to illustrate the model.

Keywords: rail-track components, maintenance, optimal clustering, possession capacity

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Authors: Bouthiba Amina

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The estimation of the statistics bound to the precipitation represents a vast domain, which puts numerous challenges to meteorologists and hydrologists. Sometimes, it is necessary, to approach in value the extreme events for sites where there is little, or no datum, as well as their periods of return. The search for a model of the frequency of the heights of daily rains dresses a big importance in operational hydrology: It establishes a basis for predicting the frequency and intensity of floods by estimating the amount of precipitation in past years. The most known and the most common approach is the statistical approach, It consists in looking for a law of probability that fits best the values observed by the random variable " daily maximal rain " after a comparison of various laws of probability and methods of estimation by means of tests of adequacy. Therefore, a frequent analysis of the annual series of daily maximal rains was realized on the data of 54 pluviometric stations of the pond of high and average. This choice was concerned with five laws usually applied to the study and the analysis of frequent maximal daily rains. The chosen period is from 1970 to 2013. It was of use to the forecast of quantiles. The used laws are the law generalized by extremes to three components, those of the extreme values to two components (Gumbel and log-normal) in two parameters, the law Pearson typifies III and Log-Pearson III in three parameters. In Algeria, Gumbel's law has been used for a long time to estimate the quantiles of maximum flows. However, and we will check and choose the most reliable law.

Keywords: return period, extreme flow, statistics laws, Gumbel, estimation

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Authors: Ankita Srivastava, Yogesh K. Garg

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Housing provides comforts and well being leading towards the quality of life. Earlier research had established that landscape elements enhance the residents’ quality of life through its significant experiences occur due to their presence in the housing. This paper tries to identify the preference of landscape elements that enhance residents’ quality of life living in the apartment. Hence, landscape elements that can be planned in the open spaces of housing and quality of life components were identified from the secondary data sources. Experts’ were asked to identify the quality of life components with respect to landscape elements. A questionnaire survey of residents’ living in the apartment housing in Bhopal, India was conducted. The statistical analysis of survey data facilitated to explore the preference of landscape elements for the quality of life in the apartment housing. The final ranking compiled from the experts’ opinion, residents’ perception as well as factor analysis results to have an insight of the preference of landscape elements for the quality of life living in the apartment. Preference of landscape elements present in the paper may provide an overview of planning for apartment housing that may be used by architects, planners and developers for enhancing residents’ quality of life.

Keywords: landscape elements, quality of life, residents, housing

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Authors: Rojin Bana Derakhshan, Abbas Toloie

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For the purpose of optimizing and developing energy efficiency in building, it is required to recognize key elements of success in optimization of energy consumption before performing any actions. Surveying Principal Components is one of the most valuable result of Linear Algebra because the simple and non-parametric methods are become confusing. So that energy management system implemented according to energy management system international standard ISO50001:2011 and all energy parameters in building to be measured through performing energy auditing. In this essay by simulating used of data mining, the key impressive elements on energy saving in buildings to be determined. This approach is based on data mining statistical techniques using feature selection method and fuzzy logic and convert data from massive to compressed type and used to increase the selected feature. On the other side, influence portion and amount of each energy consumption elements in energy dissipation in percent are recognized as separated norm while using obtained results from energy auditing and after measurement of all energy consuming parameters and identified variables. Accordingly, energy saving solution divided into 3 categories, low, medium and high expense solutions.

Keywords: energy saving, key elements of success, optimization of energy consumption, data mining

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Authors: Manikandakumar Shunmugavel, Ashwin Polishetty, Moshe Goldberg, Junior Nomani, Guy Littlefair

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Selective laser melting (SLM), a promising additive manufacturing (AM) technology, has a huge potential in the fabrication of Ti-6Al-4V near-net shape components. However, poor surface finish of the components fabricated from this technology requires secondary machining to achieve the desired accuracy and tolerance. Therefore, a systematic understanding of the machinability of SLM fabricated Ti-6Al-4V components is paramount to improve the productivity and product quality. Considering the significance of machining in SLM fabricated Ti-6Al-4V components, this research aim is to study the influence of build orientation on machinability characteristics by performing low speed orthogonal cutting tests. In addition, the machinability of SLM fabricated Ti-6Al-4V is compared with conventionally produced wrought Ti-6Al-4V to understand the influence of SLM technology on machining. This paper is an attempt to provide evidence to the hypothesis associated that build orientation influences cutting forces, chip formation and surface integrity during orthogonal cutting of SLM Ti-6Al-4V samples. Results obtained from the low speed orthogonal cutting tests highlight the practical importance of microstructure and build orientation on machinability of SLM Ti-6Al-4V.

