Search results for: daily probability model

Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

Procedia PDF Downloads 658

Authors: A. Drapeaux, S. Aviles, E. Garfoot

Abstract:

Stem cell injections are a promising alternative treatment for hip osteoarthritis. Current literature has focused on short-term outcomes for both knee and hip osteoarthritis; however, there is a significant gap for longitudinal benefits for hip OA and limited firm conclusions due to small sample sizes. The purpose of this prospective study was to determine longitudinal changes in pain, function, and radiographs following bone marrow concentrate injection (BMAC) into the osteoarthritic hip joint. Methods: A prospective, cross-sectional study was conducted over the course of 12 months at an orthopedic practice. The study recruited 15 osteoarthritic pre-surgical hips with mild to moderate osteoarthritic severity who were scheduled to undergo hip arthroscopy. Data was collected at both pre-operative and post-operative time frames. Data collected included: hip radiographs, i-HOT-33 questionnaire data, BMAC autologous volume, and demographics. Questionnaire data was captured using Qualtrics XM software, and participants were sent an anonymous link at the following time frames: pre-operative, 2 weeks, 6 weeks, 12 weeks, 6 months, 12 months, and 24 months. Radiographic changes and BMAC volume were collected and reviewed by an orthopedic surgeon and sent to the primary investigator. Data was exported and analyzed in IBM-SPSS. Results: A total of 15 hips from 15 participants (mean age: 49, gender: 50% males, 50% females, BMI: 29.7) were used in the final analysis. Summative i-HOT 33 mean scores significantly changed between pre-operative status and 2-6 weeks post-operative status (p <.001) and pre-operative status and 3-6 months post-operative status (p <.001). There were no significant changes between other post-operative phases or between pre-operative status and 12 months post-operative. Significant improvements were found between summative i-HOT 33 mean (p<.001), daily pain (p<.001), daily sitting (p=.02), daily distance walked (p =.003), and daily limp (p=0.03) and post-operative status (2-6 weeks). No significant differences between demographic variables (gender, age, tobacco use, or diabetes) and i-HOT 33 summative mean scores. Discussion/Implications: The purpose of this study was to determine longitudinal changes in pain and function following a hip joint bone marrow concentrate injection. Results indicate that participants experience a significant improvement in pain and function between pre-operative and 2-6 weeks and 3-6 months post-injection. Participants also self-reported a significant change in average daily pain with sitting and walking between pre-operation and 2-6 weeks post-operative. This study includes a larger sample size of hip osteoarthritis cases; however, future research is warranted to include random controlled trials with a larger sample size.

Keywords: adult stem cell, orthopedics, osteoarthritis (hip), patient outcome assessment

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Authors: Hugo F. Lobaton

Abstract:

The cyanobacterium Spirulina platensis is a prokaryotic photoautotrophic microorganism that is successfully cultivated for the commercialization as whole biomass due to its high protein content and promising valuable substance. For instance, phycocyanin has recently drawn the interest of the food and cosmetic industries due to its bright blue colour and its strong antioxidant capacities. The phycocyanin (PC) is the main protein-pigment in S. platensis (4% to 20%). In batches, the rate of overproduction of metabolites by cyanobacteria is limited or activated by the depletion of required substrates. The aim of this study was to develop a kinetic law that describes phycocyanin formation during batch cultivation. S. platensis was cultivated in 1 L bubble column photobioreactor with 30°C and 700 µmol m⁻² s⁻¹. Culture samples were daily collected from the bubble columns in sterile conditions. The biomass (g l⁻¹) was measured directly after a biomass lyophilisation process, and phycocyanin extractions and measurements were done according to a well-established protocol. A kinetic law for phycocyanin formation that includes nitrate and bicarbonate limitations was proposed and linked to the biomass core model. The set of differential equations were solved in MATLAB. Concerning to product formation, the experimental results show that phycocyanin mass fraction is degraded as results of the complete nitrate depletion and nitrate additions during the cultivation help to keep constant this molecule until new macro-element limitation appear. According to the model, bicarbonate is this limitation.

