Search results for: parallel k-means algorithm

Authors: V. Moser-Siegmeth, M. C. Gambal, M. Jelovcak, B. Prytek, I. Swietalsky, D. Würzl, C. Fida, V. Mühlegger

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Adaptability is the capacity to adjust without great difficulty to changing circumstances. Within our project, we aimed to detect whether older people living within a long-term care hospital lose the ability to adapt. Theoretical concepts are contradictory in their statements. There is also lack of evidence in the literature how the adaptability of older people changes over the time. Following research questions were generated: Are older residents of a long-term care facility able to adapt to changes within their daily routine? How long does it take for older people to adapt? The study was designed as a convergent parallel mixed method intervention study, carried out within a four-month period and took place within seven wards of a long-term care hospital. As a planned intervention, a change of meal-times was established. The inhabitants were surveyed with qualitative interviews and quantitative questionnaires and diaries before, during and after the intervention. In addition, a survey of the nursing staff was carried out in order to detect changes of the people they care for and how long it took them to adapt. Quantitative data was analysed with SPSS, qualitative data with a summarizing content analysis. The average age of the involved residents was 82 years, the average length of stay 45 months. The adaptation to new situations does not cause problems for older residents. 47% of the residents state that their everyday life has not changed by changing the meal times. 24% indicate ‘neither nor’ and only 18% respond that their daily life has changed considerably due to the changeover. The diaries of the residents, which were conducted over the entire period of investigation showed no changes with regard to increased or reduced activity. With regard to sleep quality, assessed with the Pittsburgh sleep quality index, there is little change in sleep behaviour compared to the two survey periods (pre-phase to follow-up phase) in the cross-table. The subjective sleep quality of the residents is not affected. The nursing staff points out that, with good information in advance, changes are not a problem. The ability to adapt to changes does not deteriorate with age or by moving into a long-term care facility. It only takes a few days to get used to new situations. This can be confirmed by the nursing staff. Although there are different determinants like the health status that might make an adjustment to new situations more difficult. In connection with the limitations, the small sample size of the quantitative data collection must be emphasized. Furthermore, the extent to which the quantitative and qualitative sample represents the total population, since only residents without cognitive impairments of selected units participated. The majority of the residents has cognitive impairments. It is important to discuss whether and how well the diary method is suitable for older people to examine their daily structure.

Keywords: adaptability, intervention study, mixed methods, nursing home residents

Procedia PDF Downloads 136

Authors: Marta Ribo, Ian D. Goodwin, Thomas Mortlock, Phil O’Brien

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Coastal behavior is best investigated using a sediment budget approach, based on the identification of sediment sources and sinks. Grain size distribution over the New South Wales (NSW) continental shelf has been widely characterized since the 1970’s. Coarser sediment has generally accumulated on the outer shelf, and/or nearshore zones, with the latter related to the presence of nearshore reef and bedrocks. The central part of the NSW shelf is characterized by the presence of fine sediments distributed parallel to the coastline. This study presents new grain size distribution maps along the NSW continental shelf, built using all available NSW and Commonwealth Government holdings. All available seabed bathymetric data form prior projects, single and multibeam sonar, and aerial LiDAR surveys were integrated into a single bathymetric surface for the NSW continental shelf. Grain size information was extracted from the sediment sample data collected in more than 30 studies. The information extracted from the sediment collections varied between reports. Thus, given the inconsistency of the grain size data, a common grain size classification was her defined using the phi scale. The new sediment distribution maps produced, together with new detailed seabed bathymetric data enabled us to revise the delineation of sediment compartments to more accurately reflect the true nature of sediment movement on the inner shelf and nearshore. Accordingly, nine primary mega coastal compartments were delineated along the NSW coast and shelf. The sediment compartments are bounded by prominent nearshore headlands and reefs, and major river and estuarine inlets that act as sediment sources and/or sinks. The new sediment grain size distribution was used as an input in the morphological modelling to quantify the sediment transport patterns (and indicative rates of transport), used to investigate sand supply rates and processes from the lower shoreface to the NSW coast. The rate of sand supply to the NSW coast from deep water is a major uncertainty in projecting future coastal response to sea-level rise. Offshore transport of sand is generally expected as beaches respond to rising sea levels but an onshore supply from the lower shoreface has the potential to offset some of the impacts of sea-level rise, such as coastline recession. Sediment exchange between the lower shoreface and sub-aerial beach has been modelled across the south, central, mid-north and far-north coast of NSW. Our model approach is that high-energy storm events are the primary agents of sand transport in deep water, while non-storm conditions are responsible for re-distributing sand within the beach and surf zone.

