Search results for: interval estimation

Authors: Jean-Philippe Amat, Timothée Vergne, Aymeric Hans, Bénédicte Ferry, Pascal Hendrikx, Jackie Tapprest, Barbara Dufour, Agnès Leblond

Abstract:

The surveillance of infectious diseases is necessary to describe their occurrence and help the planning, implementation and evaluation of risk mitigation activities. However, the exact number of detected cases may remain unknown whether surveillance is based on serological tests because identifying seroconversion may be difficult. Moreover, incomplete detection of cases or outbreaks is a recurrent issue in the field of disease surveillance. This study addresses these two issues. Using a viral animal disease as an example (equine viral arteritis), the goals were to establish suitable rules for identifying seroconversion in order to estimate the number of cases and outbreaks detected by a surveillance system in France between 2006 and 2013, and to assess the sensitivity of this system by estimating the total number of outbreaks that occurred during this period (including unreported outbreaks) using a capture-recapture model. Data from horses which exhibited at least one positive result in serology using viral neutralization test between 2006 and 2013 were used for analysis (n=1,645). Data consisted of the annual antibody titers and the location of the subjects (towns). A consensus among multidisciplinary experts (specialists in the disease and its laboratory diagnosis, epidemiologists) was reached to consider seroconversion as a change in antibody titer from negative to at least 32 or as a three-fold or greater increase. The number of seroconversions was counted for each town and modeled using a unilist zero-truncated binomial (ZTB) capture-recapture model with R software. The binomial denominator was the number of horses tested in each infected town. Using the defined rules, 239 cases located in 177 towns (outbreaks) were identified from 2006 to 2013. Subsequently, the sensitivity of the surveillance system was estimated as the ratio of the number of detected outbreaks to the total number of outbreaks that occurred (including unreported outbreaks) estimated using the ZTB model. The total number of outbreaks was estimated at 215 (95% credible interval CrI95%: 195-249) and the surveillance sensitivity at 82% (CrI95%: 71-91). The rules proposed for identifying seroconversion may serve future research. Such rules, adjusted to the local environment, could conceivably be applied in other countries with surveillance programs dedicated to this disease. More generally, defining ad hoc algorithms for interpreting the antibody titer could be useful regarding other human and animal diseases and zoonosis when there is a lack of accurate information in the literature about the serological response in naturally infected subjects. This study shows how capture-recapture methods may help to estimate the sensitivity of an imperfect surveillance system and to valorize surveillance data. The sensitivity of the surveillance system of equine viral arteritis is relatively high and supports its relevance to prevent the disease spreading.

Keywords: Bayesian inference, capture-recapture, epidemiology, equine viral arteritis, infectious disease, seroconversion, surveillance

Procedia PDF Downloads 297

Authors: Moses Mwangi, Geert Verbeke, Geert Molenberghs

Abstract:

Cross-over designs are commonly used in randomized clinical trials to estimate efficacy of a new treatment with respect to a reference treatment (placebo or standard). The main advantage of using cross-over design over conventional parallel design is its flexibility, where every subject become its own control, thereby reducing confounding effect. Jones & Kenward, discuss in detail more recent developments in the analysis of cross-over trials. We revisit the simple piecewise linear mixed-effects model, proposed by Mwangi et. al, (in press) for its first application in the analysis of cross-over trials. We compared performance of the proposed piecewise linear mixed-effects model with two commonly cited statistical models namely, (1) Grizzle model; and (2) Jones & Kenward model, used in estimation of the treatment effect, in the analysis of randomized cross-over trial. We estimate two performance measurements (mean square error (MSE) and coverage probability) for the three methods, using data simulated from the proposed piecewise linear mixed-effects model. Piecewise linear mixed-effects model yielded lowest MSE estimates compared to Grizzle and Jones & Kenward models for both small (Nobs=20) and large (Nobs=600) sample sizes. It’s coverage probability were highest compared to Grizzle and Jones & Kenward models for both small and large sample sizes. A piecewise linear mixed-effects model is a better estimator of treatment effect than its two competing estimators (Grizzle and Jones & Kenward models) in the analysis of cross-over trials. The data generating mechanism used in this paper captures two time periods for a simple 2-Treatments x 2-Periods cross-over design. Its application is extendible to more complex cross-over designs with multiple treatments and periods. In addition, it is important to note that, even for single response models, adding more random effects increases the complexity of the model and thus may be difficult or impossible to fit in some cases.

Keywords: Evaluation, Grizzle model, Jones & Kenward model, Performance measures, Simulation

Procedia PDF Downloads 122

Authors: Helena Bolini, Erick Esmerino, Adriano Cruz, Juliana Paixao

Abstract:

The currently concern for health has increased demand for low-calorie ingredients and functional foods as probiotics. Understand the reasons that infer on food choice, besides a challenging task, it is important step for development and/or reformulation of existing food products. The use of appropriate multivariate statistical techniques, such as External Preference Map (PrefMap), associated with regression by Partial Least Squares (PLS) can help in determining those factors. Thus, this study aimed to determine, through PLS regression analysis, the sensory attributes considered drivers of liking in probiotic petit suisse cheeses, strawberry flavor, sweetened with different sweeteners. Five samples in same equivalent sweetness: PROB1 (Sucralose 0.0243%), PROB2 (Stevia 0.1520%), PROB3 (Aspartame 0.0877%), PROB4 (Neotame 0.0025%) and PROB5 (Sucrose 15.2%) determined by just-about-right and magnitude estimation methods, and three commercial samples COM1, COM2 and COM3, were studied. Analysis was done over data coming from QDA, performed by 12 expert (highly trained assessors) on 20 descriptor terms, correlated with data from assessment of overall liking in acceptance test, carried out by 125 consumers, on all samples. Sequentially, results were submitted to PLS regression using XLSTAT software from Byossistemes. As shown in results, it was possible determine, that three sensory descriptor terms might be considered drivers of liking of probiotic petit suisse cheese samples added with sweeteners (p<0.05). The milk flavor was noticed as a sensory characteristic with positive impact on acceptance, while descriptors bitter taste and sweet aftertaste were perceived as descriptor terms with negative impact on acceptance of petit suisse probiotic cheeses. It was possible conclude that PLS regression analysis is a practical and useful tool in determining drivers of liking of probiotic petit suisse cheeses sweetened with artificial and natural sweeteners, allowing food industry to understand and improve their formulations maximizing the acceptability of their products.

