Academic literature on the topic 'Ordered Cluster Sampling'
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Journal articles on the topic "Ordered Cluster Sampling"
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Barua, Prabal, and Syed Hafizur Rahman. "LIVELIHOOD SECURITY DETERMINANTS OF THE ORGANIC FARM HOUSEHOLD IN SOUTH-EASTERN COAST OF BANGLADESH." Food & Agribusiness Management 2, no. 1 (November 13, 2020): 01–05. http://dx.doi.org/10.26480/fabm.01.2021.01.05.
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Organic farming is a method of crop and livestock production that that sustains the demands of production of healthy and safe food for the community. Bangladesh is now highly productive area for agriculture production in the world with large varieties of agriculture crops are vultivating here. The study employed ordered logistic regression to assessed the determinants of livelihood security of the organic farm households in the south-eastern coast of Bangladesh. The study was conducted in three upazilas of Chattogram district like Banskhali, Anwara and Sitakund. Multistage sampling technique was adopted for the study. Three upazilas were selected and from each selected upazila a cluster of 1-2 villages were selected at random. At the last stage 150 respondents were selected from a cluster of villages using random proportional sampling. Ordered logistic regression was applied to assess the determinants of the livelihood security. Landholding, distance access to market, possession of livestock were the significant determinants of livelihood security for the organic farm households in South-eastern coast of Bangladesh . Livelihood security of the organic farm households in coastal Bangladesh was influenced significantly by the determinants like landholding, access to market distance and possession of livestock.
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Pallanca, Cristina, Silvia Leanza, Francesco R. Ferraro, Barbara Lanzoni, Emanuele Dalessandro, Mario Cadelano, Enrico Vesperini, et al. "Internal Kinematics and Structure of the Bulge Globular Cluster NGC 6569 ∗." Astrophysical Journal 950, no. 2 (June 1, 2023): 138. http://dx.doi.org/10.3847/1538-4357/accce9.
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Abstract In the context of a project aimed at characterizing the properties of star clusters in the Galactic bulge, here we present the determination of the internal kinematics and structure of the massive globular cluster NGC 6569. The kinematics has been studied by means of an unprecedented spectroscopic data set acquired in the context of the ESO-VLT Multi-Instrument Kinematic Survey of Galactic globular clusters, combining the observations from four different spectrographs. We measured the line-of-sight velocity of a sample of almost 1300 stars distributed between ∼0.″8 and 770″ from the cluster center. From a subsample of high-quality measures, we determined the velocity dispersion profile of the system over its entire radial extension (from ∼5″ to ∼200″ from the center), finding the characteristic behavior usually observed in globular clusters, with a constant inner plateau and a declining trend at larger radii. The projected density profile of the cluster has been obtained from resolved star counts, by combining high-resolution photometric data in the center, and the Gaia EDR3 catalog radially extended out to ∼ 20 ′ for a proper sampling of the Galactic field background. The two profiles are properly reproduced by the same King model, from which we estimated updated values of the central velocity dispersion, main structural parameters (such as the King concentration, the core, half mass, and tidal radii), total mass, and relaxation times. Our analysis also reveals a hint of ordered rotation in an intermediate region of the cluster (40″ < r < 90″, corresponding to 2r c < r < 4.5r c ), but additional data are required to properly assess this possibility.
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Treml, Leonardo De Marino, Anadia Cattarin, Renato Marques, Franklin Galvão, Lucas Batista Crivellari, and Vinicius Morais Coutinho. "FLORISTIC SIMILARITY IN A FOREST-SAVANNAH ECOTONE IN WESTERN BAHIA STATE, BRAZIL." FLORESTA 52, no. 4 (October 7, 2022): 475. http://dx.doi.org/10.5380/rf.v52i4.80286.
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This study aimed to generate knowledge about transition areas between phytophysiognomies for the understanding and conservation of these unique environments. Thus, the existence of different floristic groups was analyzed in a spatial gradient of an ecotone in the municipality of São Desidério, state of Bahia, Brazil. To this end, a transect of approximately 4.7 km, with orientation from Northeast to Southwest, was established along a spatial gradient. Twelve (12) 10x50 m sampling plots (500 m² each) were distributed throughout this transect. The following methodology was employed: First, the floristic similarity between the sampling plots was measured. These sampling plots were then grouped and the data were graphically presented in a dendrogram (Cluster analysis) and an ordering diagram (nMDS). Finally, the phytosociological parameters by ordered group were obtained. The results showed the presence of three floristic groups: Groups I, II and III, classified as wooded savannah, seasonal deciduous forest, and forested savannah, respectively. The floristic groups were formed gradually along the spatial gradient, and transition between phytophysiognomies does not occur abruptly, since the ordering by groups is more due to the difference between the abundance of species than to their presence and/or absence. The distribution pattern of the phytophysiognomies along the spatial gradient indicates association with abiotic factors, such as the pedological characteristics and the relief found along the transect, possibly creating an environmental gradient.
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Rabbi, Mohammad Fazle, Judit Oláh, József Popp, Domicián Máté, and Sándor Kovács. "Food Security and the COVID-19 Crisis from a Consumer Buying Behaviour Perspective—The Case of Bangladesh." Foods 10, no. 12 (December 10, 2021): 3073. http://dx.doi.org/10.3390/foods10123073.