Keywords: phycocyanin, nitrate, bicarbonate, spirulina

Procedia PDF Downloads 146

Authors: Noushin Naraghi Araghi, M. Nawawi, Syed Mustafizur Rahman

Abstract:

This paper presents the effect of Sumatra fault earthquakes on west Malaysia by calculating the peak horizontal ground acceleration (PGA). PGA is calculated by a probabilistic seismic hazard assessment (PSHA). A uniform catalog of earthquakes for the interest region has been provided. We used empirical relations to convert all magnitudes to Moment Magnitude. After eliminating foreshocks and aftershocks in order to achieve more reliable results, the completeness of the catalog and uncertainty of magnitudes have been estimated and seismicity parameters were calculated. Our seismic source model considers the Sumatran strike slip fault that is known historically to generate large earthquakes. The calculations were done using the logic tree method and four attenuation relationships and slip rates for different part of this fault. Seismic hazard assessment carried out for 48 grid points. Eventually, two seismic hazard maps based PGA for 5% and 10% probability of exceedance in 50 year are presented.

Keywords: Sumatra fault, west Malaysia, PGA, seismic parameters

Procedia PDF Downloads 404

Authors: Claus N. Holm, Oliver F. Grooss, Robert A. Alphinas

Abstract:

This research strives to predict the remaining product life cycle of a song on radio after it has been played for one or two months. The best results were achieved using a k-d tree to calculate the most similar songs to the test songs and use a Random Forest model to forecast radio plays. An 82.78% and 83.44% accuracy is achieved for the two time periods, respectively. This explorative research leads to over 4500 test metrics to find the best combination of models and pre-processing techniques. Other algorithms tested are KNN, MLP and CNN. The features only consist of daily radio plays and use no musical features.

Keywords: hit song science, product life cycle, machine learning, radio

Procedia PDF Downloads 155

Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

Abstract:

The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

Procedia PDF Downloads 516

Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

Abstract:

Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

Procedia PDF Downloads 77

Authors: Matthew C. Best

Abstract:

Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

Procedia PDF Downloads 594

Authors: Suzan Sayegh, Izzeldin Ibrahim, Mercia Van Der Walt, Mohamed Al-Kuwari

Abstract:

Background: Walking is the most common form of physical activity which can promote a healthy well-being among people of different age groups. In this regard, pedometers are becoming more popular within research and are considered useful tools in monitoring physical activity levels based on individuals’ daily steps. A value of ˂5,000 steps/day is identified as a sedentary lifestyle index where individuals are physically inactive. Those achieving 5,000-7,499 steps/day have a low active lifestyle as they do not meet the moderate-to-vigorous physical activity (MVPA) recommendations. Moreover, individuals achieving ≥7,500 steps/day are classified as physically active. The objective of this study is to assess the physical activity levels of adult population in Qatar through a pedometer-based program over a one-year period. Methods: A cross-sectional analysis, as part of a longitudinal study, was carried out over one year to assess the daily step count. “Step into Health” is a community-based program launched by Aspire as an approach for the purpose of improving physical activity across the population of Qatar. The program involves distribution of pedometers to registered members which is supported by a self-monitoring online account and linked to a web database. Daily habitual physical activity (daily total step count) was assessed through Omron HJ-324U pedometer. Analyses were done on data extracted from the web database. Results: A total of 1,988 members were included in this study (males: n=1,143, 57%; females: n=845, 43%). Average age was 37.8±10.9 years distributed as 60% of age between age 25-54 (n=1,186), 27% of age 45-64 (n=546), and 13% of age 18-24 years (n=256). Majority were non-Qataris, 81% (n=1,609) compared with 19% of the Qatari nationality (n=379). Average body mass index (BMI) was 27.8±6.1 (kg/m2) where most of them (41%, n=809) were found to be overweight, between 25-30 kg/m2. Total average step count was 5,469±3,884. Majority were found to be sedentary (n=1110, 55.8%). Middle aged individuals were more active than the other two age groups. Males were seen as more active than females. Those who were less active had a higher BMI. Older individuals were more active. There was a variation in the physical activity level throughout the year period. Conclusion: It is essential to further develop the available intervention programs and increase their physical activity behavior. Planning such physical activity interventions for female population should involve aspects such as time, environmental variables and aerobic steps.