Keywords: acceptance, consumer, quantitative descriptive analysis, sweetener

Procedia PDF Downloads 446

Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

Abstract:

In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

Procedia PDF Downloads 67

Authors: Giulia Colonna, Jocelyn Hoye, Bart de Laat, Gelsina Stanley, Jose Key, Alaaddin Ibrahimy, Sule Tinaz, Evan D. Morris

Abstract:

Parkinson’s disease (PD) is the second most common neurodegenerative disease and affects approximately 1% of the world’s population. Increasing evidence suggests that aerobic physical exercise can be beneficial in mitigating both motor and non-motor symptoms of the disease. In a recent pilot study of the role of exercise on PD, we sought to confirm exercise intensity by monitoring heart rate (HR). For this purpose, we asked participants to wear a chest strap heart rate monitor (Polar Electro Oy, Kempele). The device sometimes proved uncomfortable. Looking forward to larger clinical trials, it would be convenient to employ a more comfortable and user friendly device. The Fitbit Charge 4 (Fitbit Inc) is a potentially comfortable, user-friendly solution since it is a wrist-worn heart rate monitor. Polar H10 has been used in large trials, and for our purposes, we treated it as the gold standard for the beat-to-beat period (R-R interval) assessment. In previous literature, it has been shown that Fitbit Charge 4 has comparable accuracy to Polar H10 in healthy subjects. It has yet to be determined if the Fitbit is as accurate as the Polar H10 in subjects with PD or in clinical populations, generally. Goal: To compare the Fitbit Charge 4 to the Polar H10 for monitoring HR in PD subjects engaging in an intensive exercise program. Methods: A total of 596 exercise sessions from 11 subjects (6 males) were collected simultaneously by both devices. Subjects with early-stage PD (Hoehn & Yahr <=2) were enrolled in a 6 months exercise training program designed for PD patients. Subjects participated in 3 one-hour exercise sessions per week. They wore both Fitbit and Polar H10 during each session. Sessions included rest, warm-up, intensive exercise, and cool-down periods. We calculated the bias in the HR via Fitbit under rest (5min) and intensive exercise (20min) by comparing the mean HR during each of the periods to the respective means measured by the Polar (HRFitbit – HRPolar). We also measured the sensitivity and specificity of Fitbit for detecting HRs that exceed the threshold for intensive exercise, defined as 70% of an individual’s theoretical maximum HR. Different types of correlation between the two devices were investigated. Results: The mean bias was 1.68 bpm at rest and 6.29 bpm during high intensity exercise, with an overestimation by Fitbit in both conditions. The mean bias of Fitbit across both rest and intensive exercise periods was 3.98 bpm. The sensitivity of the device in identifying high intensity exercise sessions was 97.14 %. The correlation between the two devices was non-linear, suggesting a saturation tendency of Fitbit to saturate at high values of HR. Conclusion: The performance of Fitbit Charge 4 is comparable to Polar H10 for assessing exercise intensity in a cohort of PD subjects. The device should be considered a reasonable replacement for the more cumbersome chest strap technology in future similar studies of clinical populations.

Keywords: fitbit, heart rate measurements, parkinson’s disease, wrist-wearable devices

Procedia PDF Downloads 109

Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

Abstract:

Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

Procedia PDF Downloads 157

Authors: Defne Uz

Abstract:

Horizontal Tail of helicopter is exposed to repeated oscillatory loading generated by aerodynamic and inertial loads, and bending moments depending on operating conditions and maneuvers of the helicopter. In order to ensure that maximum stress levels do not exceed certain fatigue limit of the material and to prevent damage, a numerical analysis approach can be utilized through the Finite Element Method. Therefore, in this paper, fatigue analysis of the Horizontal Tail model is studied numerically to predict high-cycle and low-cycle fatigue life related to defined loading. The analysis estimates the stress field at stress concentration regions such as around fastener holes where the maximum principal stresses are considered for each load case. Critical element identification of the main load carrying structural components of the model with rivet holes is performed as a post-process since critical regions with high-stress values are used as an input for fatigue life calculation. Once the maximum stress is obtained at the critical element and the related mean and alternating components, it is compared with the endurance limit by applying Soderberg approach. The constant life straight line provides the limit for several combinations of mean and alternating stresses. The life calculation based on S-N (Stress-Number of Cycles) curve is also applied with fully reversed loading to determine the number of cycles corresponds to the oscillatory stress with zero means. The results determine the appropriateness of the design of the model for its fatigue strength and the number of cycles that the model can withstand for the calculated stress. The effect of correctly determining the critical rivet holes is investigated by analyzing stresses at different structural parts in the model. In the case of low life prediction, alternative design solutions are developed, and flight hours can be estimated for the fatigue safe operation of the model.