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Since COVID-19 was confirmed in Bangladesh in March 2020, the government have enacted stringent measures to prevent the spread of the coronavirus, which has had a significant impact on people’s lives. Food consumption habits of consumers have shifted as a result of declining grocery shopping frequency, negative income shock, and food prices shooting up. This paper aims to explore Bangladeshi consumers’ buying behaviour in association with the stress generated from a food supply shortage during the COVID-19 pandemic and the post-outbreak perception of the food industry, using a dataset with 540 online samples collected between July and August 2021. A two-stage cluster sampling method and self-administrated questionnaire techniques were adopted for collecting the data during the third wave of COVID-19. Using partial least squares path modelling (PLS-PM) and multivariate multiple ordered logit regression (MVORD) to reveal the pertinent structure between all the blocks, this study provides two key findings. First, a higher intensity of COVID-19 impact translates into higher food stress associated with income reduction and higher food prices. Second, food stress directly affects consumer buying and consumption behaviour. We strongly recommend connecting consumers with local producers and collective use of shared warehouses through institutions, policies, and reforms to prevent disruption in the food supply chain and to keep food prices stable. Additionally, food producers, distributors, stakeholders, and policy planners should strengthen the food supply chain to stabilize food security.
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Bernacki, Katarzyna, Chakrapani Kalyanaraman, and Matthew P. Jacobson. "Virtual Ligand Screening against Escherichia coli Dihydrofolate Reductase: Improving Docking Enrichment Using Physics-Based Methods." Journal of Biomolecular Screening 10, no. 7 (September 16, 2005): 675–81. http://dx.doi.org/10.1177/1087057105281220.
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Motivated by their participation in the McMaster Data-Mining and Docking Competition, the authors developed 2 new computational technologies and applied them to docking against Escherichia coli dihydrofolate reductase: a receptor preparation procedure that incorporates rotamer optimization of side chains and a physics-based rescoring procedure for estimating relative binding affinities of the protein-ligand complexes. Both methods use the same energy function, consisting of the all-atom OPLS-AA force field and a generalized Born solvent model, which treats the protein receptor and small-molecule ligands in a consistent manner. Thus, the energy function is similar to that used in more sophisticated approaches, such as free-energy perturbation and the molecular mechanics Poisson-Boltzmann/surface area, but sampling during the rescoring procedure is limited to simple energy minimization of the ligand. The use of a highly efficient minimization algorithm permitted the authors to apply this rescoring procedure to hundreds of thousands of protein-ligand complexes during the competition, using a modest Linux cluster. To test these methods, they used the 12 competitive inhibitors identified in the training set, plus methotrexate, as positive controls in enrichment studies with both the training and test sets, each containing 50,000 compounds. The key conclusion is that combining the receptor preparation and rescoring methods makes it possible to identify most of the positive controls within the top few tenths of a percent of the rank-ordered training and test set libraries.
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Zakka, Kaku, and Romy O. Okoye. "COMPARISON OF RELIABILITY COEFFICIENTS OF TESTS CONSTRUCTED USING DIFFERENT ORDERINGS OF DIFFICULTY OF TEST ITEMS." International Journal of Education and Social Science Research 06, no. 03 (2023): 248–55. http://dx.doi.org/10.37500/ijessr.2023.6321.
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The study compared reliability coefficients of tests constructed using different orderings of difficulties of test items for English language and Mathematics in the North-East, Nigeria. Experimental research design was adopted. The population of the study comprised all the 5,403 JSS 3 students of 2021/2022 academic session in the fifteen Unity schools of the zone. The sample used for experimental study consisted of three hundred and seventy-five students obtained through a combination of multi-stage and cluster sampling techniques. Two instruments (one for each of the subjects) were used for the study. Each instrument was prepared in three different formats, titled: Mathematic Achievement Test and English Language Achievement Test. Each format of the instruments was subjected to test-retest reliability. Method of data analysis was Pearson Product Moment Correlation coefficient (PPMC). The reliability estimate that were obtained from the mathematics multiple-choice questions are as follows: FORMAT ETD (0.512), DTE (0.849) and MDI (0.718). The reliability estimate that were obtained from the English language multiple-choice questions are as follows: FORMAT ETD ETD (0.728), DTE (0.669) and MDI (0.877). The study recommends that for English Language, items ordered from easy to difficult format should be used when constructing test items; since it was the one that had the highest reliability coefficient; for Mathematics items format from difficulty to easy should be used since it has the highest reliability coefficient among the test items format.
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Harsej, Zahra, Nasrin Mokhtari Lakeh, Farzaneh Sheikholeslami, and Ehsan KazemnezhadLeili. "Internet Addiction and Its Relationship with Family Functioning in High School Students." Journal of Holistic Nursing And Midwifery 31, no. 1 (January 1, 2021): 44–52. http://dx.doi.org/10.32598/jhnm.31.1.2025.
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Introduction: Family-related factors play an important role in adolescent’s addiction to the Internet. Objective: The aim of this study was to examine the relationship between Internet addiction and family functioning in high school students. Materials and Methods: This is an analytical study with a cross-sectional design conducted on 796 high school students in Rasht city, Iran who were selected using multi-stage cluster random sampling method. Data collection tools were a demographic form, the Young’s Internet Addiction Test, and the Family Assessment Device. Chi-Square test and rank-ordered logistic regression analysis were used for data analysis. Results:The response rate of of students was 86.81%; 85.7% had at least two family members who were using the Internet; 71.2% of students had no addiction, 27.5% were exposed to Internet addiction and 1.3% had Internet addiction. The majority (65.0%) of studnets had unhealthy family functioning. The relationship between Internet addiction and family functioning was statistically significant (P=0,001). There was a significant statistical relationship between Internet addiction and family income (P= 0.003), fatherchr('39')s job (P=0.001), and duartion of internet usage per day (P=0.001). Logistic regression model showed that the family functioning score (OR=1.02, 95% CI;1.01-1.04, P=0.001), duration of Internet usage per day (OR=1.02, 95% CI;1.11-1.20, P=0.0001), and gender (male) (OR=1.02, 95% CI;1.26-2.58, P=0.001) significantly affected Internet addiction. Conclusion:Due to the direct statistical relationship between Internet addiction and family functioning, it is necessary to pay serious attention to the phenomenon of Internet addiction and make appropriate plans for adolescents and their families to use the Internet properly.
