Search results for: functional principal component analysis

Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

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Substantial research has indicated that socioeconomic and demographic characteristics’ of neighborhoods are strong determinants of food security. The aim of this study was to develop a Food Insecurity Neighborhood Index (FINI) based on the associated socioeconomic and demographic variables to identify the areas at potential risk of food insecurity in rural British Columbia (BC). Principle Component Analysis (PCA) technique was used to calculate the FINI for each rural Dissemination Area (DA) using the food security determinant variables from Canadian Census data. Using ArcGIS, the neighborhoods with the top quartile FINI values were classified as food insecure. The results of this study indicated that the most food insecure neighborhood with the highest FINI value of 99.1 was in the Bulkley-Nechako (central BC) area whereas the lowest FINI with the value of 2.97 was for a rural neighborhood in the Cowichan Valley area. In total, 98.049 (19%) of the rural population of British Columbians reside in high food insecure areas. Moreover, the distribution of food insecure neighborhoods was found to be strongly dependent on the degree of rurality in BC. In conclusion, the cluster of food insecure neighbourhoods was more pronounced in Central Coast, Mount Wadington, Peace River, Kootenay Boundary, and the Alberni-Clayoqout Regional Districts.

Keywords: neighborhood food insecurity index, socioeconomic and demographic determinants, principal component analysis, Canada census, ArcGIS

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Authors: Luciana P. Mazur, Tatiana A. Pozdniakova, Rui A. R. Boaventura, Vitor J. P. Vilar

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The principal mechanism of metal ions sequestration by brown algae involves the formation of complexes between the metal ion and functional groups present on the cell wall of the biological material. To understand the role of functional groups on copper(II) uptake by Ascophyllum nodosum, some functional groups were chemically modified. The esterification of carboxylic groups was carried out by suspending the biomass in a methanol/HCl solution under stirring for 48 h and the blocking of the sulfonic groups was performed by repeating the same procedure for 4 cycles of 48 h. The methylation of amines was conducted by suspending the biomass in a formaldehyde/formic acid solution under shaking for 6 h and the chemical modification of sulfhydryl groups on the biomass surface was achieved using dithiodipyridine for 1 h. Equilibrium sorption studies for Cu2+ using the raw and esterified algae were performed at pH 2.0 and 4.0. The experiments were performed using an initial copper concentration of 300 mg/L and algae dose of 1.0 g/L. After reaching the equilibrium, the metal in solution was quantified by atomic absorption spectrometry. The biological material was analyzed by Fourier Transform Infrared Spectroscopy and Potentiometric Titration techniques for functional groups identification and quantification, respectively. The results using unmodified algae showed that the maximum copper uptake capacity at pH 4.0 and 2.0 was 1.17 and 0.52 mmol/g, respectively. At acidic pH values most carboxyl groups are protonated and copper sorption suffered a significant reduction of 56%. Blocking the carboxylic, sulfonic, amines and sulfhydryl functional groups, copper uptake decreased by 24/26%, 69/81%, 1/23% and 40/27% at pH 2.0/4.0, respectively, when compared to the unmodified biomass. It was possible to conclude that the carboxylic and sulfonic groups are the main functional groups responsible for copper binding (>80%). This result is supported by the fact that the adsorption capacity is directly related to the presence of carboxylic groups of the alginate polymer, and the second most abundant acidic functional group in brown algae is the sulfonic acid of fucoidan that contributes, to a lower extent, to heavy metal binding, particularly at low pH.

Keywords: biosorption, brown marine macroalgae, copper, ion-exchange

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Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

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Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Murada Alholy, Mengshi Lin, Omar Alhaj, Mahmoud Abugoush

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Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between four Alicyclobacillus strains and four Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm-1 reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (e.g. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA)) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these two genera.

Keywords: alicyclobacillus, bacillus, FT-IR, spectroscopy, PCA

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Authors: Aiman Mazhar Qureshi, Ahmed Rachid

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Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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Authors: Rajeshwar Singh

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The presence of multicollinearity is common in handling with several explanatory variables simultaneously due to exhibiting a linear relationship among them. A great problem arises in understanding the impact of explanatory variables on the dependent variable. Thus, the method of least squares estimation gives inexact estimates. In this case, it is advised to detect its presence first before proceeding further. Using the ridge regression degree of its occurrence is reduced but principal components regression gives good estimates in this situation. This paper discusses well-known techniques of the ridge and principal components regressions and applies to get the estimates of coefficients by both techniques. In addition to it, this paper also discusses the conflicting claim on the discovery of the method of ridge regression based on available documents.

