Search results for: randomized response model

Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

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Authors: Sven Gehrke, Johannes Ruhland

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Data is the oil of our time, without them progress would come to a hold [1]. On the other hand, the mistrust of data mining is increasing [2]. The paper at hand shows different aspects of the concept of trust and describes the information asymmetry of the typical stakeholders of a data mining project using the CRISP-DM phase model. Based on the identified influencing factors in relation to trust, problematic aspects of the current approach are verified using various interviews with the stakeholders. The results of the interviews confirm the theoretically identified weak points of the phase model with regard to trust and show potential research areas.

Keywords: trust, data mining, CRISP DM, stakeholder management

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Authors: Adebayo J. Julius, Oluremi N. Iluyomade

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Livelihood in Nigeria is a paradox of poverty amidst plenty. The Country is endowed with a good climate for agriculture, naturally growing fruit trees and vegetables, and undomesticated water resources. In spite of all its endowment, Nigeria continues to live in poverty year in year out. This thus raises a very important question as to how can there be so much poverty in Nigeria with all its natural endowments. This study focused comparative analysis of the utilization of community informatics for sustainable livelihoods through agriculture. The idea projected in this study is that small strategic changes in the modus operandi of social informatics can have a significant impact on sustainability of livelihoods. This paper carefully explored the theories of community informatics and its efficacies in dealing with sustainability issues. This study identified, described and evaluates the roles of community informatics in some sectors of the economy, different analytical tools to benchmark the influence of social informatics in agriculture against what is obtainable in agricultural sectors of the economy were used. It further employed comparative analysis to build a case model for sustainable livelihood in agriculture through community informatics.

Keywords: informatics , model, rural community, livelihoods sustainability, Nigeria

Procedia PDF Downloads 129

Authors: Victoria Brennan, Andrea Mallaburn, Linda Seton

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Science outreach programmes connect school pupils with external agencies to provide activities and experiences that enhance their exposure to science. It can be argued that these programmes not only aim to support teachers with curriculum engagement and promote scientific literacy but also provide pivotal opportunities to spark scientific interest in students. In turn, a further objective of these programmes is to increase awareness of career opportunities within this field. Although outreach work is also often described as a fun and satisfying venture, a plethora of researchers express caution to how successful the processes are to increases engagement post-16 in science. When researching the impact of outreach programmes, it is often student feedback regarding the activities or enrolment numbers to particular science courses post-16, which are generated and analysed. Although this is informative, the longevity of the programme’s impact could be better informed by the teacher’s perceptions; the evidence of which is far more limited in the literature. In addition, there are strong suggestions that teachers can have an indirect impact on a student’s own self-concept. These themes shape the focus and importance of this ongoing research project as it presents the rationale that teachers are under-used resources when it comes to considering the design of science outreach programmes. Therefore, the end result of the research will consist of a presentation of an ‘optimum’ model of outreach. The result of which should be of interest to the wider stakeholders such as universities or private or government organisations who design science outreach programmes in the hope to recruit future scientists. During phase one, questionnaires (n=52) and interviews (n=8) have generated both quantitative and qualitative data. These have been analysed using the Wilcoxon non-parametric test to compare teachers’ perceptions of science outreach interventions and thematic analysis for open-ended questions. Both of these research activities provide an opportunity for a cross-section of teacher opinions of science outreach to be obtained across all educational levels. Therefore, an early draft of the ‘optimum’ model of science outreach delivery was generated using both the wealth of literature and primary data. This final (ongoing) phase aims to refine this model using teacher focus groups to provide constructive feedback about the proposed model. The analysis uses principles of modified Grounded Theory to ensure that focus group data is used to further strengthen the model. Therefore, this research uses a pragmatist approach as it aims to focus on the strengths of the different paradigms encountered to ensure the data collected will provide the most suitable information to create an improved model of sustainable outreach. The results discussed will focus on this ‘optimum’ model and teachers’ perceptions of benefits and drawbacks when it comes to engaging with science outreach work. Although the model is still a ‘work in progress’, it provides both insight into how teachers feel outreach delivery can be a sustainable intervention tool within the classroom and what providers of such programmes should consider when designing science outreach activities.