Keywords: New South Wales coast, off-shore transport, sand supply, sediment distribution maps

Procedia PDF Downloads 219

Authors: Ahmed Tawfik

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Oxidation of 1,4 dioxane produces metabolites by-products involving glycolaldehyde and acids that have geno- and cytotoxicity impact on microbial degradation. Thereby, the incorporation of algae with bacteria in the treatment system would eliminate and overcome the accumulation of metabolites that are utilized as a carbon source for the build-up of biomass. Therefore, the aim of the present study is to assess the potential of algae/bacteria-based membrane bioreactor (AB-MBR) for biodegradation of 1,4 dioxane-rich wastewater at a high imposed loading rate. Three identical reactors, i.e., AB-MBR1, AB-MBR2, and AB-MBR3, were operated in parallel at 1,4 dioxane loading rates of 641.7, 320.9, and 160.4 mg/L. d., and HRTs of 6.0, 12 and 24 h. respectively. The AB-MBR1 achieved 1,4 dioxane removal rate of 263.7 mg/L.d., where the residual value in the treated effluent amounted to 94.4±22.9 mg/L. Reducing the 1,4 dioxane loading rate (LR) to 320.9 mg/L.d in the AB-MBR2 maximized the removal rate efficiency of 265.9 mg/L.d., with a removal efficiency of 82.8±3.2%. The minimum value of 1,4 dioxane of 17.3±1.8 mg/L in the treated effluent of AB-MBR3 was obtained at an HRT of 24.0 h and loading rate of 160.4 mg/L.d. The mechanism of 1,4 dioxane degradation in AB-MBR was a combination of volatilization (8.03±0.6%), UV oxidation (14.1±0.9%), microbial biodegradation (49.1±3.9%) and absorption/uptake and assimilation by algae (28.8±2.%). Further, the Thioclava, Afipia, and Mycobacterium genera oxidized and produced the required enzymes for hydrolysis and cleavage of the dioxane ring into 2-hydroxy-1,4 dioxane. Moreover, the fungi, i.e., Basidiomycota and Cryptomycota, played a big role in the degradation of the 1,4 dioxane into 2-hydroxy-1,4 dioxane. Xanthobacter and Mesorhizobium were involved in the metabolism process by secreting alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), and glycolate oxidase. Bacteria and fungi produced dehydrogenase (DH) for the transformation of 2-hydroxy-1,4 dioxane into 2-hydroxy-ethoxyacetaldehyde. The latter is converted into Ethylene glycol by Aldehyde hydrogenase (ALDH). Ethylene glycol is oxidized into acids using Alcohol hydrogenase (ADH). The Diatomea, Chlorophyta, and Streptophyta utilize the metabolites for biomass assimilation and produce the required oxygen for further oxidation of the dioxane and its metabolites by-products of bacteria and fungi. The major portion of metabolites (ethylene glycol, glycolic acid, and oxalic acid were removed due to uptake and absorption by algae (43±4.3%), followed by adsorption (18.4±0.9%). The volatilization and UV oxidation contribution for the degradation of metabolites were 8.7±0.7% and 12.3±0.8%, respectively. The capabilities of genera Defluviimonas, Thioclava, Luteolibacter, and Afipia. The genera of Defluviimonas, Thioclava, Luteolibacter, and Mycobacterium were grown under a high 1,4 dioxane LR of 641.7 mg/L.d. The Chlorophyta (4.1-43.6%), Streptophyta (2.5-21.7%), and Diatomea (0.8-1.4%) phyla were dominant for degradation of 1,4 dioxane. The results of this study strongly demonstrated that the bioremediation and bioaugmentation process can safely remove 1,4 dioxane from industrial wastewater while minimizing environmental concerns and reducing economic costs.

Keywords: wastewater, membrane bioreactor, bacterial community, algal community

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Authors: T. Asefi, J. Faiz, M. A. Khan

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This paper introduces dual rotor axial flux machines with surface mounted and spoke type ferrite permanent magnets with concentrated windings; they are introduced as alternatives to a generator with surface mounted Nd-Fe-B magnets. The output power, voltage, speed and air gap clearance for all the generators are identical. The machine designs are optimized for minimum mass using a population-based algorithm, assuming the same efficiency as the Nd-Fe-B machine. A finite element analysis (FEA) is applied to predict the performance, emf, developed torque, cogging torque, no load losses, leakage flux and efficiency of both ferrite generators and that of the Nd-Fe-B generator. To minimize cogging torque, different rotor pole topologies and different pole arc to pole pitch ratios are investigated by means of 3D FEA. It was found that the surface mounted ferrite generator topology is unable to develop the nominal electromagnetic torque, and has higher torque ripple and is heavier than the spoke type machine. Furthermore, it was shown that the spoke type ferrite permanent magnet generator has favorable performance and could be an alternative to rare-earth permanent magnet generators, particularly in wind energy applications. Finally, the analytical and numerical results are verified using experimental results.