Keywords: conflicting claim on credit of discovery of ridge regression, multicollinearity, principal components and ridge regressions, variance inflation factor

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Authors: Slavka Zeković, Miodrag Vujošević, Tamara Maričić

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The paper provides a comprehensive analysis of the sustainable development in the Belgrade Metropolitan Region - BMA (level NUTS 2) preliminary evaluating the three chosen components: 1) economic growth and developmental changes; 2) competitiveness; and 3) territorial concentration and industrial specialization. First, we identified the main results of development changes and economic growth by applying Shift-share analysis on the metropolitan level. Second, the empirical evaluation of competitiveness in the BMA is based on the analysis of absolute and relative values of eight indicators by Spider method. Paper shows that the consideration of the national share, industrial mix and metropolitan/regional share in total Shift share of the BMA, as well as economic/functional specialization of the BMA indicate very strong process of deindustrialization. Allocative component of the BMA economic growth has positive value, reflecting the above-average sector productivity compared to the national average. Third, the important positive role of metropolitan/regional component in decomposition of the BMA economic growth is highlighted as one of the key results. Finally, comparative analysis of the industrial territorial concentration in the BMA in relation to Serbia is based on location quotient (LQ) or Balassa index as a valid measure. The results indicate absolute and relative differences in decrease of industry territorial concentration as well as inefficiency of utilizing territorial capital in the BMA. Results are important for the increase of regional competitiveness and territorial distribution in this area as well as for improvement of sustainable metropolitan and sector policies, planning and governance on this level.

Keywords: Belgrade Metropolitan Area (BMA), comprehensive analysis / evaluation, economic growth, competitiveness, sustainable development

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Authors: E. Grochowska-Niedworok, K. Brukało, M. Kardas

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The aim of this study was to analyze and evaluate the consumption of functional food by consumers by: age, sex, formal education level, place of residence and diagnosed diseases. The study employed an ad hoc questionnaire in a group of 300 inhabitants of Upper Silesia voivodship. Knowledge of functional food among the group covered in the study was far from satisfactory. The choice of functional food was of intuitive character. In addition, the group covered was more likely to choose pharmacotherapy instead of diet-related prevention then, which can be associated with presumption of too distant effects and a long period of treatment.

Keywords: consumer choice, functional food, healthy lifestyle, consumer knowledge

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Authors: Chaiyaset Promsri

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Based on the synthesis of related literatures, this research found thirteen related dimensions that involved the development of natural disaster preparedness awareness including hazard knowledge, hazard attitude, training for disaster preparedness, rehearsal and practice for disaster preparedness, cultural development for preparedness, public relations and communication, storytelling, disaster awareness game, simulation, past experience to natural disaster, information sharing with family members, and commitment to the community (time of living).  The 40-item of natural disaster preparedness awareness questionnaire was developed based on these thirteen dimensions. Data were collected from 595 participants in Bangkok metropolitan and vicinity. Cronbach's alpha was used to examine the internal consistency for this instrument. Reliability coefficient was 97, which was highly acceptable.  Exploratory Factor Analysis where principal axis factor analysis was employed. The Kaiser-Meyer-Olkin index of sampling adequacy was .973, indicating that the data represented a homogeneous collection of variables suitable for factor analysis. Bartlett's test of Sphericity was significant for the sample as Chi-Square = 23168.657, df = 780, and p-value < .0001, which indicated that the set of correlations in the correlation matrix was significantly different and acceptable for utilizing EFA. Factor extraction was done to determine the number of factors by using principal component analysis and varimax.  The result revealed that four factors had Eigen value greater than 1 with more than 60% cumulative of variance. Factor #1 had Eigen value of 22.270, and factor loadings ranged from 0.626-0.760. This factor was named as "Knowledge and Attitude of Natural Disaster Preparedness".  Factor #2 had Eigen value of 2.491, and factor loadings ranged from 0.596-0.696. This factor was named as "Training and Development". Factor #3 had Eigen value of 1.821, and factor loadings ranged from 0.643-0.777. This factor was named as "Building Experiences about Disaster Preparedness".  Factor #4 had Eigen value of 1.365, and factor loadings ranged from 0.657-0.760. This was named as "Family and Community". The results of this study provided support for the reliability and construct validity of natural disaster preparedness awareness for utilizing with populations similar to sample employed.