Keywords: fatigue analysis, finite element method, helicopter horizontal tail, life prediction, stress concentration

Procedia PDF Downloads 145

Authors: Mikko Salminen, Niklas Ravaja

Abstract:

Previous studies have shown that emotional intelligence (EI) has an important role in leadership and social interaction. On the other hand, physiological synchronization between two interacting participants has been related to, for example, intensity of the interaction, and interestingly also to empathy. It is suggested that the amount of covariation in physiological signals between the two interacting persons would also be related to how the discussion is perceived subjectively. To study the interrelations between physiological synchronization, emotional intelligence, and subjective perception of the interaction, performance review discussions between real manager – subordinate dyads were studied using psychophysiological measurements and self-reports. The participants consisted of 40 managers, of which 24 were female, and 78 of their subordinates, of which 45 were female. The participants worked in various fields, for example banking, education, and engineering. The managers had a normal performance review discussion with two subordinates, except two managers who, due to scheduling issues, had discussion with only one subordinate. The managers were on average 44.5 years old, and the subordinates on average 45.5 years old. Written consent, in accordance with the Declaration of Helsinki, was obtained from all the participants. After the discussion, the participants filled a questionnaire assessing their emotions during the discussion. This included a self-assessment manikin (SAM) scale for the emotional valence during the discussion, with a 9-point graphical scale representing a manikin whose facial expressions ranged from smiling and happy to frowning and unhappy. In addition, the managers filled EI360, a 37-item self-report trait emotional intelligence questionnaire. The psychophysiological activity of the participants was recorded using two Varioport-B portable recording devices. Cardiac activity (ECG, electrocardiogram) was measured with two electrodes placed on the torso. Inter-beat interval (IBI, time between two successive heart beats) was calculated from the ECG signals. The facial muscle activation (EMG, electromyography) was recorded on three sites of the left side of the face: zygomaticus major (cheek muscle), orbicularis oculi (periocular muscle), and corrugator supercilii (frowning muscle). The facial-EMG signals were rectified and smoothed, and cross-coherences were calculated between members of each dyad, for all the three EMG signals, for the baseline and discussion periods. The values were natural-log transformed to normalize the distributions. Higher cross-coherence during the discussion between the manager’s and the subordinate’s zygomatic muscles was related to more positive valence self-reported emotions, F(1; 66,137) = 7,051; p=0,01. Thus, synchronized cheek muscle activation, either due to synchronous smiling or talking, was related to more positive perception of the discussion. In addition, higher IBI synchronization between the manager and the subordinate during the discussion was related to the manager’s higher self-reported emotional intelligence, F(1; 27,981)=4,58; p=0,041. That is, the EI was related to synchronous cardiac activity and possibly to similar physiological arousal levels. The results imply that the psychophysiological synchronization could be a potentially useful index in the study of social interaction and a valuable tool in the coaching of leadership skills in organizational contexts.

Keywords: emotional intelligence, leadership, psychophysiology, social interaction, synchronization

Procedia PDF Downloads 319

Authors: Fumiya Sugino, Naohiro Nakamura, Yuji Miyazu

Abstract:

In earthquake resistant design of buildings, evaluation of vibration characteristics is important. In recent years, due to the increment of super high-rise buildings, the evaluation of response is important for not only the first mode but also higher modes. The knowledge of vibration characteristics in buildings is mostly limited to the first mode and the knowledge of higher modes is still insufficient. In this paper, using earthquake observation records of a SRC building by applying frequency filter to ARX model, characteristics of first and second modes were studied. First, we studied the change of the eigen frequency and the damping ratio during the 3.11 earthquake. The eigen frequency gradually decreases from the time of earthquake occurrence, and it is almost stable after about 150 seconds have passed. At this time, the decreasing rates of the 1st and 2nd eigen frequencies are both about 0.7. Although the damping ratio has more large error than the eigen frequency, both the 1st and 2nd damping ratio are 3 to 5%. Also, there is a strong correlation between the 1st and 2nd eigen frequency, and the regression line is y=3.17x. In the damping ratio, the regression line is y=0.90x. Therefore 1st and 2nd damping ratios are approximately the same degree. Next, we study the eigen frequency and damping ratio from 1998 after 3.11 earthquakes, the final year is 2014. In all the considered earthquakes, they are connected in order of occurrence respectively. The eigen frequency slowly declined from immediately after completion, and tend to stabilize after several years. Although it has declined greatly after the 3.11 earthquake. Both the decresing rate of the 1st and 2nd eigen frequencies until about 7 years later are about 0.8. For the damping ratio, both the 1st and 2nd are about 1 to 6%. After the 3.11 earthquake, the 1st increases by about 1% and the 2nd increases by less than 1%. For the eigen frequency, there is a strong correlation between the 1st and 2nd, and the regression line is y=3.17x. For the damping ratio, the regression line is y=1.01x. Therefore, it can be said that the 1st and 2nd damping ratio is approximately the same degree. Based on the above results, changes in eigen frequency and damping ratio are summarized as follows. In the long-term study of the eigen frequency, both the 1st and 2nd gradually declined from immediately after completion, and tended to stabilize after a few years. Further it declined after the 3.11 earthquake. In addition, there is a strong correlation between the 1st and 2nd, and the declining time and the decreasing rate are the same degree. In the long-term study of the damping ratio, both the 1st and 2nd are about 1 to 6%. After the 3.11 earthquake, the 1st increases by about 1%, the 2nd increases by less than 1%. Also, the 1st and 2nd are approximately the same degree.

Keywords: eigenfrequency, damping ratio, ARX model, earthquake observation records

Procedia PDF Downloads 217

Authors: Sahar Tabarroki, Ahad Nazari

Abstract:

The design process is one of the most key project processes in the construction industry. Although architects have the responsibility to produce complete, accurate, and coordinated documents, architectural design is accompanied by many errors. A design error occurs when the constraints and requirements of the design are not satisfied. Errors are potentially costly and time-consuming to correct if not caught early during the design phase, and they become expensive in either construction documents or in the construction phase. The aim of this research is to identify the risk factors of architectural design errors, so identification of risks is necessary. First, a literature review in the design process was conducted and then a questionnaire was designed to identify the risks and risk factors. The questions in the form of the questionnaire were based on the “similar service description of study and supervision of architectural works” published by “Vice Presidency of Strategic Planning & Supervision of I.R. Iran” as the base of architects’ tasks. Second, the top 10 risks of architectural activities were identified. To determine the positions of possible causes of risks with respect to architectural activities, these activities were located in a design process modeled by the IDEF0 technique. The research was carried out by choosing a case study, checking the design drawings, interviewing its architect and client, and providing a checklist in order to identify the concrete examples of architectural design errors. The results revealed that activities such as “defining the current and future requirements of the project”, “studies and space planning,” and “time and cost estimation of suggested solution” has a higher error risk than others. Moreover, the most important causes include “unclear goals of a client”, “time force by a client”, and “lack of knowledge of architects about the requirements of end-users”. For error detecting in the case study, lack of criteria, standards and design criteria, and lack of coordination among them, was a barrier, anyway, “lack of coordination between architectural design and electrical and mechanical facility”, “violation of the standard dimensions and sizes in space designing”, “design omissions” were identified as the most important design errors.