Keywords: additive manufacturing, build orientation, machinability, titanium alloys (Ti-6Al-4V)

Procedia PDF Downloads 283

Authors: T. S. Bubuche, L. Abubakar, N.D. Ibrahim, A. A. Aliero, H. M. Sama, B. S. Haliru

Abstract:

A two-year study was conducted at the Fadama farm of Usmanu Danfodiyo University Sokoto, Nigeria. Correlations and path coefficients analysis were used to determine the interrelationship and importance of various characters as components of yield in sugarcane during 20011-012 and 2012-013 growing seasons. Fourteen sugarcane hybrids and a local check were evaluated. The experiment was laid out in a randomized complete block design (RCBD) and replicated three times. Significant and positive correlation were recorded between total cane weight/ha and single stalk weight, between single stalk weight and final brix and between stalk girth and stalk length while final brix and number of milliable cane/ha recorded no significant correlation. Traits that had high direct contribution to the final yield were number of stalk/stool, number of milliable cane/ha, single stalk weight and brix content while high indirect positive contributions were observed in growth habit, number of internode per stalk and stalk length..

Keywords: correlation, path analysis, sugarcane, yield components

Procedia PDF Downloads 251

Authors: Amrutha Venugopal, Rabee Rustum

Abstract:

In spite of huge investments and the vital role infrastructure plays in the economy of UAE, the country has not yet developed an assessment scheme to measure the sustainability of infrastructure projects/development. The aim of this study was to develop a sustainability rating system for infrastructure projects in UAE using weighted indicator scoring. The identification of the list of 66 indicators was done by content analysis. The sources of content analysis were from government guidelines, research literature and sustainability rating system for infrastructure projects namely BCA Greenmark for Infrastructure (Singapore), ISCA (Australia) and Envision (USA). These indicators were shortlisted based on their relevance in the UAE. A mixture of qualitative and quantitative research methods is utilized to find the weightage to be applied to the indicators and to find suggestive measures to improve infrastructure sustainability in this region. Interviews and surveys were conducted with a good mix of experts from the industry. The data collected from the interviews were collated to provide suggestive measures for improving infrastructure sustainability. The collected survey data were analyzed using statistical analysis techniques to find the indicator weighing. The indicators were shortlisted by 75% to minimize the effort and investment into the process. The weighing of the deleted indicators was distributed among the critical clusters identified by Pareto analysis. Finally a simple Microsoft Excel tool was developed as the rating tool by using the calculated weighing for the indicators.

Keywords: infrastructure, rating system, suggestive measures, sustainability, UAE

Procedia PDF Downloads 305

Authors: Kemal Polat

Abstract:

In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

Procedia PDF Downloads 413

Authors: Gopi Kandaswamy, P. Balamuralidhar

Abstract:

Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

Procedia PDF Downloads 262

Authors: S. M. Al-Salem, G.A. Leeke, H. J. Karam, R. Al-Enzi, A. T. Al-Dhafeeri, J. Wang

Abstract:

Thermogravimetry has been popularized as a thermal characterization technique since the 1950s. It aims at investigating the weight loss against both reaction time and temperature, whilst being able to characterize the evolved gases from the volatile components of the organic material being tested using an appropriate hyphenated analytical technique. In an effort to characterize and identify the reclaimed waste from an unsanitary landfill site, this approach was initiated. Solid waste (SW) reclaimed from an active landfill site in the State of Kuwait was collected and prepared for characterization in accordance with international protocols. The SW was segregated and its major components were identified after washing and air drying. Shredding and cryomilling was conducted on the plastic solid waste (PSW) component to yield a material that is representative for further testing and characterization. The material was subjected to five heating rates (b) with minimal repeatable weight for high accuracy thermogravimetric analysis (TGA) following the recommendation of the International Confederation for Thermal Analysis and Calorimetry (ICTAC). The TGA yielded thermograms that showed an off-set from typical behavior of commercial grade resin which was attributed to contact of material with soil and thermal/photo-degradation.

Keywords: polymer, TGA, pollution, landfill, waste, plastic

Procedia PDF Downloads 129