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Kaveh, Sepideh, Abbas Assari Arani, Sajjad Faraji Dizaji, and Seyed Hasan Hoseini. "Determinants of Subjective Well-being: Do we Really Know What Makes People Happy? A Study on Rasht Metropolis, North of Iran." Journal of Research & Health 11, no. 1 (February 1, 2021): 11–20. http://dx.doi.org/10.32598/jrh.11.1.1691.1.
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Background: Background: Recently, along with traditional economic indicators, policymakers are increasingly dealing with Subjective Well-Being (SWB) as an evaluation criterion of their performance and as an index for the population’s psychology health. This was done to define different determinants of SWB with a focus on some specific aspects of the living area. Also, this article investigateed the effect of urban and outskirts area on SWB. Method: This study is a cross-sectional study based on a structured interview and the samples (219 people ) were selected by a two-stage cluster sampling method in 2018 in Rasht city, a metropolis in Iran. In designing the local questionnaire, Gallup’s Global Emotions questionnaire has been used. Two main contributions of this study are defining culturized and proper indices for measuring SWB, and the financial status of people while Iranian people used to understate their real income. Data analysis was conducted using STATA 14.2 applying Descriptive statistics, Correlation study, Ordered Probit regression Method. Results: Results show that improving the socio-economic status of people improve SWB. Having financial satisfaction, satisfaction with leaving area, being tenure, and living in more spacious residency have positive effects on SWB. Also, the city dwellers were found to have higher SWB (5.23 out of 7) than outskirt dwellers (4.9 out of 7) while keeping the other factors to be constant. They reported the same differences in positive feelings and negative feelings indices. Conclusion: The welfare policies should be revised to improve the financial status of all people, and increase the access to urban facilities for outskirts’ dwellers.Determinants of Subjective Well-being: Do we Really Know What Makes People Happy? A Study on Rasht Metropolis, North of Iran
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Bergendahl, M., A. Iranmanesh, W. S. Evans, and J. D. Veldhuis. "Short-Term Fasting Selectively Suppresses Leptin Pulse Mass and 24-Hour Rhythmic Leptin Release in Healthy Midluteal Phase Women without Disturbing Leptin Pulse Frequency or Its Entropy Control (Pattern Orderliness)1." Journal of Clinical Endocrinology & Metabolism 85, no. 1 (January 1, 2000): 207–13. http://dx.doi.org/10.1210/jcem.85.1.6325.
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Nutritional signals strongly regulate neuroendocrine axes, such as those subserving release of LH, GH, and TSH, presumptively in part via the adipocyte-derived neuroactive peptide leptin. In turn, leptin release is controlled by both acute (fasting) and long-term (adipose store) nutrient status. Here, we investigate the neuroendocrine impact of short-term (2.5-day) fasting on leptin release in healthy young women studied in the steroid-replete midluteal phase of the normal menstrual cycle. Eight women each underwent 24-h blood sampling at 10-min intervals during a randomly ordered 2.5-day fasting vs. fed session in separate menstrual cycles. Pulsatile leptin release was quantified by model-free Cluster analysis, the orderliness of leptin patterns by the approximate entropy statistic, and nyctohemeral leptin rhythmicity by cosinor analysis. Mean (24-h) serum leptin concentrations fell by 4.6-fold during fasting; namely, from 15.2 ± 2.3 to 3.4 ± 0.6 μg/L (P= 0.0007). Cluster analysis identified 13.9 ± 1.1 and 14.3± 1.1 leptin peaks per 24 h in the fed and fasting states (P = NS), and unchanging leptin interpeak intervals (89 ± 5.4 vs. 92 ± 5.3 min). Leptin peak area declined by 4.2-fold (155 ± 21 vs. 37 ± 7 area units, P = 0.004), due to a reduction in incremental leptin pulse amplitude (4.4 ± 0.7 vs. 1.0 ± 0.13 μg/L, P = 0.0011). The cosine amplitude and mesor (mean) of the 24-h leptin rhythm decreased by 4-fold, whereas the acrophase (timing of the nyctohemeral leptin peak) remained fixed. The approximate entropy of leptin release was stable, thus indicating preserved orderliness of leptin release patterns in fasting. Cross-correlation analysis revealed both positive (fed) and negative (fasting) leptin-GH relationships, but no leptin-LH correlations. In summary, short-term (2.5-day) fasting profoundly suppresses 24-h serum leptin concentrations and pulsatile leptin release in the sex steroid-sufficient midluteal phase of healthy women via mechanisms that selectively attenuate leptin pulse area and incremental amplitude. In contrast, the pulse-generating, nyctohemeral phase-determining, and entropy-control mechanisms that govern 24-h leptin release are not altered by acute nutrient restriction at this menstrual phase. Leptin-GH (but not leptin-LH) showed nutrient-dependent positive (fed) and negative (fasting) cross-correlations. Whether similar neuroendocrine mechanisms supervise altered leptin signaling during short-term nutrient restriction in men, children, or postmenopausal women is not known.
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Marwiya, Arfatul, Zulkifli Zulkifli, Sugito Sugito, and Muslim Muslim. "ANALISIS ESTETIS KARYA KERAJINAN KAIN PERCA SISWA KELAS VII SMP NEGERI 1 BERINGIN KABUPATEN DELI SERDANG." Gorga : Jurnal Seni Rupa 7, no. 2 (December 30, 2018): 267. http://dx.doi.org/10.24114/gr.v7i2.11894.