Keywords: architectural design, design error, risk management, risk factor

Procedia PDF Downloads 130

Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

Abstract:

Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

Procedia PDF Downloads 250

Authors: Abdulmalek Ahmed

Abstract:

Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

Procedia PDF Downloads 149

Authors: William Castillo, Hugo Viza, Arturo Vargas

Abstract:

The Pacific Alliance is a trade bloc that is composed of four emerging economies: Chile, Colombia, Peru, and Mexico. These economies have gained macroeconomic stability in the past decade and as a consequence present future economic progress. Under this positive scenario, international business firms have flourished. However, the literature in this region has been widely unexamined. Therefore, it is critical to fill this theoretical gap, especially considering that Latin America is starting to become a global player and it possesses a different institutional context than developed markets. This paper analyzes the effect of international entrepreneurial orientation and institutionalism on international performance, for the Pacific Alliance small-to-medium enterprises (SMEs). The literature considers international entrepreneurial orientation to be a powerful managerial capability – along the resource based view- that firms can leverage to obtain a satisfactory international performance. Thereby, obtaining a competitive advantage through the correct allocation of key resources to exploit the capabilities here involved. Entrepreneurial Orientation is defined around five factors: innovation, proactiveness, risk-taking, competitive aggressiveness, and autonomy. Nevertheless, the institutional environment – both local and foreign, adversely affects International Performance; this is especially the case for emerging markets with uncertain scenarios. In this way, the study analyzes an Entrepreneurial Orientation, key endogenous variable of international performance, and Institutionalism, an exogenous variable. The survey data consists of Pacific Alliance SMEs that have foreign operations in at least another country in the trade bloc. Findings are still in an ongoing research process. Later, the study will undertake a structural equation modeling (SEM) using the variance-based partial least square estimation procedure. The software that is going to be used is the SmartPLS. This research contributes to the theoretical discussion of a largely postponed topic: SMEs in Latin America, that has had limited academic research. Also, it has practical implication for decision-makers and policy-makers, providing insights into what is behind international performance.

Keywords: institutional theory, international entrepreneurial orientation, international performance, SMEs, Pacific Alliance

Procedia PDF Downloads 248

Authors: Elena Carcano, James Ball, Betty Tiko

Abstract:

Carrying capacity refers to the maximum population that a given level of resources can sustain over a specific period. In undisturbed environments, the maximum population is determined by the availability and distribution of resources, as well as the competition for their utilization. This information is typically obtained through long-term data collection. In regulated environments, where resources are artificially modified, populations must adapt to changing conditions, which can lead to additional challenges due to fluctuations in resource availability over time and throughout development. An example of this is observed in hydropower plants, which alter water flow and impact fish migration patterns and behaviors. To assess how fish species can adapt to these changes, specialized surveys are conducted, which provide valuable information on fish populations, sample sizes, and density before and after flow modifications. In such situations, it is highly recommended to conduct hydrological and biological monitoring to gain insight into how flow reductions affect species adaptability and to prevent unfavorable exploitation conditions. This analysis involves several planned steps that help design appropriate hydropower production while simultaneously addressing environmental needs. Consequently, the study aims to strike a balance between technical assessment, biological requirements, and societal expectations. Beginning with a small hydro project that requires restoration, this analysis focuses on the lower tail of the Flow Duration Curve (FDC), where both hydrological and environmental goals can be met. The proposed approach involves determining the threshold condition that is tolerable for the most vulnerable species sampled (Telestes Muticellus) by identifying a low flow value from the long-term FDC. The results establish a practical connection between hydrological and environmental information and simplify the process by establishing a single reference flow value that represents the minimum environmental flow that should be maintained.

Keywords: carrying capacity, fish bypass ladder, long-term streamflow duration curve, eta-beta method, environmental flow

Procedia PDF Downloads 40

Authors: Hong Wu, Naiji Lu

Abstract:

Improvement of health behavior among people with chronic diseases is vital for increasing longevity and enhancing quality of life. This paper researched the causal effects of informal care on the compliance with doctor’s health advices – smoking control, dietetic regulation, weight control and keep exercising – among older people with chronic diseases in China, which is facing the challenge of aging. We addressed the selection bias by using propensity score matching in the estimation process. We used the 2011-2012 national baseline data of the China Health and Retirement Longitudinal Study. Our results showed informal care can help improve health behavior of older people. First, informal care improved the compliance of smoking controls: whether smoke, frequency of smoking, and the time lag between wake up and the first cigarette was all lower for these older people with informal care; Second, for dietetic regulation, older people with informal care had more meals every day than older people without informal care; Third, three variables: BMI, whether gain weight and whether lose weight were used to measure the outcome of weight control. There were no significant difference between group with informal care and that without for BMI and the possibility of losing weight. Older people with informal care had lower possibility of gain weight than that without; Last, for the advice of keeping exercising, informal care increased the probability of walking exercise, however, the difference between groups for moderate and vigorous exercise were not significant. Our results indicate policy makers who aim to decrease accidents should take informal care to elders into account and provide an appropriate policy to meet the demand of informal care. Our birth policy and postponed retirement policy may decrease the informal caregiving hours, so adjustments of these policies are important and urgent to meet the current situation of aged tendency of population. In addition, government could give more support to develop organizations to provide formal care, such as nursing home. We infer that formal care is also useful for health behavior improvements.