Keywords: natural disaster, disaster preparedness, disaster awareness, Thai citizens

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Authors: Olakunle Moses Makanjuola, Adebola Ajayi

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Noodles are made from unleavened dough, rolled flat and cut into shapes. The instant noodle market is growing fast in Asian countries and is gaining popularity in the western market. This project reports on the proximate functional and sensory evaluation of different brands of instant noodles in Nigeria. The comparisons were based on proximate functional and sensory evaluation of the product. The result obtained from the proximate analysis showed that sample QHR has the highest moisture content, sample BMG has the highest protein content, sample CPO has the highest fat content, sample. The obtained result from the functional properties showed that sample BMG (Dangote noodles) had the highest volume increase after cooking due to its high swelling capacity, high water absorption capacity and high hydration capacity. Sample sensory analysis of the noodles showed that all the samples are of significant difference (at P < 0.05) in terms of colour, texture, and aroma but there is no significant difference in terms of taste and overall acceptability. Sample QHR (Indomie noodles) is the most preferred by the panelists.

Keywords: proximate, functional, sensory evaluation, noodles

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: Mahdiyeh Abbasi, Akbar Golchin

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It is well-known that, using principal weak flatness property, some important monoids are characterized, such as regular monoids, left almost regular monoids, and so on. In this article, we define a generalization of principal weak flatness called GP-Flatness, and will characterize monoids by this property of their right (Rees factor) acts. Also we investigate new classes of monoids called generally regular monoids and generally left almost regular monoids.

Keywords: G-left stabilizing, GP-flatness, generally regular, principal weak flatness

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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: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

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Authors: Doroteya K. Staykova, Dirk J. Lefeber, Sabine A. Fuchs, Judith J. M. Jans

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Cholestasis is characterized by the accumulation of toxic bile salts and lipids in the organism. The variety in causes (genetic, immunologic, environmental) and nature (benign, transient, chronic, progressive) combined with the need for early diagnosis and rapid clinical decisions emphasizes the need for good diagnostic strategies to improve patient outcomes. In a current diagnostic analysis of cholestasis, mass-spectrometry metabolomics is a widely adopted tool to enhance clinical decisions at point-of-care, thanks to a short turnaround in measurement times while performing comprehensive molecular profiling of patient material. However, this comes at the cost of difficult-to-identify yet actionable knowledge, often buried within large and heterogenous omics data. Here, we demonstrate how topological data analysis can overcome this challenge in large metabolomics datasets of patients with twenty categories of Metabolic Disorders and overlapping clinical manifestations. To elucidate the complexity of disease progression in three cholestasis patients, we applied topological data analysis to direct-infusion mass spectrometry data collected from 190 plasma samples, including 67 controls, at the University Medical Center in Utrecht, Netherlands. Using the Mapper algorithm and filter function defined as a two-component projection based on Principal Component Analysis, we constructed a topological graph of connected patients, termed a Patient Connectivity Network (PCN). With incorporated clinical and molecular information, PCN revealed the topological shape of causes and severity of cholestasis and transitions in patients’ conditions. In conclusion, topology based PCN provides a holistic view of cholestasis state dynamics that has the potential to support and expedite clinical decisions.

Keywords: mass spectrometry-based metabolomics, patient connectivity network, topological data analysis, unmet clinical needs in Cholestasis

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Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

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We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.

Keywords: crater detection, PCA, FPGA, image processing

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Authors: Aparna Radhakrishnan, Jancy Gupta, R. Dileepkumar

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This paper aims at assessing the Socio Economic Vulnerability (SEV) of dairy farmers to Climate Variability and Change (CVC) in 3 states of Western Ghat region in India. For this purpose, a composite SEV index has been developed on the basis of functional relationships amongst sensitivity, exposure and adaptive capacity using 30 indicators related to dairy farming underlying the principles of Intergovernmental Panel on Climate Change and Fussel framework for nomenclature of vulnerable situation. Household level data were collected through Participatory Rural Appraisal and personal interviews of 540 dairy farmers of nine taluks, three each from a district selected from Kerala, Karnataka and Maharashtra, complemented by thirty years of gridded weather data. The data were normalized and then combined into three indices for sensitivity, exposure and adaptive capacity, which were then averaged with weights given using principal component analysis, to obtain the overall SEV index. Results indicated that the taluks of Western Ghats are vulnerable to CVC. The dairy farmers of Pulpally taluka were most vulnerable having the SEV score +1.24 and 42.66% farmers under high-level vulnerability category. Even though the taluks are geographically closer, there is wide variation in SEV components. Policies for incentivizing the ‘climate risk adaptation’ costs for small and marginal farmers and livelihood infrastructure for mitigating risks and promoting grass root level innovations are necessary to sustain dairy farming of the region.