Keywords: educational partnerships, science education, science outreach, teachers

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Authors: Ayesha Sanjana Kawser Parsha

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S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Kassahun Zewdie

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-- A field experiment was conducted at Holetta research center and farmers fields during 2017 and 2018 to determine the effects of haulauxifen-methyl + florasulam (QULEX 200 WG) on broadleaf weeds in wheat. The design was a Randomized Complete Block with three replications. The treatments were included haulauxifen-Methyl + florasulam @ 25gm, 50gm and 75gm ha-1, (King-D) 2, 4-D dimethyl amine @1.0 L ha-1, 2, 4-Dichlorophenoxy acetic acid @1.0 L ha-1 rate (standard check), farmers practice twice hand weeding (25-30 and 55-60) days after sowing and weedy check. Herbicides were applied with knapsack sprayer with a spray volume of 200 L ha-1. The wheat variety “Denda” was sown at 20 cm spacing. The recommended rate of fertilizer was applied. Weed density and biomass were recorded at (25-30 and 55-60) days after sowing. The results revealed that post emergence application of haulauxifen-methyl + florasulam @50gm ha-1 had a significant (P<0.05) effect on Guizotia scabra, Polygonum nepalense, Plantago lanceolata, Galinsoga parviflora, Sonchus spp., Galium spurium, Amaranthus hybridus, Raphanus raphanistrum and Medicago polymorpha population. The magnitude ranged from two to four folds when comparing with weed densities recorded in the unweeded plot. The grain yield harvested from the untreated check plot was significantly lower than the rest treatments. The grain yield was improved by 17.3% over the standard check with better performance.

Keywords: broadleaf, grass, weeds, control

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Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Zahir Bakiri, Saci Nacefa

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In this paper a comparison in made between two models, with and without dispersion term, and focused on the characterization of the movement of the sludge blanket in the secondary sedimentation tank using the solid flux theory and the velocity settling. This allowed us develop a one-dimensional models, with and without dispersion based on a thorough experimental study carried out in situ and the application of online data which are the mass load flow, transfer concentration, and influent characteristic. On the other hand, in the proposed model, the new settling velocity law (double-exponential function) used is based on the Vesilind function.

Keywords: wastewater, activated sludge, sedimentation, settling velocity, settling models

Procedia PDF Downloads 371

Authors: Anon Paserakung, Chaloemphon Muangyen, Suban Foiklang, Yanin Opatpatanakit

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Improving nutritive values and digestibility of maize stover is an alternative way to increase their utilization in ruminant and reduce air pollution from open burning of maize stover in the northern Thailand. The present study, 2x3 factorial arrangements in completely randomized design was conducted to investigate the effect of maize stover components (whole and upper stover; cut above 5th node). Urea treatment at levels 0, 3, and 6% DM on dry matter digestibility and fermentation kinetics of maize stover using in vitro gas production. After 21 days of urea treatment, results illustrated that there was no interaction between maize stover components and urea treatment on 48h in vitro dry matter digestibility (IVDMD). IVDMD was unaffected by maize stover components (P > 0.05), average IVDMD was 55%. However, using whole maize stover gave higher cumulative gas and gas kinetic parameters than those of upper stover (P<0.05). Treating maize stover by ensiling with urea resulted in a significant linear increase in IVDMD (P<0.05). IVDMD increased from 42.6% to 53.9% when increased urea concentration from 0 to 3% and maximum IVDMD (65.1%) was observed when maize stover was ensiled with 6% urea. Maize stover treated with urea at levels of 0, 3, and 6% linearly increased cumulative gas production at 96h (31.1 vs 50.5 and 59.1 ml, respectively) and all gas kinetic parameters excepted the gas production from the immediately soluble fraction (P<0.50). The results indicate that maize stover treated with 6% urea enhance in vitro dry matter digestibility and fermentation kinetics. This study provides a practical approach to increasing utilization of maize stover in feeding ruminant animals.