Keywords: axial flux, permanent magnet generator, dual rotor, ferrite permanent magnet generator, finite element analysis, wind turbines, cogging torque, population-based algorithms

Procedia PDF Downloads 137

Authors: Ian Kingsbury

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The rapid expansion of charter schools (public schools that receive government but do not face the same regulations as traditional public schools) over the preceding two decades has raised concerns over the potential for graft and fraud. These concerns are largely justified: Incidents of financial crime and mismanagement are not unheard of, and the charter sector has become a darling of hedge fund managers. In response, several states have strengthened their charter school regulatory regimes. Imposing regulations and attempting to increase accountability seem like sensible measures, and perhaps they are necessary. However, increased regulation may come at the cost of imposing barriers to entry. Specifically, increased regulation often entails evidence for a high likelihood of fiscal solvency. That should theoretically entail access to capital in the short-term, which may systematically preclude Black or Hispanic applicants from opening charter schools. Moreover, increased regulation necessarily entails more red tape. The institutional wherewithal and the number of hours required to complete an application to open a charter school might favor those who have partnered with an education service provider, specifically a charter management organization (CMO) or education management organization (EMO). These potential barriers to entry pose a significant policy concern. Just as policymakers hope to increase the share of minority teachers and principals, they should sensibly care whether individuals who open charter schools look like the students in that school. Moreover, they might be concerned if successful applications in states with stringent regulations are overwhelmingly affiliated with education service providers. One of the original missions of charter schools was to serve as a laboratory of innovation. Approving only those applications affiliated with education service providers (and in effect establishing a parallel network of schools rather than a diverse marketplace of schools) undermines that mission. Data and methods: The analysis examines more than 2,000 charter school applications from 15 states. It compares the outcomes of applications from states with a strong regulatory environment (those with high scores) from NACSA-the National Association of Charter School Authorizers- to applications from states with a weak regulatory environment (those with a low NACSA score). If the hypothesis is correct, applicants not affiliated with an ESP are more likely to be rejected in high-regulation states compared to those affiliated with an ESP, and minority candidates not affiliated with an education service provider (ESP) are particularly likely to be rejected. Initial returns indicate that the hypothesis holds. More applications in low NASCA-scoring Arizona come from individuals not associated with an ESP, and those individuals are as likely to be accepted as those affiliated with an ESP. On the other hand, applicants in high-NACSA scoring Indiana and Ohio are more than 20 percentage points more likely to be accepted if they are affiliated with an ESP, and the effect is particularly pronounced for minority candidates. These findings should spur policymakers to consider the drawbacks of charter school accountability and consider accountability regimes that do not impose barriers to entry.

Keywords: accountability, barriers to entry, charter schools, choice

Procedia PDF Downloads 145

Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Joanna Gerszon, Aleksandra Rodacka

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In the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, protein and peptide aggregation processes play a vital role in contributing to the formation of intracellular and extracellular protein deposits. One of the major components of these deposits is the oxidatively modified glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Therefore, the purpose of this research was to answer the question whether piceatannol, a stilbene derivative, counteracts and/or slows down oxidative stress-induced GAPDH aggregation. The study also aimed to determine if this natural occurring compound prevents unfavorable nuclear translocation of GAPDH in hippocampal cells. The isothermal titration calorimetry (ITC) analysis indicated that one molecule of GAPDH can bind up to 8 molecules of piceatannol (7.3 ± 0.9). As a consequence of piceatannol binding to the enzyme, the loss of activity was observed. Parallel with GAPDH inactivation the changes in zeta potential, and loss of free thiol groups were noted. Nevertheless, the ligand-protein binding does not influence the secondary structure of the GAPDH. Precise molecular docking analysis of the interactions inside the active center allowed to presume that these effects are due to piceatannol ability to assemble a covalent binding with nucleophilic cysteine residue (Cys149) which is directly involved in the catalytic reaction. Molecular docking also showed that simultaneously 11 molecules of ligand can be bound to dehydrogenase. Taking into consideration obtained data, the influence of piceatannol on level of GAPDH aggregation induced by excessive oxidative stress was examined. The applied methods (thioflavin-T binding-dependent fluorescence as well as microscopy methods - transmission electron microscopy, Congo Red staining) revealed that piceatannol significantly diminishes level of GAPDH aggregation. Finally, studies involving cellular model (Western blot analyses of nuclear and cytosolic fractions and confocal microscopy) indicated that piceatannol-GAPDH binding prevents GAPDH from nuclear translocation induced by excessive oxidative stress in hippocampal cells. In consequence, it counteracts cell apoptosis. These studies demonstrate that by binding with GAPDH, piceatannol blocks cysteine residue and counteracts its oxidative modifications, that induce oligomerization and GAPDH aggregation as well as it prevents hippocampal cells from apoptosis by retaining GAPDH in the cytoplasm. All these findings provide a new insight into the role of piceatannol interaction with GAPDH and present a potential therapeutic strategy for some neurological disorders related to GAPDH aggregation. This work was supported by the by National Science Centre, Poland (grant number 2017/25/N/NZ1/02849).

Keywords: glyceraldehyde-3-phosphate dehydrogenase, neurodegenerative disease, neuroprotection, piceatannol, protein aggregation

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Authors: Muhammad Abubakar Alhassan, Diane Pennington

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Social networking sites have become a space for people to discuss public health issues such as non-suicidal self-injury (NSSI). There are thousands of tweets containing self-harm and self-injury hashtags on Twitter. It is difficult to distinguish between different users who participate in self-injury discussions on Twitter and how their opinions change over time. Also, it is challenging to understand the topics surrounding NSSI discussions on Twitter. We retrieved tweets using #selfham and #selfinjury hashtags and investigated those from the United kingdom. We applied inductive coding and grouped tweeters into different categories. This study used the Latent Dirichlet Allocation (LDA) algorithm to infer the optimum number of topics that describes our corpus. Our findings revealed that many of those participating in NSSI discussions are non-professional users as opposed to medical experts and academics. Support organisations, medical teams, and academics were campaigning positively on rais-ing self-injury awareness and recovery. Using LDAvis visualisation technique, we selected the top 20 most relevant terms from each topic and interpreted the topics as; children and youth well-being, self-harm misjudgement, mental health awareness, school and mental health support and, suicide and mental-health issues. More than 50% of these topics were discussed in England compared to Scotland, Wales, Ireland and Northern Ireland. Our findings highlight the advantages of using the Twitter social network in tackling the problem of self-injury through awareness. There is a need to study the potential risks associated with the use of social networks among self-injurers.