Keywords: chronic diseases, compliance, CHARLS, health advice, informal care, older people, propensity score matching

Procedia PDF Downloads 405

Authors: Moetazza M. Al-Shafei, Hala Abdel Karim, Eitedal M. Daoud, Hassan Zaki Hassuna

Abstract:

Epilepsy is a common neurological disorder affecting all age groups. It is one of the world's most prevalent non-communicable diseases. Increased evidence suggesting that long term usage of anti-epileptic drugs can have adverse effects on bone mineralization and bone molding .Aiming to study these effects and to give guide lines to support bone health through early intervention. From Neurology Out-Patient Clinic kaser Elaini University Hospital, 60 Patients were enrolled, 40 patients on antiepileptic drugs for at least two years and 20 controls matched with age and sex, epileptic but before starting treatment both chosen under specific criteria. Patients were divided into four groups, three groups with monotherapy treated with either Phynetoin, Valporic acid or Carbamazipine and fourth group treated with both Valporic acid and Carbamazipine. Estimation of serum Carboxy-Terminal Telopeptide of Type I- Collagen(ICTP) bone resorption marker, serum 25(OH )vit D3, calcium ,magnesium and phosphorus were done .Results showed that all patients on AED had significant low levels of 25(OH) vit D3 (p<0.001) ,with significant elevation of ICTP (P<0.05) versus controls. In group treated with Phynotoin highly significant elevation of (ICTP) marker and decrease of both serum 25(OH) vit D3 (P<0, 0001) and serum calcium(P<0.05)versus control. Double drug group showed significant decrease of serum 25(OH) vit D3 (P<0.0001) and decrease in Phosphorus (P<0.05) versus controls. Serum magnesium showed no significant differences between studied groups. We concluded that Anti- epileptic drugs appears to be an aggravating factor on bone mineralization ,so therapeutically it can be worth wile to supplement calcium and vitamin D even before initiation of antiepileptic therapy. ICTP marker can be used to evaluate change in bone resorption before and during AED therapy.

Keywords: antiepileptic drugs, bone minerals, carboxy teminal telopeptidetype-1-collagen bone resorption marker, vitamin D

Procedia PDF Downloads 493

Authors: Lily Ingsrisawang, Tasanee Nacharoen

Abstract:

Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

Procedia PDF Downloads 434

Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

Abstract:

Background: Intimate partner violence (hereafter IPV) is a major global public health challenge that tortures and disables women in the place where they are ought to be most secure within their own families. The fact that the family unit is commonly viewed as a private circle, violent acts towards women remains undermined. There are limited research and knowledge about the influencing factors linked to IPV in Sierra Leone. This study, therefore, estimates the prevalence rate and the predicting factors associated with IPV. Methods: Data were taken from Sierra-Leone Demographic and Health Survey (SDHS, 2013): the first in its form to incorporate information on domestic violence. Multistage cluster sampling research design was used, and information was gathered by a standard questionnaire. A total of 5185 respondents selected were interviewed, out of whom 870 were never been in union, thus excluded. To analyze the two dependent variables: experience of IPV, ‘ever’ and 'last 12 months prior to the survey', a total of 4315 (currently or formerly married) and 4029 women (currently in union) were included respectively. These dependent variables were constructed from the three forms of violence namely physical, emotional and sexual. Data analysis was applied using SPSS version 23, comprising three-step process. First, descriptive statistics were used to show the frequency distribution of both the outcome and explanatory variables. Second, bivariate analysis adopting chi-square test was applied to assess the individual relationship between the outcome and explanatory variables. Third, multivariate logistic regression analysis was undertaken using hierarchical modeling strategy to identify the influence of the explanatory variables on the outcome variables. Odds ratio (OR) and 95% confidence interval (CI) were utilized to examine the association of the variables considering p-values less than 0.05 statistically significant. Results: The prevalence of lifetime IPV among ever married women was 48.4%, while 39.8% of those currently married experienced IPV in the previous year preceding the survey. Women having 1 to 4 and more than 5 number of ever born babies were almost certain to encounter lifetime IPV. However, women who own a property, and those who referenced 3-5 reasons for which wife-beating is acceptable were less probably to experience lifetime IPV. Attesting parental violence, partner’s dominant marital behavior, and women afraid of their partner were the variables related to both experience of IPV ‘ever’ and ‘the previous year prior to the survey’. Respondents who concur that wife-beating is sensible in certain situations and occupations under the professional category had diminished chances of revealing IPV in the year prior to the data collection. Conclusion: This study indicated that factors significantly correlated with IPV in Sierra-Leone are mostly linked with husband related factors specifically, marital controlling behaviors. Addressing IPV in Sierra-Leone requires joint efforts that target men raise awareness to address controlling behavior and empower security in affiliations.

Keywords: husband behavior, married women, partner violence, Sierra Leone

Procedia PDF Downloads 132

Authors: Parimalah Velo, Ahmad Zakaria

Abstract:

Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

Procedia PDF Downloads 271

Authors: L. Nathaniel-Wurie

Abstract:

The Sellick manoeuvre a.k.a the application of cricoid force (CF), was first described by Brian Sellick in 1961. CF is the application of digital pressure against the cricoid cartilage with the intention of posterior force causing oesophageal compression against the vertebrae. This is designed to prevent passive regurgitation of gastric contents, which is a major cause of morbidity and mortality during emergency airway management inside and outside of the hospital. To the authors knowledge, there is no universally standardised training modality and, therefore, no reliable way to examine if there are appropriate outcomes. If force is not measured during training, how can one surmise that appropriate, accurate, or precise amounts of force are being used routinely. Poor homogeneity in teaching and untested outcomes will correlate with reduced efficacy and increased adverse effects. For this study, the accuracy of force delivery in trained professionals was tested, and outcomes contrasted against a novice control and a novice study group. In this study, 20 operating department practitioners were tested (with a mean experience of 5.3years of performing CF). Subsequent contrast with 40 novice students who were randomised into one of two arms. ‘Arm A’ were explained the procedure, then shown the procedure then asked to perform CF with the corresponding force measurement being taken three times. Arm B had the same process as arm A then before being tested, they had 10, and 30 Newtons applied to their hands to increase intuitive understanding of what the required force equated to, then were asked to apply the equivalent amount of force against a visible force metre and asked to hold that force for 20 seconds which allowed direct visualisation and correction of any over or under estimation. Following this, Arm B were then asked to perform the manoeuvre, and the force generated measured three times. This study shows that there is a wide distribution of force produced by trained professionals and novices performing the procedure for the first time. Our methodology for teaching the manoeuvre shows an improved accuracy, precision, and homogeneity within the group when compared to novices and even outperforms trained practitioners. In conclusion, if this methodology is adopted, it may correlate with higher clinical outcomes, less adverse events, and more successful airway management in critical medical scenarios.