Keywords: maize stover, urea treatment, ruminant feed, gas production

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Authors: S. Boria

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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

Procedia PDF Downloads 243

Authors: Abigail M. Csik, Gabriel A. Radvansky

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As people read through event-based narratives, they construct an event model that captures information about the characters, goals, location, time, and causality. For many reasons, memory for such narratives is represented at different levels, namely, the surface form, textbase, and event model levels. Rereading has been shown to decrease surface form memory, while, at the same time, increasing textbase and event model memories. More generally, distributed practice has consistently shown memory benefits over massed practice for different types of materials, including texts. However, little research has investigated distributed practice of narratives at different inter-study intervals and these effects on these three levels of memory. Recent work in our lab has indicated that there may be dramatic changes in patterns of forgetting around one week, which may affect the three levels of memory. The present experiment aimed to determine the effects of rereading on the three levels of memory as a factor of whether the texts were reread before versus after one week. Participants (N = 42) read a set of stories, re-read them either before or after one week (with an inter-study interval of three days, seven days, or fourteen days), and then took a recognition test, from which the three levels of representation were derived. Signal detection results from this study reveal that differential patterns at the three levels as a factor of whether the narratives were re-read prior to one week or after one week. In particular, an ANOVA revealed that surface form memory was lower (p = .08) while textbase (p = .02) and event model memory (p = .04) were greater if narratives were re-read 14 days later compared to memory when narratives were re-read 3 days later. These results have implications for what type of memory benefits from distributed practice at various inter-study intervals.

Keywords: memory, event cognition, distributed practice, consolidation

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Authors: T. M. Agbede, A. O. Adekiya

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Field experiments were conducted during 2013, 2014 and 2015 cropping seasons at Rufus Giwa Polytechnic, Owo, Ondo State, southwest Nigeria. The objective of the investigation was to determine the effect of Cocoa Pod Ash (CPA) and Poultry Manure (PM) applied solely and their combined form, as sources of fertilizers on soil properties, leaf nutrient composition, growth and yield of yam. Three soil amendments: CPA, PM (sole forms), CPA and PM (mixture), were applied at 20 t ha^-1 with an inorganic fertilizer (NPK 15-15-15) at 400 kg ha^-1 as a reference and a natural soil fertility, NSF (control). The five treatments were arranged in a randomized complete block design with three replications. The test soil was slightly acidic, low in organic carbon (OC), N, P, K, Ca and Mg. Results showed that soil amendments significantly increased (p = 0.05) tuber weights and growth of yam, soil and leaf N, P, K, Ca and Mg, soil pH and OC concentrations compared with the NSF (control). The mixture of CPA+PM treatment increased tuber weights of yam by 36%, compared with inorganic fertilizer (NPK) and 19%, compared with PM alone. Sole PM increased tuber weight of yam by 15%, compared with NPK. Sole or mixed forms of soil amendments showed remarkable improvement in soil physical properties, nutrient availability, compared with NPK and the NSF (control). Integrated application of CPA at 10 t ha^-1 + PM at 10 t ha^-1 was the most effective treatment in improving soil physical properties, increasing nutrient availability and yam performance than sole application of any of the fertilizer materials.

Keywords: cocoa pod ash, leaf nutrient composition, poultry manure, soil properties, yam

Procedia PDF Downloads 305

Authors: Tarek Abdelkader, Suresh Selvaraj, Prasad Iyer, Yong Mun Hin, Hajmath Begum, P. Gopalakrishnakone

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Nowadays, more and more educational institutes, as well as students, rely on 3D anatomy programs as an important tool that helps students correlate the actual locations of anatomical structures in a 3D dimension. Lately, virtual reality (VR) is gaining more favor from the younger generations due to its higher interactive mode. As a result, using virtual reality as a gamified learning platform for anatomy became the current goal. We present a model where a Virtual Human Anatomy Program (VHAP) was developed to assist with the anatomy learning experience of students. The anatomy module has been built, mostly, from real patient CT scans. Segmentation and surface rendering were used to create the 3D model by direct segmentation of CT scans for each organ individually and exporting that model as a 3D file. After acquiring the 3D files for all needed organs, all the files were introduced into a Virtual Reality environment as a complete body anatomy model. In this ongoing experiment, students from different Allied Health orientations are testing the VHAP. Specifically, the cardiovascular system has been selected as the focus system of study since all of our students finished learning about it in the 1st trimester. The initial results suggest that the VHAP system is adding value to the learning process of our students, encouraging them to get more involved and to ask more questions. Involved students comments show that they are excited about the VHAP system with comments about its interactivity as well as the ability to use it solo as a self-learning aid in combination with the lectures. Some students also experienced minor side effects like dizziness.