Keywords: self-harm, non-suicidal self-injury, Twitter, social networks

Procedia PDF Downloads 115

Authors: A. Maghoul, A. Rostampouryasouri, MR. Maghami

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The development of an urban design and power network planning has been gaining momentum in recent years. The integration of renewable energy with urban design has been widely regarded as an increasingly important solution leading to climate change and energy security. Through the use of passive strategies and solar integration with Urban Building Energy Modeling (UBEM) tools, architects and designers can create high-quality designs that meet the needs of clients and stakeholders. To determine the most effective ways of combining renewable energy with urban development, we analyze the relationship between urban form and renewable energy production. The procedure involved in this practice include passive solar gain (in building design and urban design), solar integration, location strategy, and 3D models with a case study conducted in Tehran, Iran. The study emphasizes the importance of spatial and temporal considerations in the development of sector coupling strategies for solar power establishment in arid and semi-arid regions. The substation considered in the research consists of two parallel transformers, 13 lines, and 38 connection points. Each urban load connection point is equipped with 500 kW of solar PV capacity and 1 kWh of battery Energy Storage (BES) to store excess power generated from solar, injecting it into the urban network during peak periods. The simulations and analyses have occurred in EnergyPlus software. Passive solar gain involves maximizing the amount of sunlight that enters a building to reduce the need for artificial lighting and heating. Solar integration involves integrating solar photovoltaic (PV) power into smart grids to reduce emissions and increase energy efficiency. Location strategy is crucial to maximize the utilization of solar PV in an urban distribution feeder. Additionally, 3D models are made in Revit, and they are keys component of decision-making in areas including climate change mitigation, urban planning, and infrastructure. we applied these strategies in this research, and the results show that it is possible to create sustainable and energy-efficient urban environments. Furthermore, demand response programs can be used in conjunction with solar integration to optimize energy usage and reduce the strain on the power grid. This study highlights the influence of ancient Persian architecture on Iran's urban planning system, as well as the potential for reducing pollutants in building construction. Additionally, the paper explores the advances in eco-city planning and development and the emerging practices and strategies for integrating sustainability goals.

Keywords: energy-efficient urban planning, sustainable architecture, solar energy, sustainable urban design

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Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

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Authors: Hassan M. H. Mustafa

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This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

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Authors: Belal Mohamadi Kalesar, Raouf Hasanpour

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Proper placement of Distributed Generation (DG) units such as wind turbine generators in distribution system are still very challenging issue for obtaining their maximum potential benefits because inappropriate placement may increase the system losses. This paper proposes Particle Swarm Optimization (PSO) technique for optimal placement of wind based DG (WDG) in the primary distribution system to reduce energy losses and voltage profile improvement with four different wind levels modeling in year duration. Also, wind turbine is modeled as a DFIG that will be operated at unity power factor and only one wind turbine tower will be considered to install at each bus of network. Finally, proposed method will be implemented on widely used 69 bus power distribution system in MATLAB software environment under four scenario (without, one, two and three WDG units) and for capability test of implemented program it is supposed that all buses of standard system can be candidate for WDG installing (large search space), though this program can consider predetermined number of candidate location in WDG placement to model financial limitation of project. Obtained results illustrate that wind speed increasing in some months will increase output power generated but this can increase / decrease power loss in some wind level, also results show that it is required about 3MW WDG capacity to install in different buses but when this is distributed in overall network (more number of WDG) it can cause better solution from point of view of power loss and voltage profile.

Keywords: wind turbine, DG placement, wind levels effect, PSO algorithm

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Authors: Mustafa M. Donma, Orkide Donma, Murat Aydin, Muhammet Demirkol, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