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AbstrakPenelitian ini bertujuan untuk meningkatkan hasil belajar siswa pada pelajaran prakarya, khususnya pada materi pelajaran kerajinan limbah kain perca dan mengetahui pemanfaatan limbah kain perca menjadi produk kerajinan tangan kain perca sarung kotak tisu dan mengetahui kualitas estetis karya kerajinan tangan kain perca sarung kotak tisu yang dihasilkan siswa kelas VII SMP Negeri 1 Beringin Kabupaten Deli Serdang. Penelitian ini menggunakan metode penelitian kualitatif dengan sampel 20 karya kerajinan kain perca sarung kotak tisu siswa kelas VII yang diambil menggunakn teknik Cluster Random Sampling. Instrumen penelitian ini menggunakan tes membuat karya kerajinan kain perca sarung kotak tisu. Teknik analisis data yang digunakan analisis deskriptif.Berdasarkan hasil penelitian dapat disimpulkan bahwa secara keseluruhan siswa telah menghasilkan karya kerajinan limbah kain perca berupa sarung kotak tisu. Secara keseluruhan tingkat kualitas estetis karya kerajinan kain perca pada kelas VII-1 SMP Negeri 1 Beringin Kabupaten Deli Serdang yaitu dari aspek bentuk, warna, ornamen/hiasan, dan nilai fungsi dikategorikan cukup baik. Dari aspek bentuk kerajinan secara umum memperoleh jumlah nilai rata-rata cukup baik karena, secara keseluruhan bentuk dari karya kerajinan sarung kotak tisu siswa belum tersususn secara baik dalam kesatuan yang harmonis dan bentuk yang sempurna. Aspek warna secara umum memperoleh nilai rata-rata cukup baik, karena secara keseluruhan warna dari karya kerajinan sarung kotak tisu siswabelum terdapat warna yang harmonis dan kesesuaian warna dengan unsur lain. Aspek ornamen atau hiasan secara umum memperoleh jumlah nilai rata-rata cukup baik, karena secara keseluruhan ornamen atau hiasan dari karya kerajinan sarung kotak tisu siswa tampak kurang rapi, unik, menarik dan harmonis dengan unsur lain. Dan aspek nilai fungsi secara umum memperoleh jumlah nilai rata-rata cukup baik, namun secara keseluruhan nilai fungsi dari karya kerajinan sarung kotak tisu siswa sudah memiliki nilai fungsi yang ergonomis.Kata Kunci: nilai estetis, kerajinan, kain percaAbstractThis study aims to improve students’ learning achievement at the craft lesson, especially for the lesson material about the handicraft made of rag and to find out the use of the rag in order to make one handicraft product, namely sarong tissue boxes and to find out the aesthetic quality of sarong tissue boxeshandicraft made of rag, which is made by students of seventh (VII) grade of SMP Negeri 1 Beringin Deli Serdang. The study used qualitative research design with 20 products of rag sarong tissue boxes made by seventh (VII) grade students which is taken by using cluster random sampling technigue. The instrument of the study use a test how to make rag sarong tissue boxes. The technigue of data analysis is descriptive analysis. Based on the research finding, it is concluded that all the students made rag sarong tissue boxes handicraft the level 07. The aesthetic quality on them made by VII-1 classs SMP Negeri 1 Beringin Deli Serdang which consist of some aspects, namely shape, colour, ornament/decoration, and function value can be categoryzed at fair level. From the shape aspect totally is got the fair score because the shape of all rag sarong tissue boxes have ast been ordered well in harmonious unity and perfect form. The colour aspect is got the fair score, because totally the colour of students’ rag sarong tissue boxes handicraft have not used harmonious calour and unmatching colour to another element. Overall, the ornament aspect or decoration got fair score, because all the ornaments or the decoration of students’ rag sarong tissue boxes handicraft looked less neat, less unigue and less atractive and less harmonic to another element and the function value aspect got fair score but overall the function value of the students’ rag sarong tissue boxes already had ergnoic function value.Keywords: aesthetic value, patchworks craft
Dissertations / Theses on the topic "Ordered Cluster Sampling"
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Wu, Rong-Fu, and 吳榮富. "Using adaptive cluster sampling based on order statistics for kriging estimation of heavy metal in soils." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/66762249633985364881.
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碩士國立臺灣大學
農業化學研究所
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The spatial interpolation of pollutants in contaminated sites is essential for determining hazardous areas needed for remediation. The spatial distribution of pollutants in contaminated sites can be estimated by using geostatistics methods. However, the accuracy of spatial estimation is highly dependent on the sampling design. If the location of high pollution, i.e. hot spots where are priority areas needed for remediation, are not sampled in the sampling process, the accuracy of spatial estimation of pollutants in contaminated site will be decreased and therefore the effectiveness of remediation will be reduced. In this study, one method of adaptive samplings: adaptive cluster sampling based on order statistics, which can locate hot spots, was combined with geostatistics for spatial interpolation of heavy metal distribution in heavy-metal contaminated site. The simulation approach was used to comparing the effect of adaptive cluster sampling based on order statistics and random sampling on the spatial interpolation of pollutants in contaminated site using geostatistics. The results can be used for evaluate the feasibility of using adaptive sampling combined with geostatistics for increasing the accuracy of estimation of spatial distribution of pollutants. In this study, soil Cu concentration data of 177 blocks (1 ha per block ) from Hsing-chu were used. Five hundred simulations were performed using samples from adaptive cluster sampling based on order statistics and random sampling respectively to estimate the Cu concentration of each block by block kriging. Since avoiding the under-estimates of pollutant is most important for delineating hazardous areas of contaminated soils for remediation, the error of under-estimates were used to evaluate to the performance of estimation by block kriging using the two sampling designs. The 500 simulation results show that there fewer numbers of blocks having under-estimates by using adaptive cluster sampling based on order statistics than random sampling. It indicates that adaptive cluster sampling based on order statistics can reduce under-estimates in estimation of spatial distribution of heavy metal when compared to using random sampling. It suggests that adaptive cluster sampling based on order statistics can be used to locate hot spots in a heavy-metal contaminated site, and therefore , can be combined with kriging estimation for obtaining the spatial distribution of heavy metals in soils without loss of spatial information of hot spots.