Keywords: 3D construction, health sciences, teaching pedagogy, virtual reality

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Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: A. D. Rao, Sachiko Mohanty, R. Gayathri, V. Ranga Rao

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Modeling on coupled physical and biogeochemical processes of coastal waters is vital to identify the primary production status under different natural and anthropogenic conditions. About 7, 500 km length of Indian coastline is occupied with number of semi enclosed coastal bodies such as estuaries, inlets, bays, lagoons, and other near shore, offshore shelf waters, etc. This coastline is also rich in wide varieties of ecosystem flora and fauna. Directly/indirectly extensive domestic and industrial sewage enter into these coastal water bodies affecting the ecosystem character and create environment problems such as water quality degradation, hypoxia, anoxia, harmful algal blooms, etc. lead to decline in fishery and other related biological production. The present study is focused on the southeast coast of India, starting from Pulicat to Gulf of Mannar, which is rich in marine diversity such as lagoon, mangrove and coral ecosystem. Three dimensional Massachusetts Institute of Technology general circulation model (MITgcm) along with Darwin biogeochemical module is configured for the western Bay of Bengal (BoB) to study the biogeochemistry over this region. The biogeochemical module resolves the cycling of carbon, phosphorous, nitrogen, silica, iron and oxygen through inorganic, living, dissolved and particulate organic phases. The model domain extends from 4°N-16.5°N and 77°E-86°E with a horizontal resolution of 1 km. The bathymetry is derived from General Bathymetric Chart of the Oceans (GEBCO), which has a resolution of 30 sec. The model is initialized by using the temperature, salinity filed from the World Ocean Atlas (WOA2013) of National Oceanographic Data Centre with a resolution of 0.25°. The model is forced by the surface wind stress from ASCAT and the photosynthetically active radiation from the MODIS-Aqua satellite. Seasonal climatology of nutrients (phosphate, nitrate and silicate) for the southwest BoB region are prepared using available National Institute of Oceanography (NIO) in-situ data sets and compared with the WOA2013 seasonal climatology data. The model simulations with the two different initial conditions viz., WOA2013 and the generated NIO climatology, showed evident changes in the concentration and the evolution of the nutrients in the study region. It is observed that the availability of nutrients is more in NIO data compared to WOA in the model domain. The model simulated primary productivity is compared with the spatially distributed satellite derived chlorophyll data and at various locations with the in-situ data. The seasonal variability of the model simulated primary productivity is also studied.

Keywords: Bay of Bengal, Massachusetts Institute of Technology general circulation model, MITgcm, biogeochemistry, primary productivity

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Authors: Nurlisa Uke Dessy, Dwi Septian Erwinsyah, Zuprizal

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This experiment was aimed to investigate the effect of rosella flower flour in diet on broiler chicken Performace. The materials used in this experiment were 72 broiler chickens and were divided into six treatments, those were R0 = without rosella flower flour addition, R1 = 0.5% rosella flower flour addition, R2 = 1.0% rosella flower flour addition, R3 = 1.5% rosella flower flour addition, R4 = 2.0% rosella flower flour addition, and R5 = 2.5% rosella flower flour addition. Each treatment consisted of three replications and each replication consisted of four broiler chickens. This research took 35 days to collect the data. Parameters measured were feed intake, rosella flower flour consumption, body weight gain, feed conversion and mortality. The collected data were analyzed using Completely Randomized Design (CRD) and the differences of mean were tested by Duncan’s New Multiple Range Test (DMRT). The result showed the average of feed consumption were 2154; 2154; 2034; 2154; 2034 and 2154 g/bird on broiler chicken that were feed respectively by 0.0; 0.5; 1.0; 1.5; 2.0; and 2.5% rosella flower flour level. The average consumptions of rosella flower flour respectively were 0; 10.77; 20.34; 32.31; 40.68; and 53.85 g/bird. The body weight gains were 1263.33±70.40; 1422.42±36.33; 1443.75±30.00; 1387.42± 35.30; 1411.17±29.58 and 1457.08±40.75 g/bird. Feed conversion results were 1.71±0.94; 1.51±0.37; 1.47±0.62; 1.55±0.40; 1.53±0.30 and 1.48±0.40. The conclusion of the experiment was known that using rosella flower flour until 2.5% level in diet was able to increase broiler chicken performance, and also to decrease broiler chicken feed conversion.