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Childhood obesity is an ever increasing global health problem, affecting both developed and developing countries. Accurate evaluation of obesity in children requires difficult and detailed investigation. In our study, obesity in children was evaluated using new body fat ratios and indices. Assessment of anthropometric measurements, as well as some ratios, is important because of the evaluation of gender differences particularly during the late periods of obesity. A total of 239 children; 168 morbid obese (MO) (81 girls and 87 boys) and 71 normal weight (NW) (40 girls and 31 boys) children, participated in the study. Informed consent forms signed by the parents were obtained. Ethics Committee approved the study protocol. Mean ages (years)±SD calculated for MO group were 10.8±2.9 years in girls and 10.1±2.4 years in boys. The corresponding values for NW group were 9.0±2.0 years in girls and 9.2±2.1 years in boys. Mean body mass index (BMI)±SD values for MO group were 29.1±5.4 kg/m² and 27.2±3.9 kg/m² in girls and boys, respectively. These values for NW group were calculated as 15.5±1.0 kg/m² in girls and 15.9±1.1 kg/m² in boys. Groups were constituted based upon BMI percentiles for age-and-sex values recommended by WHO. Children with percentiles >99 were grouped as MO and children with percentiles between 85 and 15 were considered NW. The anthropometric measurements were recorded and evaluated along with the new ratios such as trunk-to-appendicular fat ratio, as well as indices such as Index-I and Index-II. The body fat percent values were obtained by bio-electrical impedance analysis. Data were entered into a database for analysis using SPSS/PASW 18 Statistics for Windows statistical software. Increased waist-to-hip circumference (C) ratios, decreased head-to-neck C, height ‘to’ ‘two’-‘to’-waist C and height ‘to’ ‘two’-‘to’-hip C ratios were observed in parallel with the development of obesity (p≤0.001). Reference value for height ‘to’ ‘two’-‘to’-hip ratio was detected as approximately 1.0. Index-II, based upon total body fat mass, showed much more significant differences between the groups than Index-I based upon weight. There was not any difference between trunk-to-appendicular fat ratios of NW girls and NW boys (p≥0.05). However, significantly increased values for MO girls in comparison with MO boys were observed (p≤0.05). This parameter showed no difference between NW and MO states in boys (p≥0.05). However, statistically significant increase was noted in MO girls compared to their NW states (p≤0.001). Trunk-to-appendicular fat ratio was the only fat-based parameter, which showed gender difference between NW and MO groups. This study has revealed that body ratios and formula based upon body fat tissue are more valuable parameters than those based on weight and height values for the evaluation of morbid obesity in children.

Keywords: anthropometry, childhood obesity, gender, morbid obesity

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Authors: Salah Abdul Hameed Saleh, Ghada Hasan

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The aim of this work is to produce an empirical model for the determination of particulate matter (PM10) concentration in the atmosphere using visible bands of Landsat 8 OLI satellite image over Kirkuk city- IRAQ. The suggested algorithm is established on the aerosol optical reflectance model. The reflectance model is a function of the optical properties of the atmosphere, which can be related to its concentrations. The concentration of PM10 measurements was collected using Particle Mass Profiler and Counter in a Single Handheld Unit (Aerocet 531) meter simultaneously by the Landsat 8 OLI satellite image date. The PM10 measurement locations were defined by a handheld global positioning system (GPS). The obtained reflectance values for visible bands (Coastal aerosol, Blue, Green and blue bands) of landsat 8 OLI image were correlated with in-suite measured PM10. The feasibility of the proposed algorithms was investigated based on the correlation coefficient (R) and root-mean-square error (RMSE) compared with the PM10 ground measurement data. A choice of our proposed multispectral model was founded on the highest value correlation coefficient (R) and lowest value of the root mean square error (RMSE) with PM10 ground data. The outcomes of this research showed that visible bands of Landsat 8 OLI were capable of calculating PM10 concentration with an acceptable level of accuracy.

Keywords: air pollution, PM10 concentration, Lansat8 OLI image, reflectance, multispectral algorithms, Kirkuk area

Procedia PDF Downloads 434

Authors: Somya Ranjan Patro, Abhigna Bhatt, Arnab Banerjee

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Inertial amplifier has recently gained increasing attention as a new mechanism for vibration control of structures. Currently, theoretical investigations are undertaken by researchers to reveal its fundamentals and to understand its underline principles in altering the structural response of structures against dynamic loadings. This paper investigates experimental and analytical studies on the dynamic characteristics of hybrid beam inertial amplifier (HBIA). The analytical formulation of the HBIA has been derived by implementing the spectral element method and rigid body dynamics. This formulation gives the relation between dynamic force and the response of the structure in the frequency domain. Further, for validation of the proposed HBIA, the experiments have been performed. The experimental setup consists of a 3D printed HBIA of polylactic acid (PLA) material screwed at the base plate of the shaker system. Two numbers of accelerometers are used to study the response, one at the base plate of the shaker second one placed at the top of the inertial amplifier. A force transducer is also placed in between the base plate and the inertial amplifier to calculate the total amount of load transferred from the base plate to the inertial amplifier. The obtained time domain response from the accelerometers have been converted into the frequency domain using the Fast Fourier Transform (FFT) algorithm. The experimental transmittance values are successfully validated with the analytical results, providing us essential confidence in our proposed methodology.

Keywords: inertial amplifier, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers

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Authors: Disha Batra

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The Industrial Revolution 4.0 is quite different, and a paradigm shift is underway in the media industry. With the advent of automated journalism and social media platforms, newspaper organizations have changed the way news was gathered and reported. The emergence of the fourth industrial revolution in the early 21st century has made the newspapers to adapt the changing technologies to remain relevant. This paper investigates the content of Indian business-papers in the era of the fourth industrial revolution and how these organizations have emerged in the time of convergence. The study is the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017 over a decade. The parametric analysis of the different parameters (source of information, use of illustrations, advertisements, layout, and framing, etc.) have been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. Further, this study reveals the effect of high-speed algorithm-based trading, the aftermath of the fourth industrial revolution on the creative and investigative aspect of delivering financial stories by these respective newspapers. The study indicates a change heading towards an ongoing paradigm shift in the business newspaper industry with an adequate change in the source of information gathering along with the subtle increase in the coverage of financial news stories over the time.

