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... The principle of ordinary least square (OLS) parameter estimation [42] is to minimize the residual sum of square (RSS) written in Equation (6). In this test, parameter estimation will be performed on the Y 1t model with the parameters β 1 , γ 11 , and θ 11 . ...
... The first step is to calculate the probability transition PM 2.5 data, which is classified by No Risk , Medium Risk (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48), and Moderate (> 49). In this paper, we are using monthly data from January 2014 to May 2019 in 2 Taiwanese locations, Pingtung and Chaozhou. ...
Air pollution is the entry or inclusion of living things, energy substances, and other components into the air. Moreover, Air pollution is the presence of one or several contaminants in the outside atmospheric air such as dust, foam, gas, fog, smoke or steam in large quantities with various properties and time intervals of the contaminants in the air resulting in disturbances to the lives of humans, plants or animals. One of the parameters measured in determining air quality is PM2.5. However, PM2.5 has a higher probability of being able to enter the lower respiratory tract because small particle diameters can potentially pass through the lower respiratory tract. In this paper, we will get two different insight. First, the probability of status change using Markov chain and second, forecasting by using VAR-NN-PSO(Vector Autoregressive, Neural Network, Particle Swarm optimization). More details we classify by three classifications no risk (1-30), medium risk (30-48), and moderate (>49) in Pingtung and Chaozhou start from January 2014 to May 2019. This data is starting from January 2014 to May 2019 so that it can be modeled with the Markov chain. At the same time, we perform Hybrid VAR-NN-PSO to forecast PM2.5 in Pingtung and Chaozhou. In this optimization, the search for solutions is carried out by a population consisting of several particles. Based on the results of the discussion, opportunities for the transition from monthly status change are obtained continuous stochastic time with a stationary probability distribution. Regarding the VAR-NN-PSO, we obtained the mean absolute percentage error (MAPE) 3.57% for PM2.5 data in Pingtung and 4.87% for PM2.5 data in Chaozhou, respectively. This model can be predicted to forecasting 180 days ahead. The population in PSO has generated randomly with the smallest value and the largest value the accuracy.
... Multiple linear regression models can be used to explain a dependent variable that has multiple independent (predictor) variables (Olive, 2017). The output of these models are equations for a prediction line that theoretically accounts for all factors affecting the dependent variable and is one of the most precise statistical modeling systems (Smith et al. 2013 where μ{NO3│x} is the predicted mean groundwater nitrate level (mg nitrate-N L -1 ); β0 is the constant term; β1 is the regression coefficient for the surface N load factor; XNload is the measured N load calculation for the 500 m radius AOI (kg N ha -1 year -1 ); β2 is the regression coefficient for the CAFO factor, and XCAFO is either a 1 or 0 whether the well is within the AOI of a CAFO or not. ...
The shallow aquifer in Southern Willamette Valley (SWV) has high levels of nitrate, and we are exploring the time trends in nitrate, and the hydrologic and land management factors that contribute to this problem. Nitrogen (N) inputs to farmland from fertilizer is thought to be the primary source of nitrogen to the Southern Willamette Valley (SWV) landscape. Elevated levels of nitrate in the shallow domestic wells have been measured at nitrate concentrations identified by the state of Oregon as a human health concern. In 2004, the Oregon Department of Environmental Quality (DEQ) designated a portion of the Southern Willamette Valley as a Groundwater Management Area (GWMA) where water quality data in 44 domestic and monitoring wells have been collected since 2005. Ranging from the northern boundary of Corvallis to the Springfield/Eugene region, the GWMA is characterized by substantial sources of nitrate which include agricultural fertilizers, home septic systems, concentrated animal feeding operations, and other non-point sources. This project was oriented around understanding how the groundwater nitrate levels changed since 2005. Using geospatial and statistical modeling techniques, as well as machine learning, representative prediction models were produced to give an indication of how the nitrate levels are changing over time, and to infer the likely sources. Using annual remote sensing landcover data dating back to 2004, we explored how land use and expected N fertilizer inputs over time based on locally-derived crop type have influenced monitoring well nitrate levels dynamics over the last 14 years. Approximately 57% of the wells in the study area increased between 2006 and 2019, and the total mean nitrate- N level in wells has increased from the 2006 through 2011 well mean of 5.41 mg nitrate-N L-1 to a mean of 6.28 mg nitrate-N L-1 from 2012 to 2019. Our findings indicate despite the greater awareness of the issue of groundwater nitrate contamination in the SWV GWMA, groundwater nitrate concentrations increased over the last 14 years, with the average monitoring well concentration now falling above the state of Oregon’s action level of 7 mg nitrate-N L-1. Future efforts may need to find new approaches to improving drinking water quality in the area and continue to reach out to residents to ensure public safety.