Keywords: feed intake, consumptions rosella flower flour, broiler chickens, body weight gain, feed conversion

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Authors: J. M. Uriarte, H. R. Guemez, J. A. Romo, R. Barajas, J. M. Romo

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This research was carried out with the objective of knowing the productive performance of sows in lactation when fed with diets containing cull chickpea instead of corn and soybean meal. Thirty-six (Landrace x Yorkshire) lactating sows were divided into three treatments with 12 sows per treatment. On day 107 of gestation, sows were moved into farrowing crates in an environmentally regulated (2.2 × 0.6 m) contained an area (2.2 × 0.5 m) for newborn pigs on each side, all diets were provided as a dry powder, and the sows received free access to water throughout the experimental period. After farrowing, daily feed allowance increased gradually, and sows had ad libitum access to feed by day four. They were fed diets containing 0 (CONT), cull chickpeas 15 % (CHP15), or cull chickpeas 30% (CHP30) for 28 days. The diets contained the same calculated levels of crude protein and metabolizable energy, and contained vitamins and minerals that exceeded the National Research Council (1998) recommendations; sows were fed three times daily. On day 28, piglets were weaned and performances of lactating sows and nursery piglets were recorded. All data in this experiment were analyzed in accordance with a completely randomized design. Results indicated that average daily feed intake (5.61, 5.59 and 5.46 kg for CONT, CHP15, and CHP30 respectively) of sows were not affected (P > 0.05) by different dietary. There was no difference (P > 0.05) in average body weight of piglets on the day of birth (1.35 vs. 1.30, and 1.32 kg) and day 28 (7.10, 6.80 and 6.92 kg) between treatments. The numbers of weaned piglets (10.65 on average) were not affected by treatments. It is concluded that the use of cull chickpea at 30% of the diet does not affect the productive performance of lactating sows.

Keywords: cull chickpea, lactating sow, performance, pigs

Procedia PDF Downloads 126

Authors: Fikru Fentaw Abera

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Climate changes alter regional hydrologic conditions and results in a variety of impacts on water resource systems. Such hydrologic changes will affect almost every aspect of human well-being. The goal of this paper is to assess the impact of climate change on the hydrology of Upper Guder catchment located in northwest of Ethiopia. The GCM derived scenarios (HadCM3 A2a & B2a SRES emission scenarios) experiments were used for the climate projection. The statistical downscaling model (SDSM) was used to generate future possible local meteorological variables in the study area. The down-scaled data were then used as input to the soil and water assessment tool (SWAT) model to simulate the corresponding future stream flow regime in Upper Guder catchment of the Abay River Basin. A semi distributed hydrological model, SWAT was developed and Generalized Likelihood Uncertainty Estimation (GLUE) was utilized for uncertainty analysis. GLUE is linked with SWAT in the Calibration and Uncertainty Program known as SWAT-CUP. Three benchmark periods simulated for this study were 2020s, 2050s and 2080s. The time series generated by GCM of HadCM3 A2a and B2a and Statistical Downscaling Model (SDSM) indicate a significant increasing trend in maximum and minimum temperature values and a slight increasing trend in precipitation for both A2a and B2a emission scenarios in both Gedo and Tikur Inch stations for all three bench mark periods. The hydrologic impact analysis made with the downscaled temperature and precipitation time series as input to the hydrological model SWAT suggested for both A2a and B2a emission scenarios. The model output shows that there may be an annual increase in flow volume up to 35% for both emission scenarios in three benchmark periods in the future. All seasons show an increase in flow volume for both A2a and B2a emission scenarios for all time horizons. Potential evapotranspiration in the catchment also will increase annually on average 3-15% for the 2020s and 7-25% for the 2050s and 2080s for both A2a and B2a emissions scenarios.