Keywords: climate change, dairy, vulnerability, livelihoods, adaptation strategies

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Authors: Neda Lovričević, Đilda Pečarić, Josip Pečarić

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The Jensen functional in its discrete form is brought in relation to the Csiszar divergence functional, this time via its monotonicity property. This approach presents a generalization of the previously obtained results that made use of interpolating Jensen-type inequalities. Thus the monotonicity property is integrated with the Zipf-Mandelbrot law and applied to f-divergences for probability distributions that originate from the Csiszar divergence functional: Kullback-Leibler divergence, Hellinger distance, Bhattacharyya distance, chi-square divergence, total variation distance. The Zipf-Mandelbrot and the Zipf law are widely used in various scientific fields and interdisciplinary and here the focus is on the aspect of the mathematical inequalities.

Keywords: Jensen functional, monotonicity, Csiszar divergence functional, f-divergences, Zipf-Mandelbrot law

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Authors: Stephanie K. Douglas, Gordon R. Haley

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Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

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Authors: Francis Angelo A. Sta. Ana

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Heavy metal pollutants are a major environmental concern in built-up areas in the Philippines. It causes negative effects on aquatic organisms and human health. Heavy metals concentrations of chromium, mercury, lead, copper, arsenic, zinc, cadmium, and nickel were investigated in Sta. Maria river, in Laguna. A total of 16 sediment samples were collected from the river at four stations. Atomic absorption spectroscopy (AAS) was used for element detection. It is found that copper is associated with chromium based on statistical analysis using principal component analysis (PCA). Conduct of Sediment Quality Guideline (SQG) revealed that chromium has high toxicity due to values higher than Sediment Quality Guidelines Probable Effect Level (SQG’s PEL). Copper, Nickel, and Pb fall on average toxicity while others are below PEL and effect range low (ERL).

Keywords: heavy metals, pollutants, sediment quality guidelines, atomic absorption spectroscopy

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Authors: Mouna Mesbahi, M. Loutfi Benkhedir

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In CZTS films solar cell, the preferable reaction between Cu and sulfur vapor was likely to be induced by out diffusion of the bottom Cu component to the surface; this would lead to inhomogeneous distribution of the Cu component to form the Cu2SnS3 secondary phase and formation of many voids and crevices in the resulting CZTS film; which is also the cause of the decline in performance. In this work we study the electronic and optical properties of Cu2SnS3. For this purpose we used the Wien2k code based on the theory of density functional theory (DFT) with the modified Becke-Johnson exchange potential mBJ and the Hubbard potential individually or combined. We have found an energy gap 0.92 eV. The results are in good agreement with experimental results.

Keywords: Cu2SnS3, DFT, electronic and optical properties, mBJ+U, WIEN2K

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Authors: Saba Ebrahimi, Hedieh Ashrafi

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Predicting the cover type of forests is a challenge for natural resource managers. In this project, we aim to perform a comprehensive comparative study of two well-known classification methods, support vector machine (SVM) and decision tree (DT). The comparison is first performed among different types of each classifier, and then the best of each classifier will be compared by considering different evaluation metrics. The effect of boosting and bagging for decision trees is also explored. Furthermore, the effect of principal component analysis (PCA) and feature selection is also investigated. During the project, the forest cover-type dataset from the remote sensing and GIS program is used in all computations.

Keywords: classification methods, support vector machine, decision tree, forest cover-type dataset

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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: Renate Krassnig, Gloria M. Hohenberger, Uldis Berzins, Stefen Fischerauer

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Background: Only a few reports discuss the effectiveness of intraoperative radiographs for placing femoral components. Therefore there is no international standard in using intraoperative imaging in the proceeding of total hip replacement. Method: Case report; an 84-year-old female patient underwent changing the components of the Total hip arthroplasty (THA) because of aseptic loosening. Due to circumstances, the surgeon decided to implant a cemented femoral component. The procedure was without any significant abnormalities. The first postoperative radiograph was planned after recovery – as usual. The x-ray imaging showed a misplaced femoral component. Therefore a CT-scan was performed additionally and the malposition of the cemented femoral component was confirmed. The patient had to undergo another surgery – removing of the cemented femoral component and implantation of a new well placed one. Conclusion: Intraoperative imaging of the femoral component is not a common standard but this case shows that intraoperative imaging is a useful method for detecting errors and gives the surgeon the opportunity to correct errors intraoperatively.