Keywords: airway, cricoid, medical education, sellick

Procedia PDF Downloads 79

Authors: Gheorghe Braniste

Abstract:

The management of the training process in sports is closely related to the awareness of the close connection between performance and the morphological, functional and psychological characteristics of the athlete's body. Achieving high results in Olympic sports is influenced, on the one hand, by the genetically determined characteristics of the body and, on the other hand, by the morphological, functional and motor abilities of the athlete. Taking into account the importance of properly understanding the evolutionary specificity of athletes to assess their competitive potential, this study provides a comparative analysis of the parameters that characterize the growth and development of the level of adaptation of sweeping rowers, considering the growth interval between 12 and 20 years. The study established that, in the multi-annual training process, the bodies of the targeted athletes register significant adaptive changes while analyzing parameters of the morphological, functional, psychomotor and sports-technical spheres. As a result of the influence of physical efforts, both specific and non-specific, there is an increase in the adaptability of the body, its transfer to a much higher level of functionality within the parameters, useful and economical adaptive reactions influenced by environmental factors, be they internal or external. The research was carried out for 7 years, on a group of 28 athletes, following their evolution and recording the specific parameters of each age stage. In order to determine the level of physical, morpho-functional, psychomotor development and technical training of rowers, the screening data were applied at the State University of Physical Education and Sports in the Republic of Moldova. During the research, measurements were made on the waist, in the standing and sitting position, arm span, weight, circumference and chest perimeter, vital capacity of the lungs, with the subsequent determination of the vital index (tolerance level to oxygen deficiency in venous blood in Stange and Genchi breath-taking tests that characterize the level of oxygen saturation, absolute and relative strength of the hand and back, calculation of body mass and morphological maturity indices (Kettle index), body surface area (body gait), psychomotor tests (Romberg test), test-tepping 10 s., reaction to a moving object, visual and auditory-motor reaction, recording of technical parameters of rowing on a competitive distance of 200 m. At the end of the study it was found that highly performance is sports is to be associated on the one hand with the genetically determined characteristics of the body and, on the other hand, with favorable adaptive reactions and energy saving, as well as morphofunctional changes influenced by internal and external environmental factors. The importance of the results obtained at the end of the study was positively reflected in obtaining the maximum level of training of athletes in order to demonstrate performance in large-scale competitions and mostly in the Olympic Games.

Keywords: olympics, parameters, performance, peak

Procedia PDF Downloads 123

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

Procedia PDF Downloads 78

Authors: Raj Banerjee, Aniruddha Sengupta

Abstract:

An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

Procedia PDF Downloads 180

Authors: Lee Tasker, Ali Karrech, Jeffrey Shragge, Matthew Josh

Abstract:

Monitoring for the deterioration of concrete infrastructure is an important assessment tool for an engineer and difficulties can be experienced with monitoring for deterioration within an infrastructure. If a failure crack, or fluid seepage through such a crack, is observed from the surface often the source location of the deterioration is not known. Geophysical methods are used to assist engineers with assessing the subsurface conditions of materials. Techniques such as Ground Penetrating Radar (GPR) provide information on the location of buried infrastructure such as pipes and conduits, positions of reinforcements within concrete blocks, and regions of voids/cavities behind tunnel lining. This experiment underlines the application of GPR as an infrastructure-monitoring tool to highlight and monitor regions of possible deterioration within a concrete test wall due to an increase in the generation of fractures; in particular, during a time period of applied load to a concrete wall up to and including structural failure. A three-point load was applied to a concrete test wall of dimensions 1700 x 600 x 300 mm³ in increments of 10 kN, until the wall structurally failed at 107.6 kN. At each increment of applied load, the load was kept constant and the wall was scanned using GPR along profile lines across the wall surface. The measured radar amplitude responses of the GPR profiles, at each applied load interval, were reconstructed into depth-slice grids and presented at fixed depth-slice intervals. The corresponding depth-slices were subtracted from each data set to compare the radar amplitude response between datasets and monitor for changes in the radar amplitude response. At lower values of applied load (i.e., 0-60 kN), few changes were observed in the difference of radar amplitude responses between data sets. At higher values of applied load (i.e., 100 kN), closer to structural failure, larger differences in radar amplitude response between data sets were highlighted in the GPR data; up to 300% increase in radar amplitude response at some locations between the 0 kN and 100 kN radar datasets. Distinct regions were observed in the 100 kN difference dataset (i.e., 100 kN-0 kN) close to the location of the final failure crack. The key regions observed were a conical feature located between approximately 3.0-12.0 cm depth from surface and a vertical linear feature located approximately 12.1-21.0 cm depth from surface. These key regions have been interpreted as locations exhibiting an increased change in pore-space due to increased mechanical loading, or locations displaying an increase in volume of micro-cracks, or locations showing the development of a larger macro-crack. The experiment showed that GPR is a useful geophysical monitoring tool to assist engineers with highlighting and monitoring regions of large changes of radar amplitude response that may be associated with locations of significant internal structural change (e.g. crack development). GPR is a non-destructive technique that is fast to deploy in a production setting. GPR can assist with reducing risk and costs in future infrastructure maintenance programs by highlighting and monitoring locations within the structure exhibiting large changes in radar amplitude over calendar-time.