Keywords: climate change, Guder sub-basin, GCM, SDSM, SWAT, SWAT-CUP, GLUE

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Authors: Tasnuba Binte Jamal, Khan Mahmud Amanat

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Carbon Fiber-Reinforced Polymer (CFRP) composite materials have proven to have valuable properties and suitability to be used in the construction of new buildings and in upgrading the existing ones due to its effectiveness, ease of implementation and many more. In the present study, a numerical finite element investigation has been conducted using ANSYS 18.1 to study the behavior of square HSS AISC sections under eccentric compressive loading strengthened with CFRP materials. A three-dimensional finite element model for square HSS section using shell element was developed. Application of CFRP strengthening was incorporated in the finite element model by adding an additional layer of shell elements. Both material and geometric nonlinearities were incorporated in the model. The developed finite element model was applied to simulate experimental studies done by past researchers and it was found that good agreement exists between the current analysis and past experimental results, which established the acceptability and validity of the developed finite element model to carry out further investigation. Study was then focused on some selected non-compact AISC square HSS columns and the effects of number of CFRP layers, amount of eccentricities and cross-sectional geometry on the strength gain of those columns were observed. Load was applied at a distance equal to the column dimension and twice that of column dimension. It was observed that CFRP strengthening is comparatively effective for smaller eccentricities. For medium sized sections, strengthening tends to be effective at smaller eccentricities as well. For relatively large AISC square HSS columns, with increasing number of CFRP layers (from 1 to 3 layers) the gain in strength is approximately 1 to 38% to that of unstrengthened section for smaller eccentricities and slenderness ratio ranging from 27 to 54. For medium sized square HSS sections, effectiveness of CFRP strengthening increases approximately by about 12 to 162%. The findings of the present study provide a better understanding of the behavior of HSS sections strengthened with CFRP subjected to eccentric compressive load.

Keywords: CFRP strengthening, eccentricity, finite element model, square hollow section

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

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

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

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Authors: H. Tanyildizi, M. Abuqebitah, I. Cavdar, M. Demir, L. Kabasakal

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Aim: Whole liver radiation has the modest benefit in the treatment of unresectable hepatic metastases but the radiation doses must keep in control. Otherwise, RILD complications may arise. In this study, we aimed to calculate amount of maximum permissible activity (MPA) and critical organ absorbed doses with MIRD methodology, to evaluate tumour doses for treatment response and whole liver doses for RILD and to find optimal liver function test additionally. Materials and Methods: This study includes 29 patients who attended our nuclear medicine department suffering from Y-90 microspheres treatment. 10 mCi Tc-99m MAA was applied to the patients for dosimetry via IV. After the injection, whole body SPECT/CT images were taken in one hour. The minimum therapeutic tumour dose is on the point of being 120 Gy1, the amount of activities were calculated with MIRD methodology considering volumetric tumour/liver rate. A sub-working group was created with 11 patients randomly and liver clearance rate with Tc-99m-Mebrofenin was calculated according to Ekman formalism. Results: The volumetric tumour/liver rates were found between 33-66% (Maksimum Tolarable Dose (MTD) 48-52Gy3) for 4 patients, were found less than 33% (MTD 72Gy3) for 25 patients. According to these results the average amount of activity, mean liver dose and mean tumour dose were found 1793.9±1.46 MBq, 32.86±0.19 Gy, and 138.26±0.40 Gy. RILD was not observed in any patient. In sub-working group, the relationship between Bilirubin, Albumin, INR (which show presence of liver disease and its degree), liver clearance with Tc-99m-Mebrofenin and calculated activity amounts were found r=0.49, r=0.27, r=0.43, r=0.57, respectively. Discussions: The minimum tumour dose was found 120 Gy for positive dose-response relation. If volumetric tumour/liver rate was > 66%, dose 30 Gy; if volumetric tumour/liver rate 33-66%, dose escalation 48 Gy; if volumetric tumour/liver rate < 33%, dose 72 Gy. These dose limitations did not create RILD. Clearance measurement with Mebrofenin was concluded that the best method to determine the liver function. Therefore, liver clearance rate with Tc-99m-Mebrofenin should be considered in calculation of yttrium-90 microspheres dosimetry.