Book chapters on the topic "Ordered Cluster Sampling"
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Danlami, Abubakar Hamid, and Shri Dewi Applanaidu. "Sustaining a Cleaner Environment by Curbing Down Biomass Energy Consumption." In African Handbook of Climate Change Adaptation, 1423–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_211.
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AbstractEnvironmental degradation, soil erosion, and desertification are some of the consequences of high rate of traditional biomass fuel use by households in developing countries. The critical issues to raise here are how can these households be encouraged to change their energy consumption behavior? What are the factors that cause the rampant use of biomass fuel in developing countries? How and to what extent can these factors be manipulated so that households in developing countries are encouraged to adopt clean energy fuel an alternative to the most widely used biomass fuel? Therefore, this chapter tries to find answer to the above questions raised, by carrying out an in depth analysis of households’ use of biomass fuel in developing countries using Bauchi State, Nigeria, as the case study. Cluster area sampling technique was utilized to generate the various responses, where a total number of 539 respondents were analyzed. The study estimated ordered logit model to analyze the factors that influence the movement of households along the energy ladder from nonclean energy to the cleaner energy. Furthermore, Ordinary Least Squares (OLS) model was estimated to analyze the impacts of socio-economic, residential, and environmental factors on biomass energy consumption. It was found that age of the household head and his level of education, income, living in urban areas, home ownership, and hours of electricity supply have positive and significant impact on household energy switching from traditional biomass energy use to the cleaner energy. Therefore, policies that will enhance household income and the increase in the availability of cheap cleaner energy will encourage households switching to cleaner energy sources thereby reducing the level of environmental pollution in the study area.
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Danlami, Abubakar Hamid, and Shri Dewi Applanaidu. "Sustaining a Cleaner Environment by Curbing Down Biomass Energy Consumption." In African Handbook of Climate Change Adaptation, 1–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-42091-8_211-1.
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AbstractEnvironmental degradation, soil erosion, and desertification are some of the consequences of high rate of traditional biomass fuel use by households in developing countries. The critical issues to raise here are how can these households be encouraged to change their energy consumption behavior? What are the factors that cause the rampant use of biomass fuel in developing countries? How and to what extent can these factors be manipulated so that households in developing countries are encouraged to adopt clean energy fuel an alternative to the most widely used biomass fuel? Therefore, this chapter tries to find answer to the above questions raised, by carrying out an in depth analysis of households’ use of biomass fuel in developing countries using Bauchi State, Nigeria, as the case study. Cluster area sampling technique was utilized to generate the various responses, where a total number of 539 respondents were analyzed. The study estimated ordered logit model to analyze the factors that influence the movement of households along the energy ladder from nonclean energy to the cleaner energy. Furthermore, Ordinary Least Squares (OLS) model was estimated to analyze the impacts of socio-economic, residential, and environmental factors on biomass energy consumption. It was found that age of the household head and his level of education, income, living in urban areas, home ownership, and hours of electricity supply have positive and significant impact on household energy switching from traditional biomass energy use to the cleaner energy. Therefore, policies that will enhance household income and the increase in the availability of cheap cleaner energy will encourage households switching to cleaner energy sources thereby reducing the level of environmental pollution in the study area.
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Kanetaki, Zoe, Constantinos Stergiou, Georgios Bekas, Christos Troussas, and Cleo Sgouropoulou. "Data Mining for Improving Online Higher Education Amidst COVID-19 Pandemic: A Case Study in the Assessment of Engineering Students." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210088.
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Instructional materials, internet accessibility, student involvement and communication have always been integral characteristics of e-learning. During the transition from face-to-face to COVID-19 new online learning environments, the lectures and laboratories at universities have taken place either synchronously (using platforms, like MS Teams) or asynchronously (using platforms, like Moodle). In this study, a case study of a Greek university on the online assessment of learners is presented. As a testbed of this research, MS Teams was employed and tested as being a Learning Management System for evaluating a single platform use in order to avoid disruption of the educational procedure with concurrent LMS operations during the pandemic. A statistical analysis including a correlation analysis and a reliability analysis has been used to mine and filter data from online questionnaires. 37 variables were found to have a significant impact on the testing of tasks’ assignment into a single platform that was used at the same time for synchronous lectures. The calculation of Cronbach’s Alpha coefficient indicated that 89% of the survey questions have been found to be internally consistent and reliable variables and sampling adequacy measure (Bartlett’s test) was determined to be good at 0.816. Two clusters of students have been differentiated based on the parameters of their diligence, communication abilities and level of knowledge embedding. A hierarchical cluster analysis has been performed extracting a dendrogram indicating 2 large clusters in the upper branch, three clusters in the lower branch and an ensuing lower branch containing five clusters.
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Foufopoulos, Johannes, Gary A. Wobeser, and Hamish McCallum. "Sampling, Experimental Design, and Statistical Analysis." In Infectious Disease Ecology and Conservation, 65–75. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780199583508.003.0004.