Keywords: adults, pedometer, physical activity, step-count

Procedia PDF Downloads 361

Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

Procedia PDF Downloads 372

Authors: Hagos Abraham, Solomon Gizaw, Mengistu Urge

Abstract:

A sound breeding objective is the basis for genetic improvement in overall economic merit of farm animals. Begait goat is one of the identified breeds in Ethiopia, which is a multipurpose breed as it serves as source of cash income and source of food (meat and milk). Despite its importance, no formal breeding objectives exist for Begait goat. The objective of the present study was to identify breeding objectives for the breed through two approaches: using own-flock ranking experiment and developing deterministic bio-economic models as a preliminary step towards designing sustainable breeding programs for the breed. In the own-flock ranking experiment, a total of forty five households were visited at their homesteads and were asked to select, with reasons, the first best, second best, third best and the most inferior does from their own flock. Age, previous reproduction and production information of the identified animals were inquired; live body weight and some linear body measurements were taken. The bio-economic model included performance traits (weights, daily weight gain, kidding interval, litter size, milk yield, kid mortality, pregnancy and replacement rates) and economic (revenue and costs) parameters. It was observed that there was close agreement between the farmers’ ranking and bio-economic model results. In general, the results of the present study indicated that Begait goat owners could improve performance of their goats and profitability of their farms by selecting for litter size, six month weight, pre-weaning kid survival rate and milk yield.

Keywords: bio-economic model, economic parameters, own-flock ranking, performance traits

Procedia PDF Downloads 67

Authors: Tejush Badal, Sanaa Alwidian

Abstract:

Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

Procedia PDF Downloads 74

Authors: Farzam Fatolazadeh, Kalifa Goita, Mehdi Eshagh, Shusen Wang

Abstract:

The Gravity Recovery and Climate Experiment (GRACE) is a satellite mission with twin satellites for the precise determination of spatial and temporal variations in the Earth’s gravity field. The products of this mission are monthly global gravity models containing the spherical harmonic coefficients and their errors. These GRACE models can be used for estimating terrestrial water storage (TWS) variations across the globe at large scales, thereby offering an opportunity for surface and groundwater storage (GWS) assessments. Yet, the ability of GRACE to monitor changes at smaller scales is too limited for local water management authorities. This is largely due to the low spatial and temporal resolutions of its models (~200,000 km2 and one month, respectively). High-resolution GRACE data products would substantially enrich the information that is needed by local-scale decision-makers while offering the data for the regions that lack adequate in situ monitoring networks, including northern parts of Canada. Such products could eventually be obtained through downscaling. In this study, we extended the spectral combination theory to simultaneously downscale spatiotemporally the 3o spatial coarse resolution of GRACE to 0.25o degrees resolution and monthly coarse resolution to daily resolution. This method combines the monthly gravity field solution of GRACE and daily hydrological model products in the form of both low and high-frequency signals to produce high spatiotemporal resolution TWSA and GWSA products. The main contribution and originality of this study are to comprehensively and simultaneously consider GRACE and hydrological variables and their uncertainties to form the estimator in the spectral domain. Therefore, it is predicted that we reach downscale products with an acceptable accuracy.

Keywords: GRACE satellite, groundwater storage, spectral combination, terrestrial water storage

Procedia PDF Downloads 83

Authors: Yagya Murti Aryal, Bipin Adhikari, Pradeep Gyawali

Abstract:

The Lesser Himalaya zone of Nepal consists of thrusting and folding belts, which play an important role in the sustainable management of groundwater in the Himalayan regions. The study area is located in the Dolakha and Ramechhap Districts of Bagmati Province, Nepal. Geologically, these districts are situated in the Lesser Himalayas and partly encompass the Higher Himalayan rock sequence, which includes low-grade to high-grade metamorphic rocks. Following the Gorkha Earthquake in 2015, numerous springs dried up, and many others are currently experiencing depletion due to the distortion of the natural groundwater flow. The primary objective of this study is to identify potential groundwater areas and determine suitable sites for artificial groundwater recharge. Two distinct statistical approaches were used to develop models: The Frequency Ratio (FR) and Shannon Entropy (SE) methods. The study utilized both primary and secondary datasets and incorporated significant role and controlling factors derived from field works and literature reviews. Field data collection involved spring inventory, soil analysis, lithology assessment, and hydro-geomorphology study. Additionally, slope, aspect, drainage density, and lineament density were extracted from a Digital Elevation Model (DEM) using GIS and transformed into thematic layers. For training and validation, 114 springs were divided into a 70/30 ratio, with an equal number of non-spring pixels. After assigning weights to each class based on the two proposed models, a groundwater potential map was generated using GIS, classifying the area into five levels: very low, low, moderate, high, and very high. The model's outcome reveals that over 41% of the area falls into the low and very low potential categories, while only 30% of the area demonstrates a high probability of groundwater potential. To evaluate model performance, accuracy was assessed using the Area under the Curve (AUC). The success rate AUC values for the FR and SE methods were determined to be 78.73% and 77.09%, respectively. Additionally, the prediction rate AUC values for the FR and SE methods were calculated as 76.31% and 74.08%. The results indicate that the FR model exhibits greater prediction capability compared to the SE model in this case study.