Keywords: clearance, dosimetry, liver, RILD

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Authors: Ghazal Zahed, Leila Tabatabaee, Amirhossein Hosseini, Somaye Fatahi

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Functional retentive overflow incontinence (Retentive FI) is the most common cause of fecal soiling in children. Affected patients may have more problems with their parents and peer group, self-esteem issues, and more psychiatric comorbidities than the general population. Therapeutic interventions for Retentive FI and related problems and comorbid conditions are needed at the same time. Based on the clinical experiences, patients with retentive FI and comorbid psychiatric disorders, were accelerated in their treatment of fecal incontinence when they were being treated with Risperidone for their psychiatric comorbidities, therefore this study was conducted to evaluate the effect of Risperidone in the treatment of Retentive FI in children and adolescents. In this double-blind randomized clinical trial, 136 patients aged 4-18 years eligible for the study were randomly divided into two groups receiving Risperidone and placebo. About half of these patients had newly diagnosed psychiatric disorders and were drug naïve, this was considered in their division. In addition to polyethylene glycol, all the participants received family counseling and education for withholding behaviors and related behavioral interventions, and nonpharmacological interventions for psychiatric comorbidities. A significant correlation was observed between the duration of treatment with risperidone and the presence of psychiatric comorbidities (P <0.001) for diurnal fecal incontinence. Based on our findings in this study, Risperidone, used commonly for psychiatric disorders in children and adolescents, may be useful in the treatment of retentive fecal incontinence in the presence of psychiatric comorbidities, and along with other interventions.

Keywords: Retentive Fecal Incontinence, Risperidone, Treatment, Pediatric, Encopresis, Atypical Antipsychotics, Fecal Soiling

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Authors: Ping Chou, Xiaoyan Zhou

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Domestically and internationally, the Chinese education has long been criticized for being test-oriented, and in spite of efforts made by the Chinese government, it remains hard to find a solution. This paper intends to look at the situation in a comparatively objective manner and discuss the significance of the Shanghai Model as a newly-scheduled experiment for education reform. As a breakthrough, in addition to comprehensive inner-quality evaluation, a small but important step is to be taken in shifting focus of attention back to students by giving them more freedom in selecting certain courses for aptitude tests for college admission. As the first author of the paper has studied and taught both in Chinese and American colleges and universities, comparisons are made when the situation becomes relevant. The official solution for test-oriented education is to make students well-rounded but the writers of this paper believe that it is even more important to make the system well-rounded so it can accept a spectrum of diverse individuals with different potential.

Keywords: college admission, education reform, Shanghai model, test-oriented education

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Authors: Kaycee Bills

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This study will determine if students with disabilities have higher student loan debt payments than other student populations. The hypothesis was that students with disabilities would have significantly higher student loan debt payments than other students due to the length of time they spend in school. Using the Bachelorette and Beyond Study Wave 2015/017 dataset, quantitative methods were employed. These data analysis methods included linear regression and a correlation matrix. Due to the exploratory nature of the study, the significance levels for the overall model and each variable were set at .05. The correlation matrix demonstrated that students with certain types of disabilities are more likely to fall under higher student loan payment brackets than students without disabilities. These results also varied among the different types of disabilities. The result of the overall linear regression model was statistically significant (p = .04). Despite the overall model being statistically significant, the majority of the significance values for the different types of disabilities were null. However, several other variables had statistically significant results, such as veterans, people of minority races, and people who attended private schools. Implications for how this impacts the economy, capitalism, and financial wellbeing of various students are discussed.