Keywords: business-papers, business news, financial news, industrial revolution 4.0.

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Hossein Ghadimi, Alireza Alizadeh, Oveis Abedinia, Noradin Ghadimi

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This paper presents an enhanced Honey Bee Mating Optimization (HBMO) to solve the optimal design of multi machine power system stabilizer (PSSs) parameters, which is called the Interactive Honey Bee Mating Optimization (IHBMO). Power System Stabilizers (PSSs) are now routinely used in the industry to damp out power system oscillations. The design problem of the proposed controller is formulated as an optimization problem and IHBMO algorithm is employed to search for optimal controller parameters. The proposed method is applied to multi-machine power system (MPS). The method suggested in this paper can be used for designing robust power system stabilizers for guaranteeing the required closed loop performance over a prespecified range of operating and system conditions. The simplicity in design and implementation of the proposed stabilizers makes them better suited for practical applications in real plants. The non-linear simulation results are presented under wide range of operating conditions in comparison with the PSO and CPSS base tuned stabilizer one through FD and ITAE performance indices. The results evaluation shows that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers.

Keywords: power system stabilizer, IHBMO, multimachine, nonlinearities

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Authors: José Manue Carvalho Vieira, Mariana Magalhães, Elizabeth Serra

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The Port Wine industry is essential to Portugal because it carries a tangible cultural heritage and for social and economic reasons. Positioned as a luxury product, brands need to pay more attention to the new generation's habits, preferences, languages, and sensory perceptions. Healthy lifestyles, anti-alcohol campaigns, and digitalisation of their buying decision process need to be better understood to understand the wine market in the future. The purpose of this study is to clarify the sensory perception gap between Port Wine descriptors promotion and the new generation's perceptions to help wineries to align their strategies. Based on the interpretivist approach - multiple methods and techniques (mixed-methods), different world views and different assumptions, and different data collection methods and analysis, this research integrated qualitative semi-structured interviews, Port Wine promotion contents, and social media perceptions mined by Sentiment Analysis Enginius algorithm. Findings confirm that Port Wine CEOs' strategies, brands' promotional content, and social perceptions are not sufficiently aligned. The central insight for Port Wine brands' managers is that there is a long and continuous work of understanding and associating their descriptors with the most relevant perceptual values and criteria of their targets to reposition (when necessary) and sustainably revitalise their brands. Finally, this study hypothesised a sensory gap that leads to a decrease in consumption, trying to find recommendations on how to transform it into an advantage for a better attraction towards the young age group (18-25).

Keywords: port wine, consumer habits, sensory gap analysis, wine marketing

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Authors: Jin-Qu Chen, Jie Liu, Yong Yin, Zi-Qi Ju, Yu-Yao Wu

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Increase in travel fare and station’s failure will have huge impact on passengers’ travel. The Urban Rail Transit (URT) station’s accessibility reliability under increasing travel fare and station failure are analyzed in this paper. Firstly, the passenger’s travel path is resumed based on stochastic user equilibrium and Automatic Fare Collection (AFC) data. Secondly, calculating station’s importance by combining LeaderRank algorithm and Ratio of Station Affected Passenger Volume (RSAPV), and then the station’s accessibility evaluation indicators are proposed based on the analysis of passenger’s travel characteristic. Thirdly, station’s accessibility under different scenarios are measured and rate of accessibility change is proposed as station’s accessibility reliability indicator. Finally, the accessibility of Hangzhou metro stations is analyzed by the formulated models. The result shows that Jinjiang station and Liangzhu station are the most important and convenient station in the Hangzhou metro, respectively. Station failure and increase in travel fare and station failure have huge impact on station’s accessibility, except for increase in travel fare. Stations in Hangzhou metro Line 1 have relatively worse accessibility reliability and Fengqi Road station’s accessibility reliability is weakest. For Hangzhou metro operational department, constructing new metro line around Line 1 and protecting Line 1’s station preferentially can effective improve the accessibility reliability of Hangzhou metro.

Keywords: automatic fare collection data, AFC, station’s accessibility reliability, stochastic user equilibrium, urban rail transit, URT

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Authors: Tal Remez, Or Litany, Alex Bronstein

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The pursuit of smaller pixel sizes at ever increasing resolution in digital image sensors is mainly driven by the stringent price and form-factor requirements of sensors and optics in the cellular phone market. Recently, Eric Fossum proposed a novel concept of an image sensor with dense sub-diffraction limit one-bit pixels (jots), which can be considered a digital emulation of silver halide photographic film. This idea has been recently embodied as the EPFL Gigavision camera. A major bottleneck in the design of such sensors is the image reconstruction process, producing a continuous high dynamic range image from oversampled binary measurements. The extreme quantization of the Poisson statistics is incompatible with the assumptions of most standard image processing and enhancement frameworks. The recently proposed maximum-likelihood (ML) approach addresses this difficulty, but suffers from image artifacts and has impractically high computational complexity. In this work, we study a variant of a sensor with binary threshold pixels and propose a reconstruction algorithm combining an ML data fitting term with a sparse synthesis prior. We also show an efficient hardware-friendly real-time approximation of this inverse operator. Promising results are shown on synthetic data as well as on HDR data emulated using multiple exposures of a regular CMOS sensor.