Keywords: groundwater potential mapping, frequency ratio, Shannon’s Entropy, Lesser Himalaya Zone, sustainable groundwater management

Procedia PDF Downloads 81

Authors: Alejandro Rodríguez-Molinero, Carlos Pérez-López, Jorge Hernández-Vara, Àngels Bayes-Rusiñol, Juan Carlos Martínez-Castrillo, David A. Pérez-Martínez

Abstract:

Background: Monitoring motor symptoms in Parkinson's patients is often a complex and time-consuming task for clinicians, as Hauser's diaries are often poorly completed by patients. Recently, new automatic devices (Parkinson's holter: STAT-ON®) have been developed capable of monitoring patients' motor fluctuations. The MoMoPa-EC clinical trial (NCT04176302) investigates which of the two methods produces better clinical results. In this sub-analysis, the concordance between both methods is analyzed. Methods: In the MoMoPa-EC clinical trial, 164 patients with moderate-severe Parkinson's disease and at least two hours a day of Off will be included. At the time of patient recruitment, all of them completed a seven-day motor fluctuation diary at home (Hauser’s diary) while wearing the Parkinson's holter. In this sub-analysis, 71 patients with complete data for the purpose of this comparison were included. The intraclass correlation coefficient was calculated between the patient diary entries and the Parkinson's holter data in terms of time On, Off, and time with dyskinesias. Results: The intra-class correlation coefficient of both methods was 0.57 (95% CI: 0.3-0.74) for daily time in Off (%), 0.48 (95% CI: 0.14-0.68) for daily time in On (%), and 0.37 (95% CI %: -0.04-0.62) for daily time with dyskinesias (%). Conclusions: Both methods have a moderate agreement with each other. We will have to wait for the results of the MoMoPa-EC project to estimate which of them has the greatest clinical benefits. Acknowledgment: This work is supported by AbbVie S.L.U, the Instituto de Salud Carlos III [DTS17/00195], and the European Fund for Regional Development, 'A way to make Europe'.

Keywords: Parkinson, sensor, motor fluctuations, dyskinesia

Procedia PDF Downloads 232

Authors: Souzan Al Sayegh, Izzeldin Ibrahim, Mercia Van Der Walt, Mohamed Al-Kuwari

Abstract:

Background: Walking is the most common form of physical activity which can promote a healthy well-being among people of different age groups. In this regard, pedometers are becoming more popular within research and are considered useful tools in monitoring physical activity levels based on individuals’ daily steps. A value of ˂5,000 steps/day is identified as a sedentary lifestyle index where individuals are physically inactive. Those achieving 5,000-7,499 steps/day have a low active lifestyle as they do not meet the moderate-to-vigorous physical activity (MVPA) recommendations. Moreover, individuals achieving ≥7,500 steps/day are classified as physically active. The objective of this study is to assess the physical activity levels of adult population in Qatar through a pedometer-based program over a one-year period. Methods: A cross-sectional analysis, as part of a longitudinal study, was carried out over one year to assess the daily step count. 'Step into Health' is a community-based program launched by Aspire as an approach for the purpose of improving physical activity across the population of Qatar. The program involves the distribution of pedometers to registered members which is supported by a self-monitoring online account and linked to a web database. Daily habitual physical activity (daily total step count) was assessed through Omron HJ-324U pedometer. Analyses were done on data extracted from the web database. Results: A total of 1,988 members were included in this study (males: n=1,143, 57%; females: n=845, 43%). Average age was 37.8±10.9 years distributed as 60% of age between age 25-54 (n=1,186), 27% of age 45-64 (n=546), and 13% of age 18-24 years (n=256). Majority were non-Qataris, 81% (n=1,609) compared with 19% of the Qatari nationality (n=379). Average body mass index (BMI) was 27.8±6.1 (kg/m2) where most of them (41%, n=809) were found to be overweight, between 25-30 kg/m2. Total average step count was 5,469±3,884. Majority were found to be sedentary (n=1110, 55.8%). Middle aged individuals were more active than the other two age groups. Males were seen as more active than females. Those who were less active had a higher BMI. Older individuals were more active. There was a variation in the physical activity level throughout the year period. Conclusion: It is essential to further develop the available intervention programs and increase their physical activity behavior. Planning such physical activity interventions for female population should involve aspects such as time, environmental variables and aerobic steps.