Keywords: 4D GPR, engineering geophysics, ground penetrating radar, infrastructure monitoring

Procedia PDF Downloads 179

Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

Abstract:

Background: Youth in general and young females in particular, remain at the center of the HIV/AIDS epidemic. Sexual risk-taking among young unmarried women is relatively high and are the most vulnerable and highly exposed to HIV/AIDS. Improvements in the status of HIV/AIDS knowledge and acceptance attitude towards people living with HIV (PLWHIV) plays a great role in averting the incidence of HIV/AIDS. Thus, the aim of the study was to explore the level and correlates of HIV/AIDS knowledge and accepting attitude toward PLWHIV. Methods: A cross-sectional study was conducted using data from the Uganda Demographic Health Survey 2016 (UDHS-2016). National level representative household surveys using a multistage cluster probability sampling method, face to face interviews with standard questionnaires were performed. Unmarried women aged 15-24 years with a sample size of 2019 were selected from the total sample of 8674 women aged 15-49 years and were analyzed using SPSS version 23. Independent variables such as age, religion, educational level, residence, and wealth index were included. Two binary outcome variables (comprehensive HIV/AIDS knowledge and acceptance attitude toward PLWHIV) were utilized. We used the chi-square test as well as multivariate regression analysis to explore correlations of explanatory variables with the outcome variables. The results were reported by odds ratios (OR) with 95% confidence interval (95% CI), taking a p-value less than 0.05 as significant. Results: Almost all (99.3%) of the unmarried women aged 15-24 years were aware of HIV/AIDS, but only 51.2% had adequate comprehensive knowledge on HIV/AIDS. Only 69.4% knew both methods: using a condom every time had sex, and having only one faithful uninfected partner can prevent HIV/AIDS transmission. About 66.6% of the unmarried women reject at least two common local misconceptions about HIV/AIDS. Moreover, an alarmingly few (20.3%) of the respondents had a positive acceptance attitude to PLWHIV. On multivariate analysis, age (20-24 years), living in urban, being educated and wealthier, were predictors of having adequate comprehensive HIV/AIDS knowledge. On the other hand, research participants with adequate comprehensive knowledge about HIV/AIDS were highly likely (OR, 1.94 95% CI, 1.52-2.46) to have a positive acceptance attitude to PLWHIV than those with inadequate knowledge. Respondents with no education, Muslim, and Pentecostal religion were emerged less likely to have a positive acceptance attitude to PLWHIV. Conclusion: This study found out the highly accepted level of awareness, but the knowledge and positive acceptance attitude are not encouraging. Thus, expanding access to comprehensive sexuality and strengthening educational campaigns on HIV/AIDS in communities, health facilities, and schools is needed with a greater focus on disadvantaged women having low educational level, poor socioeconomic status, and those residing in rural areas. Sexual risk behaviors among the most affected people - young women have also a role in the spread of HIV/AIDS. Hence, further research assessing the significant contributing factors for sexual risk-taking might have a positive impact on the fight against HIV/AIDS.

Keywords: acceptance attitude, HIV/AIDS, knowledge, unmarried women

Procedia PDF Downloads 151

Authors: Pratima Poudel, Austin Himes, Heidi Renninger, Eric McConnel

Abstract:

Populus spp. (poplar) are the fastest-growing trees in North America, making them ideal for a range of applications as they can achieve high yields on short rotations and regenerate by coppice. Furthermore, poplar undergoes biochemical conversion to fuels without complexity, making it one of the most promising, purpose-grown, woody perennial energy sources. Employing wood-based biomass for bioenergy offers numerous benefits, including reducing greenhouse gas (GHG) emissions compared to non-renewable traditional fuels, the preservation of robust forest ecosystems, and creating economic prospects for rural communities.In order to gain a better understanding of the potential use of poplar as a biomass feedstock for biofuel in the southeastern US, the conducted a techno-economic assessment (TEA). This assessment is an analytical approach that integrates technical and economic factors of a production system to evaluate its economic viability. the TEA specifically focused on a short rotation coppice system employing a single-pass cut-and-chip harvesting method for poplar. It encompassed all the costs associated with establishing dedicated poplar plantations, including land rent, site preparation, planting, fertilizers, and herbicides. Additionally, we performed a sensitivity analysis to evaluate how different costs can affect the economic performance of the poplar cropping system. This analysis aimed to determine the minimum average delivered selling price for one metric ton of biomass necessary to achieve a desired rate of return over the cropping period. To inform the TEA, data on the establishment, crop care activities, and crop yields were derived from a field study conducted at the Mississippi Agricultural and Forestry Experiment Station's Bearden Dairy Research Center in Oktibbeha County and Pontotoc Ridge-Flatwood Branch Experiment Station in Pontotoc County.

Keywords: biomass, populus species, sensitivity analysis, technoeconomic analysis

Procedia PDF Downloads 83

Authors: Sakda Loetpiparwanich, Preecha Vichitthamaros

Abstract:

Nowadays, poor data quality is considered one of the majority costs for a data project. The data project with data quality awareness almost as much time to data quality processes while data project without data quality awareness negatively impacts financial resources, efficiency, productivity, and credibility. One of the processes that take a long time is defining the expectations and measurements of data quality because the expectation is different up to the purpose of each data project. Especially, big data project that maybe involves with many datasets and stakeholders, that take a long time to discuss and define quality expectations and measurements. Therefore, this study aimed at developing meaningful indicators to describe overall data quality for each dataset to quick comparison and priority. The objectives of this study were to: (1) Develop a practical data quality indicators and measurements, (2) Develop data quality dimensions based on statistical characteristics and (3) Develop Composite Indicator that can describe overall data quality for each dataset. The sample consisted of more than 500 datasets from public sources obtained by random sampling. After datasets were collected, there are five steps to develop the Dataset Quality Index (SDQI). First, we define standard data quality expectations. Second, we find any indicators that can measure directly to data within datasets. Thirdly, each indicator aggregates to dimension using factor analysis. Next, the indicators and dimensions were weighted by an effort for data preparing process and usability. Finally, the dimensions aggregate to Composite Indicator. The results of these analyses showed that: (1) The developed useful indicators and measurements contained ten indicators. (2) the developed data quality dimension based on statistical characteristics, we found that ten indicators can be reduced to 4 dimensions. (3) The developed Composite Indicator, we found that the SDQI can describe overall datasets quality of each dataset and can separate into 3 Level as Good Quality, Acceptable Quality, and Poor Quality. The conclusion, the SDQI provide an overall description of data quality within datasets and meaningful composition. We can use SQDI to assess for all data in the data project, effort estimation, and priority. The SDQI also work well with Agile Method by using SDQI to assessment in the first sprint. After passing the initial evaluation, we can add more specific data quality indicators into the next sprint.