Keywords: disability, student loan debt, higher education, social work

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Authors: Ignatio Madanhire, Charles Mbohwa

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This study looks at the best model of aggregate planning activity in an industrial entity and uses the trial and error method on spreadsheets to solve aggregate production planning problems. Also linear programming model is introduced to optimize the aggregate production planning problem. Application of the models in a furniture production firm is evaluated to demonstrate that practical and beneficial solutions can be obtained from the models. Finally some benchmarking of other furniture manufacturing industries was undertaken to assess relevance and level of use in other furniture firms

Keywords: aggregate production planning, trial and error, linear programming, furniture industry

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Authors: Hideyuki Shintani, Ichiro Koshijima

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In Cyber Physical System (CPS), if there are a large number of persons in the process, a role of person in CPS might be different comparing with the one-man system. It is also necessary to consider how Human-in-The-Loop Cyber Physical Systems (HiTLCPS) ensure safety of each person in the loop process. In this paper, the authors discuss a system safety framework with an illustrative example with STAMP model to clarify what point for safety should be considered and what role of person in the should have.

Keywords: cyber-physical-system, human-in-the-loop, safety, STAMP model

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Authors: Silvia Platania, Martina Morando, Giuseppe Santisi

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Introduction: In the last thirty years, there is constant talk of sustainable consumption and a "transition" of consumer lifestyles towards greater awareness of consumer choices (United Nation, 1992). The 2019 coronavirus (COVID-19) epidemic that has hit the world population since 2020 has had significant consequences in all areas of people's lives; individuals have been forced to change their behaviors, to redefine their owngoals, priorities, practices, and lifestyles, to rebuild themselves in the new situation dictated by the pandemic. Method(Participants and procedure ): The data were collected through an online survey; moreover, we used convenience sampling from the general population. The participants were 669 Italians consumers (Female= 514, 76.8%; Male=155, 23.2%) that choice sustainability brands, aged between 18 and 65 years (Mₐ𝓰ₑ = 35.45; Standard Deviation, SD = 9.51).(Measure ): The following measures were used: The Muncy–Vitell Consumer Ethics Scale; Attitude Toward Business Scale; Perceived Consumer Effectiveness Scale; Consumers Perception on Sustainable Brand Attitudes. Results: Preliminary analyses were conducted to test our model. Pearson's bivariate correlation between variables shows that all variables of our model correlate significantly and positively, PCE with CPSBA (r = .56, p <.001). Furthermore, a CFA, according to Harman's single-factor test, was used to diagnose the extent to which common-method variance was a problem. A comparison between the hypothesised model and a model with one factor (with all items loading on a unique factor) revealed that the former provided a better fit for the data in all the CFA fit measures [χ² [6, n = 669] = 7.228, p = 0.024, χ² / df = 1.20, RMSEA = 0.07 (CI = 0.051-0.067), CFI = 0.95, GFI = 0.95, SRMR = 0.04, AIC = 66.501; BIC = 132,150). Next, amulti mediation was conducted to test our hypotheses. The results show that there is a direct effect of PCE on ethical consumption behavior (β = .38) and on ATB (β = .23); furthermore, there is a direct effect on the CPSBA outcome (β = .34). In addition, there is a mediating effect by ATB (C.I. =. 022-.119, 95% interval confidence) and by CES (C.I. =. 136-.328, 95% interval confidence). Conclusion: The spread of the COVID-19 pandemic has affected consumer consumption styles and has led to an increase in online shopping and purchases of sustainable products. Several theoretical and practical considerations emerge from the results of the study.

Keywords: decision making, sustainability, pandemic, multimediation model

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Authors: Kwok W. Cheung

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A scientific interpretation of creation reconciling the beliefs of six literal days of creation and a 13.7-billion-year-old universe currently perceived by most modern cosmologists is proposed. We hypothesize that the reference timeframe of God’s creation is associated with some cosmic time different from the earth's time. We show that the scale factor of earth time to cosmic time can be determined by the solution of the Friedmann equations. Based on this scale factor and some basic assumptions, we derive a Cosmic Time Dilation model that harmonizes the literal meaning of creation days and scientific discoveries with remarkable accuracy.

Keywords: cosmological expansion, time dilation, creation, genesis, relativity, Big Bang, biblical hermeneutics

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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