Keywords: adults, pedometer, physical activity, step-count

Procedia PDF Downloads 306

Authors: Xinhai Li, Huidong Tian, Yumin Guo

Abstract:

Bird migration is fantastic natural phenomenon. In recent years, the use of GPS transmitters has generated a vast amount of data, and the Movebank platform has made these data publicly accessible. For researchers, what they need are data analysis tools. Although there are approximately 90 R packages dedicated to animal movement analysis, the capacity for comprehensive processing of bird migration data remains limited. Hence, we introduce a novel package called migrationR. This package enables the calculation of movement speed, direction, changes in direction, flight duration, daily and annual movement distances. Furthermore, it can pinpoint the starting and ending dates of migration, estimate nest site locations and stopovers, and visualize movement trajectories at various time scales. migrationR distinguishes individuals through NMDS (non-metric multidimensional scaling) coordinates based on movement variables such as speed, flight duration, path tortuosity, and migration timing. A distinctive aspect of the package is the development of a hetero-occurrences species distribution model that takes into account the daily rhythm of individual birds across different landcover types. Habitat use for foraging and roosting differs significantly for many waterbirds. For example, White-naped Cranes at Poyang Lake in China typically forage in croplands and roost in shallow water areas. Both of these occurrence types are of equal importance. Optimal habitats consist of a combination of crop lands and shallow waters, whereas suboptimal habitats lack both, which necessitates birds to fly extensively. With migrationR, we conduct species distribution modeling for foraging and roosting separately and utilize the moving distance between crop lands and shallow water areas as an index of overall habitat suitability. This approach offers a more nuanced understanding of the habitat requirements for migratory birds and enhances our ability to analyze and interpret their movement patterns effectively. The functions of migrationR are demonstrated using our own tracking data of 78 White-naped Crane individuals from 2014 to 2023, comprising over one million valid locations in total. migrationR can be installed from a GitHub repository by executing the following command: remotes::install_github("Xinhai-Li/migrationR").

Keywords: bird migration, hetero-occurrences species distribution model, migrationR, R package, satellite telemetry

Procedia PDF Downloads 63

Authors: Yasir Ali Soomro

Abstract:

Companies that demonstrate corporate social responsibilities (CSR) are more likely to withstand any downturn or crises because of the trust built with stakeholders. Many firms are utilizing CSR marketing to improve the interactions with their various stakeholders, mainly the consumers. Most previous research on CSR has focused on the impact of CSR on customer responses and behaviors toward a company. As online food ordering and grocery shopping remains inevitable. This study will investigate structural relationships among consumer positive emotions (CPE) and negative emotions (CNE), Corporate Reputation (CR), Customer Trust (CT), Brand Image (BI), and Brand attitude (BA) on behavioral outcomes such as Online purchase intention (OPI) and Word of mouth (WOM) in retail grocery and food restaurants setting. Hierarchy of Effects Model will be used as theoretical, conceptual framework. The model describes three stages of consumer behavior: (i) cognitive, (ii) affective, and (iii) conative. The study will apply a quantitative method to test the hypotheses; a self-developed questionnaire with non-probability sampling will be utilized to collect data from 500 consumers belonging to generation X, Y, and Z residing in KSA. The study will contribute by providing empirical evidence to support the link between CSR and customer affective and conative experiences in Saudi Arabia. The theoretical contribution of this study will be empirically tested comprehensive model where CPE, CNE, CR, CT, BI, and BA act as mediating variables between the perceived CSR & Online purchase intention (OPI) and Word of mouth (WOM). Further, the study will add more to how the emotional/ psychological process mediates in the CSR literature, especially in the Middle Eastern context. The proposed study will also explain the effect of perceived CSR marketing initiatives directly and indirectly on customer behavioral responses.