Keywords: data quality, dataset quality, data quality management, composite indicator, factor analysis, principal component analysis

Procedia PDF Downloads 139

Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

Abstract:

The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

Procedia PDF Downloads 55

Authors: Vandana Mohan, Ashwani Koul

Abstract:

Aim: To evaluate the potential of Aqueous Tinospora cordifolia stem extract (Aq.Tc) and Arabinogalactan (AG) on pulmonary carcinogenesis and associated tumor markers. Background: Lung cancer is one of the most frequent malignancy with high mortality rate due to limitation of early detection resulting in low cure rates. Current research effort focuses on identifying some blood-based biomarkers like CEA, ctDNA and LDH which may have potential to detect cancer at an early stage, evaluation of therapeutic response and its recurrence. Medicinal plants and their active components have been widely investigated for their anticancer potentials. Aqueous preparation of T. Cordifolia extract is enriched in the polysaccharide fraction i.e., AG when compared with other types of extract. Moreover, reports are available of polysaccharide fraction of T. Cordifolia in in vitro lung cancer models which showed profound anti-metastatic activity against these cell lines. However, not much has been explored about its effect in in vivo lung cancer models and the underlying mechanism involved. Experimental Design: Mice were randomly segregated into six groups. Group I animals served as control. Group II animals were administered with Aq. Tc extract (200 mg/kg b.w.) p.o.on the alternate days. Group III animals were fed with AG (7.5 mg/kg b.w.) p.o. on the alternate days (thrice a week). Group IV animals were installed with Benzo(a)pyrene (50 mg/kg b.w.), i.p. twice within an interval of two weeks. Group V animals received Aq. Tc extract as in group II along with it B(a)P was installed after two weeks of Aq. Tc administration following the same protocol as for group IV. Group VI animals received AG as in group III along with it B(a)P was installed after two weeks of AG administration. Results: Administration of B(a)P to mice resulted in increased tumor incidence, multiplicity and pulmonary somatic index with concomitant increase in serum/plasma markers like CEA, ctDNA, LDH and TNF-α.Aq.Tc and AG supplementation significantly attenuated these alterations at different stages of tumorigenesis thereby showing potent anti-cancer effect in lung cancer. A pronounced decrease in serum/plasma markers were observed in animals treated with Aq.Tc as compared to those fed with AG. Also, extensive hyperproliferation of alveolar epithelium was prominent in B(a)P induced lung tumors. However, treatment of Aq.Tc and AG to lung tumor bearing mice exhibited reduced alveolar damage evident from decreased number of hyperchromatic irregular nuclei. A direct correlation between the concentration of tumor markers and the intensity of lung cancer was observed in animals bearing cancer co-treated with Aq.Tc and AG. Conclusion: These findings substantiate the chemopreventive potential of Aq.Tc and AG against lung tumorigenesis. Interestingly, Aq.Tc was found to be more effective in modulating the cancer as reflected by various observations which may be attributed to the synergism offered by various components of Aq.Tc. Further studies are in progress to understand the underlined mechanism in inhibiting lung tumorigenesis by Aq.Tc and AG.

Keywords: Arabinogalactan, Benzo(a)pyrene B(a)P, carcinoembryonic antigen (CEA), circulating tumor DNA (ctDNA), lactate dehydrogenase (LDH), Tinospora cordifolia

Procedia PDF Downloads 185

Authors: Anamika Sahu

Abstract:

The Himalayas, like many mountainous regions, is susceptible to multiple hazards. In recent times, the frequency of such disasters is continuously increasing due to extreme weather phenomena. These natural hazards are responsible for irreparable human and economic loss. The Indian Himalayas has repeatedly been ruptured by great earthquakes in the past and has the potential for a future large seismic event as it falls under the seismic gap. Damages caused by earthquakes are different in different localities. It is well known that, during earthquakes, damage to the structure is associated with the subsurface conditions and the quality of construction materials. So, for sustainable mountain development, prior estimation of site characterization will be valuable for designing and constructing the space area and for efficient mitigation of the seismic risk. Both geotechnical and geophysical investigation of the subsurface is required to describe the subsurface complexity. In mountainous regions, geophysical methods are gaining popularity as areas can be studied without disturbing the ground surface, and also these methods are time and cost-effective. The MASW method is used to calculate the Vs30. Vs30 is the average shear wave velocity for the top 30m of soil. Shear wave velocity is considered the best stiffness indicator, and the average of shear wave velocity up to 30 m is used in National Earthquake Hazards Reduction Program (NEHRP) provisions (BSSC,1994) and Uniform Building Code (UBC), 1997 classification. Parameters obtained through geotechnical investigation have been integrated with findings obtained through the subsurface geophysical survey. Joint interpretation has been used to establish inter-relationships among mineral constituents, various textural parameters, and unconfined compressive strength (UCS) with shear wave velocity. It is found that results obtained through the MASW method fitted well with the laboratory test. In both conditions, mineral constituents and textural parameters (grain size, grain shape, grain orientation, and degree of interlocking) control the petrophysical and mechanical properties of rocks and the behavior of shear wave velocity.

Keywords: MASW, mechanical, petrophysical, site characterization

Procedia PDF Downloads 86