... From the image it can be found that the distribution of points is nearly linear. Therefore, the multiple linear regression [17] can be used to establish the functional relationship between video length and number and . ...
MOOCs (massive open online courses) are developing rapidly, but they also face many problems. As the MOOC’s most important resource, the course videos have a very important influence on the learning. This article defines the ratio R ( R=Average viewing duration/Video length ), which reflects the popularity of the video. By analyzing the relationship between the video length, release time, and R , we found a significant negative linear correlation between video length and R and video release time and R . However, when the number of videos is less than the threshold, the release time has less influence on R . This paper presents a video viewing behavior analysis algorithm based on multiple linear regression. The residual independence test proved that the algorithm has a good approximation to the data. It can predict the popularity of similar course videos to help producers optimize video design.
In an attempt to thrive open innovation and collaboration with young and innovative start-up companies, more and more corporate firms use so-called corporate accelerators. Thereby established corporate firms aim to profit from the problem-solving and business opportunity-exploring capabilities of agile and flexible organized entrepreneurial firms and to facilitate knowledge and technology insourcing. Start-ups on the other side get access to corporate resources, networks and expertise.
Such corporate accelerators are described in literature as relatively autonomously operating and structurally separated entities – with a climate and routines and processes strongly deviating from the ones typically prevalent in a big and established corporate company. Thereby serving as a means to facilitate open innovation and fast and efficient external knowledge exploration and absorption.
In a quantitative analysis of a single case of corporate acceleration, this master’s thesis aims to validate these assumptions by comparing the open innovation climate prevalent in a corporate accelerator with other conventional business units of the same company and its impact on realized absorptive capacity. Regarding the concept open innovation climate, this thesis is primarily oriented towards the work of Remneland-Wikhamn and Wikhamn (2011). With regard to the well-known concept of absorptive capacity, this thesis refers primarily to the work of Cohen and Levinthal (1990) and Zahra and George (2002).
The main research interest of this work is to deepen the understanding of open innovation-facilitating effects of corporate acceleration, but also to explore its accompanying limits and challenges. The first literature-theoretical part of this work will furthermore draw up the antecedents and underlying logics of big firm – start-up collaborations in general and corporate acceleration in particular.
Fakta bahwa di beberapa negara berkembang, konsumsi rokok menimbulkan beban ekonomis yang signifikan (Toukan, 2016; Block dan Webb, 2009). Juga, untuk konteks Indonesia kontemporer, Kepala BPS mengatakan bahwa belanja rokok merupakan pengeluaran kedua terbesar dan memberikan kontribusi nyata terhadap angka kemiskinan nasional. Namun, kajian kontemporer yang secara komprehensif membahas beras dan rokok terhadap kemiskinan belum banyak dibahas. Celah penelitian tersebut menjadi dasar bagi kami untuk melakukan kajian mengenai hubungan konsumsi beras dan pengeluaran potensial rokok di antara rumah tangga miskin di Indonesia 2014. Untuk keperluan telaah kajian penelitian ini, kami membagi kategori rumah tangga berdasarkan tempat tinggal (perdesaan/perkotaan), rumah tangga dengan banyak anggota rumah tangga usia dewasa (di atas 15 tahun), dsb. Tujuan dari kajian ini adalah untuk menganalisa apakah rumah tangga miskin lebih memilih mengurangi konsumsi beras dibanding mengurangi konsumsi rokok .Untuk kajian ini, kami menggunakan Survei Sosial Ekonomi Nasional tahun 2014. Dengan menggunakan Model Regresi Linier Berganda, kami menggunakan sampel rumah tangga yang memiliki anggota rumah tangga dewasa yang merokok (NIndonesia = 285.371). Hasil penelitian kami menunjukkan bahwa rumah tangga miskin yang memiliki anggota rumah tangga perokok secara rata-rata mengkonsumsi beras relatif lebih sedikit dibandingkan rumah tangga yang tidak memiliki anggota rumah tangga perokok, baik yang termasuk kategori miskin maupun tidak. Hal ini mengindikasikan bahwa rumah tangga miskin lebih memprioritaskan konsumsi rokok dibandingkan konsumsi beras.