Keywords: corporate social responsibility, corporate reputation, consumer emotions, loyalty, online purchase intention, word-of-mouth, structural equation modeling

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Authors: Mardiati Zain, Yetti Marlida, Elihasridas Elihasridas, Erpomen Erpomen, Andri Andri

Abstract:

Background: Livestock productivity is greatly influenced by the energy and protein balance in diet. This study aimed to determine the energy and protein balance of male Simenthal cattle diet with protein and energy levels. The experimental design used was a randomized block design (RBD) 2x3x3 factorial design. There are two factors namely A level of energy diet that is 65% and 70% TDN. Factor B is a protein level of diet used were 10, 12 and 14% and each treatment is repeated three times. The weight of Simenthal cattle used ranged between 240 - 300 kg. Diet consisted of ammoniated rice straw and concentrated with ratio 40:60. Concentrate consisted of palm kernel cake, rice brain, cassava, mineral, and urea. The variables measured were digestibility of dry matter, organic matter and fiber, dry matter intake, daily gain, feed efficiency and blood characteristic. Results: There was no interaction between protein and energy level of diet on the nutrients intake (DM intake, OM intake, CP intake), weight gain and efficiency (P < 0.01). There was an interaction between protein and energy level of diet on digestibility (DM, OM, CP and allantoin urine (P > 0.01) Nutrients intake decreases with increasing levels of energy and protein diet, while nutrient digestibility, Avarage daily gain and feed efficiency increases with increasing levels of energy and protein diet. Conclusions: The result can be concluded that the best treatment was A2B1 which is energy level 70% TDN and protein 10%, where are dry matter intake 7.66 kg/d, daily gain 1.25 kg/d, feed efficiency 16.12%, and dry matter and organic matter digestibility 64.08 and 69.42% respectively.

Keywords: energy and protein ratio, simenthal cattle, rice straw ammoniated, digestibility

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

Abstract:

Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Anil Khanal, Ali Osareh, Gary Lebby

Abstract:

Wind energy offers a significant advantage such as no fuel costs and no emissions from generation. However, wind energy sources are variable and non-dispatchable. The utility grid is able to accommodate the variability of wind in smaller proportion along with the daily load. However, at high penetration levels, the variability can severely impact the utility reserve requirements and the cost associated with it. In this paper, the impact of wind energy is evaluated in detail in formulating the total utility cost. The objective is to minimize the overall cost of generation while ensuring the proper management of the load. Overall cost includes the curtailment cost, reserve cost and the reliability cost as well as any other penalty imposed by the regulatory authority. Different levels of wind penetrations are explored and the cost impacts are evaluated. As the penetration level increases significantly, the reliability becomes a critical question to be answered. Here, we increase the penetration from the wind yet keep the reliability factor within the acceptable limit provided by NERC. This paper uses an economic dispatch (ED) model to incorporate wind generation into the power grid. Power system costs are analyzed at various wind penetration levels using Linear Programming. The goal of this study shows how the increases in wind generation will affect power system economics.

Keywords: wind power generation, wind power penetration, cost analysis, economic dispatch (ED) model

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: Shengdan Yang

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The outbreak of the COVID-19 pandemic in early 2020 has made public health issues to be re-examined. The value of green space configuration is an important measure of community health quality. By combining quantitative and qualitative methods, the structure and function of community green space can be better evaluated. This study selects Wuhan Kunhou Community as the site and proposes to analyze the daily health service function of the community's green infrastructure. Through GIS-based spatial analysis, case study, and field investigation, this study evaluates the accessibility of green infrastructure and discusses the ideal green space form based on health indicators. The findings show that Kunhou Community lacks access to green infrastructure and public space for daily activities. The research findings provide a bridge between public health indicators and community space planning and propose design suggestions for green infrastructure planning.