Keywords: femoral component, intraoperative imaging, malplacement, revison

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Mirjana Ilic, Dragan Zivotic, Aleksandra Perovic, Predrag Gavrilovic

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The service quality perception depends on many factors, such as the area in which the services are provided, socioeconomic status, educational status, experience, age and gender of consumers, as well as many others. For this reason, it is not possible to apply instrument for establishing the service quality perception that is developed in other areas and in other populations. The aim of the research was to form an instrument for assessing the quality perception in the field of fitness in Serbia. After analyzing the available literature and conducting a pilot research, there were 15 isolated areas in which it was possible to observe the service quality perception. The areas included: material and technical basis, secondary facilities, coaches, programs, reliability, credibility, security, rapid response, compassion, communication, prices, satisfaction, loyalty, quality outcomes and motives. These areas were covered by a questionnaire consisted of 100 items where the number of items varied from area to area from 3 up to 11. The questionnaire was administered to 350 subjects of both genders (174 men and 176 women) aged from 18 to 68 years, being beneficiaries of fitness services for at least 1 year. In each of the areas was conducted a factor analysis in its exploratory form by principal components method. The number of significant factors has been determined in accordance with the Kaiser Guttman criterion. The initial factor solutions were simplified using the Varimax rotation. Analyses per areas have produced from 1 to 4 factors. Afterward, the factor analysis of factor scores on the first principal component of each of the respondents in each of the analyzed area was performed, and the factor structure was obtained with four latent dimensions interpreted as offer, the relationship with the coaches, the experience of quality and the initial impression. This factor structure was analysed by hierarchical analysis of Oblique factors, which in the second order space produced single factor interpreted as a general factor of the service quality perception. The resulting questionnaire represents an instrument which can serve managers in the field of fitness to optimize the centers development, raising the quality of services in line with consumers needs and expectations.

Keywords: fitness, hierarchical model, quality perception, factor analysis

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Authors: Maximilian Winkens, Matthias Goerke

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The state-oriented maintenance enables the preventive intervention before the failure of a component and guarantees avoidance of expensive breakdowns. Because the timing of the maintenance is defined by the component’s state, the remaining service life can be exhausted to the limit. The basic requirement for the state-oriented maintenance is the ability to define the component’s state. New potential for this is offered by gentelligent components. They are developed at the Corporative Research Centre 653 of the German Research Foundation (DFG). Because of their sensory ability they enable the registration of stresses during the component’s use. The data is gathered and evaluated. The methodology developed determines the current state of the gentelligent component based on the gathered data. This article presents this methodology as well as current research. The main focus of the current scientific work is to improve the quality of the state determination based on the life-cycle data analysis. The methodology developed until now evaluates the data of the usage phase and based on it predicts the timing of the gentelligent component’s failure. The real failure timing though, deviate from the predicted one because the effects from the production phase aren’t considered. The goal of the current research is to develop a methodology for state determination which considers both production and usage data.

Keywords: state-oriented maintenance, life-cycle data, gentelligent component, preventive intervention

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Authors: Rosa Alin Cristian

Abstract:

As in any other sports branch, there is also a relationship of dependence between the motor qualities and the technical skills in the sports dance, in the sense that superior performances from a technical, artistic point of view can be obtained only on the basis of a certain level of motor qualities and of the morphological and functional indices of the organism. Starting from the premise that physical training is a basic component of the dancers' training process, determining the efficacy and efficiency of the athletes in training and competitions, its main objectives are to obtain an optimal functional capacity of the body, which is reached through a superior level of development and manifestation of the basic and specific motor qualities, through appropriate values of the morph-functional indices, all against the background of a perfect state of health. We propose in this paper to create an inventory of the motor qualities specific to the sports dance, of their forms of manifestation, to establish some methodical priorities for their development, in order to support the specialists in their attempt to approach the physical training in the most rigorous and efficient way, according to the characteristics of each age category.

Keywords: physical training, motor skills, sports dance, performance

Procedia PDF Downloads 48