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Performing experiments that investigate disease in wildlife populations poses numerous logistic, statistical, and analytical challenges. Efficient study design is therefore very important and typically centers on careful consideration of the “three Rs of sampling and study design.” The first is representativeness; the individuals selected for a study must be representative of the population relevant to the research question. Second, because differences between treatments can only be indicative relative to variation within treatments, replication is needed in order to cover the range of variation in the population of interest. The number of replicates in an experiment depends on the magnitude of the parameter in question, as well as the extent of variation in the response variable. Finally, ensuring randomness through unbiased random sampling of experimental subjects is critical to ensuring representativeness. Several methods of random sampling, including simple random sampling, stratified random sampling, systematic sampling, and cluster sampling are discussed. A final consideration of experimental design explained is statistical power, or a study’s ability to detect a biologically relevant effect or difference. Once an experiment has been designed and conducted, hypothesis testing of the null and alternative hypotheses will help determine whether the patterns observed can be attributed to the infectious agent and how they can be used to guide management decisions.
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"Anadromous Sturgeons: Habitats, Threats, and Management." In Anadromous Sturgeons: Habitats, Threats, and Management, edited by Pierre Nellis, Jean Munro, Daniel Hatin, Gaston Desrosiers, Rachel D. Simons, and Frédéric Guilbard. American Fisheries Society, 2007. http://dx.doi.org/10.47886/9781888569919.ch6.
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<em>Abstract.</em>—The St. Lawrence estuarine transition zone (ETZ) harbors the only known concentrations of age-0 and early juveniles of the St. Lawrence Atlantic sturgeon and lake sturgeon populations. Past dredging and disposal operations conducted in the ETZ to deepen the navigation channel resulted in the creation of an extensive sand dune biotope near the juvenile sturgeon concentration areas. In order to characterize the dune biotope within a diversified set of biotopes in the ETZ, nine areas were selected for study, including two areas to cover the sand dune complex. The study objectives were (1) to identify the benthos assemblages of the ETZ and the main physical factors controlling them, (2) to measure the sampling areas’ biological characteristics and feeding potential for sturgeon, and (3) to compare the dune areas’ feeding potential with selected control areas. In 1999–2001, grab sampling was conducted at 141 stations to determine macrobenthos composition and sediment parameters. Depth, slope, and slope orientation were measured from multibeam sonar echosoundings. Salinity, current velocity, and tidal amplitude were provided by a hydrodynamic model of the ETZ. Benthos assemblages were determined using cluster analysis on taxon biomass. Four major assemblages were identified, all having Tubificidae as the dominant or subdominant taxon: zebra mussel <em>Dreissena polymorpha</em>, <em>Gammarus tigrinus</em>, Tubificidae, and <em>Capitella</em> sp. assemblages. A succession of the major assemblages was observed from the freshwater front to the upper mesohaline waters. Three minor assemblages, the Chironomidae, Physidae, and Cumacea, were concentrated in the upper oligohaline zone. Taxonomic richness was highest in areas with the lowest maximum salinity (0.0–0.5), and diversity was highest in areas with intermediate maximum salinities (0.5–2.0). The largest biomass values were found in areas with maximum salinities less than 0.5, in the zebra mussel assemblage. Controls and dune areas had similar macrobenthos richness and diversity, but dune areas had significantly lower densities and biomasses. Feeding potential for a given sturgeon life stage was measured as the sum of taxa biomasses standardized using the prey proportions in that life stage’s feeding regime. For age-0 Atlantic sturgeon and for all lake sturgeon life stages, all of which feed mostly on gammarids, the feeding potential of control and dune areas were not significantly different. For juvenile and subadult Atlantic sturgeon, which feed mostly on tubificids, the dune areas had a significantly lower feeding potential than the control areas. The lower feeding potential of the sand dune areas created by dredged sediment deposition is considered an important issue for the management of the St. Lawrence Atlantic sturgeon population.
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Liu, Jiaming. "Factors of Spatial Distribution of Recreation Areas in Peri-Urban Beijing." In Global Hospitality and Tourism Management Technologies, 72–90. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-041-5.ch005.
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With the increase of disposable income and leisure time, recreation has become an important lifestyle of urban residents in China. Peri-urban recreation areas, as the important one, could not only meet the outdoor recreational demands of both tourists and residents, but also contribute to sustaining urban ecological security. Rational spatial patterns for recreational land use will mediate the contradictions between urban sprawl and natural preservation, and, economic growth and social development. Based on the case study of peripheral urban areas in Beijing, this chapter aims to identify the factors which will influence the spatial distribution of peri-urban recreation areas, by analyzing the collected data from questionnaires, online survey, documentation and field investigations. In order to achieve sound information, relevant data from different management departments, owners and land-use types involved in the case study area is collected. A sampling database for peri-urban recreation areas in Beijing is established, and GIS spatial analyses as well as statistic analyses are applied. The result indicates that spatial distribution of recreation areas is majorly influenced by four factors, e.g. tourism attractions and environmental conditions, policy and spatial governance, consumption demand and preference, land price and availability. The influencing mechanism of each factor towards different type of recreation areas is various. Tourism attractions and environmental conditions are dominant factors for public recreation areas. Commercial recreation areas are highly related with accessibility. Agricultural recreation areas are usually attached to special farmlands near large-scaled scenic areas. Meanwhile, recreational business clusters have appeared in suburbs influenced by mass recreation market growth. Controlled by the land price, commercial recreation areas are differentiated on their scales and developing intensity. Policy and spatial governance have made arrangements of recreation areas more balancing and more human-oriented. A peri-urban recreation area model is therefore established on basis of this analysis, which can guide urban planning and designing, land-use planning and recreation resource development.