Keywords: accessibility, community health, GIS, green infrastructure

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Rania Hanafi Said, Rasha Mohamed Taha

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Background: By using nanoparticles as drug delivery, it may be possible to avoid the drawbacks of systemic antibiotic dosing, including bacterial antibiotic resistance. The goal of this study was to see how well tetracycline loaded on nanochitosan worked to treat gingival inflammation in albino rats caused by Porphyromonas gingivalis. The study analyzed immunohistochemically the localization of the pro-inflammatory cytokine Interleukin-1beta (IL-1β). Material and methods: In this study, fifty mature male albino rats weighing 150 to 180 grams each were used. They were randomly divided into five groups. We checked for weight changes in rats. Ten male albino rats were included in Group I, which served as a negative control group. Ten rats were included in Group II, where they were exposed once to Porphyromonas. Group III contained ten rats, which were treated the same as Group II plus daily injections of diluted tetracycline powder at the infection sites. Ten rats in Group IV received the same procedure as those in Group II before receiving daily injections of nanochitosan at the injection sites. Finally, Group V, which had ten rats. Following the same protocol as Group II, they received localized injections of tetracycline loaded on nanochitosan once daily. Rats' gingivae were extracted and prepared after they were anesthetized. The biopsies were examined histologically and immunohistochemically by light microscopy. Results: Groups I and V had a nearly normal histological appearance of gingival tissue. In Groups II, III, and IV, degeneration was seen because the epithelial cells were bigger, collagen fibers were pulling away from the lamina propria connective tissue, and the basement membranes had come to an end. There was no discernible difference between groups V and I when they were examined immunohistochemically. Conclusion: The use of nano chitosan as a tetracycline carrier is a novel technique to overcome the drug's rising level of resistance.

Keywords: Immunohistochemistry, Nanochitosan, porphyromonas gingivitis, Tetracycline

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Funda Kul, İsmail Gür

Abstract:

Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

Procedia PDF Downloads 183

Authors: E Tolufase

Abstract:

The demand, high costs and health implications of using energy derived from hydrocarbon compound have necessitated the continuous search for alternative source of energy. The World energy market is facing some challenges viz: depletion of fossil fuel reserves, population explosion, lack of energy security, economic and urbanization growth and also, in Nigeria some rural areas still depend largely on wood, charcoal, kerosene, petrol among others, as the sources of their energy. To overcome these short falls in energy supply and demand, as well as taking into consideration the risks from global climate change due to effect of greenhouse gas emissions and other pollutants from fossil fuels’ combustion, brought a lot of attention on efficiently harnessing the renewable energy sources. A very promising among the renewable energy resources for a clean energy technology for power production, vehicle and domestic usage is biogas. Therefore, optimization of biogas yield and quality is imperative. Hence, this study investigated yield and quality of biogas using low cost bio-digester and combination of various feed stocks referred to as co-digestion. Batch/Discontinuous Bio-digester type was used because it was cheap, easy, plausible and appropriate for different substrates used to get the desired results. Three substrates were used; cow dung, chicken droppings and lemon grass digested in five separate 21 litre digesters, A, B, C, D, and E and the gas collection system was designed using locally available materials. For single digestion we had; cow dung, chicken droppings, lemon grass, in Bio-digesters A, B, and C respectively, the co-digested three substrates in different mixed ratio 7:1:2 in digester D and E in ratio 5:3:2. The respective feed-stocks materials were collected locally, digested and analyzed in accordance with standard procedures. They were pre-fermented for a period of 10 days before being introduced into the digesters. They were digested for a retention period of 28 days, the physiochemical parameters namely; pressure, temperature, pH, volume of the gas collector system and volume of biogas produced were all closely monitored and recorded daily. The values of pH and temperature ranged 6.0 - 8.0, and 220C- 350C respectively. For the single substrate, bio-digester A(Cow dung only) produced biogas of total volume 0.1607m3(average volume of 0.0054m3 daily),while B (Chicken droppings ) produced 0.1722m3 (average of 0.0057m3 daily) and C (lemon grass) produced 0.1035m3 (average of 0.0035m3 daily). For the co-digested substrates in bio-digester D the total biogas produced was 0.2007m³ (average volume of 0.0067m³ daily) and bio-digester E produced 0.1991m³ (average volume of 0.0066m³ daily) It’s obvious from the results, that combining different substrates gave higher yields than when a singular feed stock was used and also mixing ratio played some roles in the yield improvement. Bio-digesters D and E contained the same substrates but mixed with different ratios, but higher yield was noticed in D with mixing ratio of 7:1:2 than in E with ratio 5:3:2.Therefore, co-digestion of substrates and mixing proportions are important factors for biogas production optimization.

Keywords: anaerobic, batch, biogas, biodigester, digestion, fermentation, optimization

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