Keywords: binary pixels, maximum likelihood, neural networks, sparse coding

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

Procedia PDF Downloads 139

Authors: Roberto M. G. Velásquez, Jonas R. Gazoli, Nelson Ponce Jr, Valério L. Borges, Alessandro Sete, Fernanda M. C. Tomé, Julian D. Hunt, Heitor C. Lira, Cristiano L. de Souza, Fabio T. Bindemann, Wilmar Wounnsoscky

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Nowadays, society is working toward reducing energy losses and greenhouse gas emissions, as well as seeking clean energy sources, as a result of the constant increase in energy demand and emissions. Energy loss occurs in the gas pressure reduction stations at the delivery points in natural gas distribution systems (city gates). Installing pressure reduction turbines (PRT) parallel to the static reduction valves at the city gates enhances the energy efficiency of the system by recovering the enthalpy of the pressurized natural gas, obtaining in the pressure-lowering process shaft work and generating electrical power. Currently, the Brazilian natural gas transportation network has 9,409 km in extension, while the system has 16 national and 3 international natural gas processing plants, including more than 143 delivery points to final consumers. Thus, the potential of installing PRT in Brazil is 66 MW of power, which could yearly avoid the emission of 235,800 tons of CO2 and generate 333 GWh/year of electricity. On the other hand, an economic viability analysis of these energy efficiency projects is commonly carried out based on estimates of the project's cash flow obtained from several variables forecast. Usually, the cash flow analysis is performed using representative values of these variables, obtaining a deterministic set of financial indicators associated with the project. However, in most cases, these variables cannot be predicted with sufficient accuracy, resulting in the need to consider, to a greater or lesser degree, the risk associated with the calculated financial return. This paper presents an approach applied to the technical-economic viability analysis of PRTs projects that explicitly considers the uncertainties associated with the input parameters for the financial model, such as gas pressure at the delivery point, amount of energy generated by TRP, the future price of energy, among others, using sensitivity analysis techniques, scenario analysis, and Monte Carlo methods. In the latter case, estimates of several financial risk indicators, as well as their empirical probability distributions, can be obtained. This is a methodology for the financial risk analysis of PRT projects. The results of this paper allow a more accurate assessment of the potential PRT project's financial feasibility in Brazil. This methodology will be tested at the Cuiabá thermoelectric plant, located in the state of Mato Grosso, Brazil, and can be applied to study the potential in other countries.

Keywords: pressure reduction turbine, natural gas pressure drop station, energy efficiency, electricity generation, monte carlo methods

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Authors: Olga Blagova, Yuliya Osipova, Evgeniya Kogan, Alexander Nedostup

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Purpose: to quantify the value of various clinical, laboratory and instrumental signs in the diagnosis of myocarditis in comparison with morphological studies of the myocardium. Methods: in 100 patients (65 men, 44.7±12.5 years) with «idiopathic» arrhythmias (n = 20) and dilated cardiomyopathy (DCM, n = 80) were performed 71 endomyocardial biopsy (EMB), 13 intraoperative biopsy, 5 study of explanted hearts, 11 autopsy with virus investigation (real-time PCR) of the blood and myocardium. Anti-heart antibodies (AHA) were also measured as well as cardiac CT (n = 45), MRI (n = 25), coronary angiography (n = 47). The comparison group included of 50 patients (25 men, 53.7±11.7 years) with non-inflammatory heart diseases who underwent open heart surgery. Results. Active/borderline myocarditis was diagnosed in 76.0% of the study group and in 21.6% of patients of the comparison group (p < 0.001). The myocardial viral genome was observed more frequently in patients of comparison group than in study group (group (65.0% and 40.2%; p < 0.01. Evaluated the diagnostic value of noninvasive markers of myocarditis. The panel of anti-heart antibodies had the greatest importance to identify myocarditis: sensitivity was 81.5%, positive and negative predictive value was 75.0 and 60.5%. It is defined diagnostic value of non-invasive markers of myocarditis and diagnostic algorithm providing an individual assessment of the likelihood of myocarditis is developed. Conclusion. The greatest significance in the diagnosis of latent myocarditis in patients with 'idiopathic' arrhythmias and DCM have AHA. The use of complex of noninvasive criteria allows estimate the probability of myocarditis and determine the indications for EMB.