Conference papers on the topic "Ordered Cluster Sampling"
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Acain, Jose, Christopher Kitts, Thomas Adamek, Kamak Ebadi, and Mike Rasay. "A Multi-Robot Testbed for Adaptive Sampling Experimentation via Radio Frequency Fields." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47697.
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Adaptive navigation is the process by which a vehicle determines where to go based on information received while moving through the field of interest. Adaptive sampling is a specific form of this in which that information is environmental data sampled by the robot. This may be beneficial in order to save time/energy compared to a conventional navigation strategy in which the entire field is traversed. Our work in this area focuses on multi-robot gradient-based techniques for the adaptive sampling of a scalar field. To date, we have experimentally demonstrated multi-robot gradient ascent/descent as well as contour following using automated marine surface vessels. In simulation we have verified controllers for ridge descent / valley ascent as well as saddle point detection and loitering. To support rapid development of our controllers, we have developed a new testbed using wireless transmitters to establish a simple, large-scale, customizable scalar field based on the strength of the radio frequency field. A cluster of six land rovers equipped with radio signal strength sensors is then used to process sampled data, to make adaptive decisions on how to move, and to execute those moves. In this paper, we describe the technical design of the testbed, present initial experimental results, and describe our ongoing research and development work in the area of adaptive sampling and multi-robot control.
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Qingnan, Wang, and Zhang Zhaogong. "Active Learning Entropy Sampling based Clustering Optimization Method for Electricity Data." In 12th International Conference on Artificial Intelligence, Soft Computing and Applications. Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.122316.
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Clustering is a crucial part in the field of data mining, and common clustering methods include division-based methods, hierarchy-based methods, density-based methods, and grid-based methods. In order to improve the accuracy of clustering, an optimization study is made mainly for the division-based method FCM clustering, and an FCM clustering method that integrates active learning and principal component analysis (PCA) is proposed. The method first uses principal component analysis to reduce the dimensionality of the data to reduce the computation of electricity data, then trains the sample model by active learning, and introduces the entropy (Entropy) method in the uncertainty sampling method, the larger the entropy means the greater the uncertainty of the sample, and the smaller the entropy means the smaller the uncertainty of the sample, so as to filter the electricity data, and finally the electricity data are clustered by FCM clustering The power data is finally categorized by FCM clustering, and with the proliferation of power data, the power data can be more accurately categorized using this method to achieve the stability of the power grid as well as the utilization rate. Experimental results on three datasets show that this method improves the accuracy of power data clustering by up to 2 percentage points compared to the traditional clustering method without active learning, and achieves good results in each dataset compared to other methods.
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Wang, Lei, Xianguo Tuo, and Chunlai Liu. "Research of Radon Transportation Model to Investigate Buried Fault." In 18th International Conference on Nuclear Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/icone18-29191.
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How to get the position, direction and width of buried fault effectively is still very difficult when finding buried faults by measuring 222Rn radioactivity. In this paper we established a technique to carry out buried fault investigation. It was based on Fick’s fist law, Darcy’s law and theory of clusters to analyze radon transportation and simulate 222Rn transportation in ideal conditions. The feasibility indicates that measuring or investigating the concentration of radon to find abnormal region can help people find buried faults. 218Po and 214Po, daughter products of 222Rn, are generally considered to be proportional to initial concentration of 222Rn. 218Po and 214Po have short half-life of 3.05 min and 164us respectively which is very suitable for actual measure work. So in order to accumulate alpha particles effectively, soil gas sampling period is set about twice half-life of 218Po. The established model is applied to analyze two buried fault areas in Southwest China and the results are really much better.
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Li, Jun, Handong Zhao, Zhiqiang Tao, and Yun Fu. "Large-scale Subspace Clustering by Fast Regression Coding." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/297.
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Large-Scale Subspace Clustering (LSSC) is an interesting and important problem in big data era. However, most existing methods (i.e., sparse or low-rank subspace clustering) cannot be directly used for solving LSSC because they suffer from the high time complexity-quadratic or cubic in n (the number of data points). To overcome this limitation, we propose a Fast Regression Coding (FRC) to optimize regression codes, and simultaneously train a non-linear function to approximate the codes. By using FRC, we develop an efficient Regression Coding Clustering (RCC) framework to solve the LSSC problem. It consists of sampling, FRC and clustering. RCC randomly samples a small number of data points, quickly calculates the codes of all data points by using the non-linear function learned from FRC, and employs a large-scale spectral clustering method to cluster the codes. Besides, we provide a theorem guarantee that the non-linear function has a first-order approximation ability and a group effect. The theorem manifests that the codes are easily used to construct a dividable similarity graph. Compared with the state-of-the-art LSSC methods, our model achieves better clustering results in large-scale datasets.
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Allebach, J. P., D. S. Chen, and J. B. Koskol. "Motion Estimation and Object Recovery with Time-Sequentially Sampled Imagery*." In Machine Vision. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/mv.1985.fa4.