– In this paper, the development of novel macros for MINITAB are presented, to perform certain operations: (i) a curve-fitting examining 14 algorithms, (ii) comparing experimental designs, (iii) analyzing Latin square designs with sub-samplings,(iv) orthogonal contrasts comparisons, (v) performing multivariate path coefficient analysis, (vi, vii) analyzing stability analysis of genotypes. Twenty of recently-bred maize genotypes were examined under 2 drought environments along with the control in the field, and grain yield (YLD), seeds per ear (SPE), and ear length (EL) were scored. In the results, the relative efficiencies (RE) showed that LS design has a lower RE than its lower-level designs. The orthogonal comparison indicated a significant difference between two groups of maize genotypes (9 vs 11). Accordingly, our macro unraveled a specific kind of the exponential curves with the highest R-sq(adj) index (91.54%). Path coefficients analysis showed the effects of EL and SPE traits on grain yield. The stability analysis introduced genotype BARAKAT-74, GARZA, and DKC-6101, BOLSON as the most stable genotypes under drought. Finally, the AMMI2 model was the best model and introduced the stable, high-yielding and moderate-tolerant maize genotypes. The macros presented here could be utilized in various areas of biological sciences, especially plant breeding, to perform advanced statistical and experimental design analyses.
Background:
The lumbar region is a potential donor site for perforator-based rotational or free flaps or as a recipient site for free flaps to obtain coverage for deficits in the sacral region. Because of the lack of consensus regarding the microvascular anatomy of this potential flap site, a robust investigation of the anatomy of this region is required.
Methods:
Three-dimensional reconstructions (n = 6) of the microvasculature of the lumbar region were generated using MIMICS software (Materialise, Belgium) for each of the four paired lumbar vessels. Diameter, course, and pedicle length were recorded for all lumbar artery (LA) perforators. Statistical analysis was performed using SigmaStat 4.0 and graphs were generated using GraphPad Prism 6 Software.
Results:
Perforators arising from the first pair of LAs are reliably detected along the inferior margin of the 12th rib, extending inferiorly and laterally from the midline while perforators arising from the fourth pair of LA perforate the fascia along a horizontal plane connecting the posterior iliac crests. There are significantly more cutaneous perforators arising from the first (L1) and fourth (L4) pairs of LA than from the second (L2) and third (L3) (mean ± SD: L1, 5.5 ± 1.2; L2, 1.4 ± 0.7; L3, 1.3 ± 0.7; L4, 4.8 ± 1.0; P < 0.05). The average perforator diameter arising from L1 is greater than those arising from L4 (diameter ± SD: L1, 1.2 mm ± 0.2 >L4, 0.8 mm ± 0.2; P < 0.0001). L1 and L4 perforators have longer pedicle lengths than those arising from L2 and L3 (length ± SD: L1, 98.2 mm ± 57.8; L4, 106.1 mm ± 23.3 >L2, 67.5 mm ± 27.4; L3, 78.5 mm ± 30.3; P < 0.05).
Conclusions:
Perforators arising from the first and fourth LAs arise in a predictable fashion, have adequate pedicle lengths, and are of suitable diameter to support a perforator flap. We present a case to support the potential use of this flap for microvascular breast reconstruction.
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