Keywords: myocarditis, "idiopathic" arrhythmias, dilated cardiomyopathy, endomyocardial biopsy, viral genome, anti-heart antibodies

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Authors: Rui Liu, Klaus Greve

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The navigation information is a kind of dynamic geographic information, and the navigation information system is a kind of special geographic information system. At present, there are many researches on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing is not deeply applied into the research of navigation information service. And the imperfection of navigation target coordination and navigation information sharing mechanism under certain navigation tasks has greatly affected the reliability and scientificity of navigation service such as path planning. Considering this, the project intends to study the multi-source information fusion and multi-objective united navigation information interaction mechanism: first of all, investigate the actual needs of navigation users in different areas, and establish the preliminary navigation information classification and importance level model; and then analyze the characteristics of the remote sensing and GIS vector data, and design the fusion algorithm from the aspect of improving the positioning accuracy and extracting the navigation environment data. At last, the project intends to analyze the feature of navigation information of the land, sea and air navigation targets, and design the united navigation data standard and navigation information sharing model under certain navigation tasks, and establish a test navigation system for united navigation simulation experiment. The aim of this study is to explore the theory of united navigation service and optimize the navigation information service model, which will lay the theory and technology foundation for the united navigation of land, sea and air targets.

Keywords: information fusion, united navigation, dynamic path planning, navigation information visualization

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

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Authors: Ruslin, R. E. Kartasasmita, M. S. Wibowo, S. Ibrahim

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An aphrodisiac is a substance contained in food or drug that can arouse sexual instinct and increase pleasure while working, these substances derived from plants, animals, and minerals. When consuming substances that have aphrodisiac activity and duration can improve the sexual instinct. The natural aphrodisiac effect can be obtained through plants, animals, and minerals. Leonurine compound has aphrodisiac activity, these compounds can be isolated from plants of Leonurus Sp, Sundanese people is known as deundereman, this plant is empirical has aphrodisiac activity and based on the isolation of active compounds from plants known to contain compounds leonurine, so that the compound is expected to have activity aphrodisiac. Leonurine compound can be isolated from plants or synthesized chemically with material dasa siringat acid. Leonurine compound can be obtained commercial and derivatives of these compounds can be synthesized in an effort to increase its activity. This study aims to obtain derivatives leonurine better aphrodisiac activity compared with the parent compound, modified the structure of the compounds in the form leonurin guanidino butyl ester group with butyl amin and bromoetanol. ArgusLab program version 4.0.1 is used to determine the binding energy, hydrogen bonds and amino acids involved in the interaction of the compound PDE5 receptor. The in vivo test leonurine compounds and derivatives as an aphrodisiac ingredients and hormone testosterone levels using 27 male rats Wistar strain and 9 female mice of the same species, ages ranged from 12 weeks rats weighing + 200 g / tail. The test animal is divided into 9 groups according to the type of compounds and the dose given. Each treatment group was orally administered 2 ml per day for 5 days. On the sixth day was observed male rat sexual behavior and taking blood from the heart to measure testosterone levels using ELISA technique. Statistical analysis was performed in this study is the ANOVA test Least Square Differences (LSD) using the program Statistical Product and Service Solutions (SPSS). Aphrodisiac efficacy of the leonurine compound and its derivatives have proven in silico and in vivo test, the in silico testing leonurine derivatives have smaller binding energy derivatives leonurine so that activity better than leonurine compounds. Testing in vivo using rats of wistar strain that better leonurine derivative of this compound shows leonurine that in silico studies in parallel with in vivo tests. Modification of the structure in the form of guanidine butyl ester group with butyl amin and bromoethanol increase compared leonurine compound for aphrodisiac activity, testosterone derivatives of compounds leonurine experienced a significant improvement especial is 1RD compounds especially at doses of 100 and 150 mg/bb. The results showed that the compound leonurine and its compounds contain aphrodisiac activity and increase the amount of testosterone in the blood. The compound test used in this study acts as a steroid precursor resulting in increased testosterone.

Keywords: aphrodisiac dysfunction erectile leonurine 1-RD 2-RD, dysfunction, erectile leonurine, 1-RD 2-RD

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

Procedia PDF Downloads 304

Authors: Mostafa Aminzadeh, Min Deng

Abstract:

Modeling loss data is an important part of actuarial science. Actuaries use models to predict future losses and manage financial risk, which can be beneficial for marketing purposes. In the insurance industry, small claims happen frequently while large claims are rare. Traditional distributions such as Normal, Exponential, and inverse-Gaussian are not suitable for describing insurance data, which often show skewness and fat tails. Several authors have studied classical and Bayesian inference for parameters of composite distributions, such as Exponential-Pareto, Weibull-Pareto, and Inverse Gamma-Pareto. These models separate small to moderate losses from large losses using a threshold parameter. This research introduces a computational approach using a nonlinear regression model for loss data that relies on multiple predictors. Simulation studies were conducted to assess the accuracy of the proposed estimation method. The simulations confirmed that the proposed method provides precise estimates for regression parameters. It's important to note that this approach can be applied to datasets if goodness-of-fit tests confirm that the composite distribution under study fits the data well. To demonstrate the computations, a real data set from the insurance industry is analyzed. A Mathematica code uses the Fisher information algorithm as an iteration method to obtain the maximum likelihood estimation (MLE) of regression parameters.

Keywords: maximum likelihood estimation, fisher scoring method, non-linear regression models, composite distributions

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