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Algorithms for estimating the motion of a moving object from digital imagery acquired in real time generally rely on two important assumptions: 1) the field of view is sampled frame-instantaneously, i.e. a record of the radiation integrated over a time interval that is short compared to the frame interval is stored at the focal plane, and this frozen image is read out serially during the interval between frames; and 2) there is relatively little change in the image between consecutive frames. With many digital imaging systems, the field of view is sampled time-sequentially during the entire interval between frames; and the radiation sensed at the focal plane changes continuously during this time. Typically, the field of view is sampled in a lexicographic (LEX) or 2:1 line-interlaced (2:1-LI) fashion. These patterns are illustrated in Table 1 which shows the order in which a 4 × 4 array of points would be sampled. With both these patterns, consecutive samples are clustered spatially. Table 1 also shows three dot-interlaced sampling patterns which disperse consecutive samples over the entire field of view. The 2:1 dot-interlaced (2:1-DI) and bit-reversed dot-interlaced (BRV-DI) patterns have been considered for bandwidth compression in video systems. The congruential dot-interlaced (CGR-DI) pattern has been shown to be optimal for sampling bandlimited signals [1],[2]. It also simplifies certain signal processing operations [3]. This particular pattern generates a 5 × 4 array of samples.
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Kanner, Samuel, Alexia Aubault, Antoine Peiffer, and Bingbin Yu. "Efficient Algorithm for Discretization of Metocean Data Into Clusters of Arbitrary Size and Dimension." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-62077.
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In order to run a fatigue analysis on a floating structure, it is common practice among ocean engineers to rely upon a large set of test cases, each with a unique set of environmental conditions. For a specific test site, the issue remains of how to obtain a limited set of environmental conditions for these test cases, sometimes known as bins, which can accurately recreate the conditions. When considering a floating offshore wind turbine, it is necessary to obtain a timeseries of not only the wave conditions, but also the wind conditions (and perhaps current, if possible). Thus, it is common to have greater than 5 dimensions in the time-series (e.g., significant wave height, wave period, wave direction, wind speed, wind direction, etc). The creation of bins in two dimensions is quite easily solved by creating an arbitrary grid and taking the mean of all the observations which fall in a specific cell. In higher dimensions, an N-dimensional cell is not easily visualized and so the resulting set of bins cannot easily be graphically represented. In this paper, an efficient, iterative algorithm is developed to convert N-dimensional metocean data into a set of discrete bins of arbitrary size. The algorithm works by setting a tolerance level on the number of observations that must be included in a cell in order to create a bin. If the population threshold is not met, the observations remain unbinned and another iteration is required. Generally, the population threshold can be a function of iteration number so that all observations will be binned. The algorithm can properly take into account extreme data by setting a tolerance level on the N-dimensional distance by which an observation can be included in a certain bin. A quality measure, q, is created to measure the level of representation of the original data by a set of bins, independent of the number of bins. Depending on the tolerance levels, the algorithm can be completed in seconds on a normal laptop for the available data set of 20 years with a 3-hour sampling rate. The observations and bins from a case study are shown as an example of how the bins can be created and visualized.
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Kim, Jin-Hyuk, Kyung-Hun Cha, and Kwang-Yong Kim. "Sirocco Fan Design for Residential Ventilation Through Multi-Objective Optimization to Enhance Aerodynamic Performance." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68528.
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A multi-objective optimization of a sirocco fan for residential ventilation has been carried out in the present work. A hybrid multi-objective evolutionary algorithm combined with response surface approximation is applied to optimize the total-to-total efficiency and total pressure rise of the sirocco fan for residential ventilation. Three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model are discretized by finite volume method and solved on hexahedral grids for the flow analysis. Numerical results are validated with the experimental data for the total-to-total efficiency and total pressure. The total-to-total efficiency and total pressure rise of the sirocco fan are used as objective functions for the optimization. In order to improve the total-to-total efficiency and total pressure rise of the sirocco fan, four variables defining the scroll cut-off angle, scroll diffuser expansion angle, hub ratio and the blade exit angle, respectively, are selected as the design variables in this study. Latin-hypercube sampling as design-of-experiments is used to generate the design points within the design space. A fast non-dominated sorting genetic algorithm with an ε–constraint strategy for the local search is applied to determine the global Pareto-optimal solutions. The trade-off between two objectives is determined and discussed with respect to the representative clustered optimal solutions in the Pareto-optimal solutions compared to the reference shape.
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Liu, Tao, Yanhua Shen, Haoshuai Wang, and Zuyang Liu. "Trajectory Planning on Autonomous Truck with Dual-Modular Chassis Using Artificial Potential Field and Polynomial." In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0690.
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<div class="section abstract"><div class="htmlview paragraph">Autonomous truck with modular chassis has the characteristics of high driving flexibility and strong load capacity. It can be equipped with different numbers of modular chassis according to the task requirements. The application of autonomous truck can solve the problems of traffic accidents and shortage of drivers effectively, which is the development trend of trucks in the future. For the collision-free trajectory planning problem of dual-modular chassis autonomous truck, this paper designs a hierarchical local trajectory planner that combines the artificial potential field method with polynomial curve fitting method. This planner plans the center of mass trajectory firstly, and then generates the modular chassis trajectories according to the position relationship between the center of mass and the chassis. The center of mass local trajectory cluster satisfying the environment constraints and truck motion constraints is obtained by polynomial curve fitting method for sampling the road discrete points in the parameter space. In order to make the evasive maneuver of dual-modular chassis autonomous truck start earlier to make the obstacle avoidance process safer, a three-dimensional repulsive potential field is constructed based on artificial potential field method around the obstacle. The repulsive potential field of the obstacle is regarded as the constraint of the collision-free trajectory of the truck. The optimal collision-free trajectory is selected by constructing multi-object function. Simulations of obstacle avoidance of dual-modular chassis autonomous truck on different curvature roads with different speeds in Simulink/Simscape environment are conducted to demonstrate performance of the proposed collision-free trajectory planner. The simulation results show that the collision-free trajectory planner based on artificial potential field method and polynomial curve fitting method can make the autonomous truck avoid collision safely and steady on different curvature roads with different speeds.</div></div>