Search results for: multimodal data

Authors: Rimac Smiljanic Ana, Pepur Sandra, Bulog Ivana

Abstract:

Financial decision-making in the household is not simple, and it demands that the decision-maker has proper knowledge and skills. Usually, high uncertainty, risk, and stress surround household financial decision-making since it is extremely important and critical for household wealth accumulation and for the well-being of all household members. Generally, skilful people tend to have higher confidence in certain tasks they perform, and they achieve better results. Therefore, in the household context, the possession of certain skills by the ones who make financial decisions for the household is of particular importance. This paper addresses financial literacy as an important skill for household decision-making. Apart from financial literacy, the paper also considers other factors, such as employment, education, and age, as significant for household financial decision-making. The analysis is based on quantitative individual-level survey data. The data collection was conducted during January and February 2021 in Croatia through an online survey. To reach a wide variety of participants, the snowball sampling method was used. The result revealed interesting and somewhat puzzling results. Our results point to the importance of financial literacy skills for household decision-making.

Keywords: skill, financial literacy, decision-making, household financijal decision making

Procedia PDF Downloads 97

Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

Abstract:

The study focused on probing the effectiveness of online consumer privacy and protection laws, electronic transaction laws, privacy and data protection laws, and cybercrime legislation amid frequent cyber-attacks and malware types worldwide. An empirical analysis was engaged to uncover ties and causations between the stringency and implementation of these legal structures and the prevalence of cyber threats. A deliberate sample of seventy-eight countries (thirteen countries each from six continents) was chosen as sample size to study the challenges linked with trending regulations and possible panoramas for improving cybersecurity through refined legal approaches. Findings establish if the frequency of cyber-attacks and malware types vary significantly. Also, the result proved that various cybercrime laws differ statistically, and electronic transactions law does not statistically impact the frequency of cyber-attacks. The result also statistically revealed that the online Consumer Privacy and Protection law does not influence the total number of cyber-attacks. In addition, the results implied that Privacy and Data Protection laws do not statistically impact the total number of cyber-attacks worldwide. The calculated value also proved that cybercrime law does not statistically impact the total number of cyber-attacks. Finally, the computed value concludes that combined multiple cyber laws do not significantly impact the total number of cyber-attacks worldwide. Suggestions were produced based on findings from the study, contributing to the ongoing debate on the validity of legal approaches in battling cybercrime and shielding consumers in the digital age.

Keywords: cybercrime legislation, cyber attacks, consumer privacy and protection law, detection, electronic transaction law, prevention, privacy and data protection law, prohibition, prosecution

Procedia PDF Downloads 42

Authors: Philip Speranza

Abstract:

As everyday transit options are shifting from autocentric to pedestrian and bicycle oriented modes for healthy living, downtown streets are becoming more attractive places to live. However, tools and methods to measure the natural environment at the small scale of streets do not exist. Fortunately, a combination of mobile data collection technology and parametric urban design software now allows an interface to relate urban ecological conditions. This paper describes creation of an interactive tool to measure urban phenomena of air, water, and heat/light at the scale of new three-by-three block pedestrianized areas in Barcelona called Superilles. Each Superilla limits transit to the exterior of the blocks and to create more walkable and bikeable interior streets for healthy living. The research will describe the integration of data collection, analysis, and design output via a live interface using parametric software Rhino Grasshopper and the Human User Interface (UI) plugin.

Keywords: transit, urban design, GIS, parametric design, Superilles, Barcelona, urban ecology

Procedia PDF Downloads 247

Authors: Michael C. Nwaohia

Abstract:

Whereas anecdotal evidence supports the notion that increase in information technology (IT) know-how may enhance output of professionals in the accounting sector, this has not been systematically explored in the Nigerian context. Against this background, this paper examines the correlation between knowledgeability of IT and level of performance at everyday auditing and accounting tasks. It utilizes primary and secondary data from selected business organizations in Lagos, Nigeria. Accounting staff were administered structured questionnaires which, amongst other things, sought to examine knowledge and exposure to information technology prior to joining the firms and current level of performance based on self-reporting and supervisor comments. In addition, exposure to on-the-job IT training and current level of performance was examined. The statistical analysis of the data was done using the SPSS package. The results strongly suggest that prior exposure to IT skills enabled accounting professionals to better flexibly fit into the dynamic environment in which contemporary business takes place. Ultimately, the paper attempts to explicate some of the implications of these findings for individuals and business firms.

Keywords: accounting, firms, information technology, professional behavior

Procedia PDF Downloads 235

Authors: Iqbal Ahmed Chowdhury

Abstract:

Diarrhea is considered to be one of the influential factors of child death in Bangladesh. While it is known that diarrhea is a water-driven disease, due to the lack of studies, little is known about the extent to which various feeding patterns contribute to such an incidence. Our paper intends to fill this gap by looking into different feeding patterns and their influence on diarrhea incidence among children in Bangladesh. Using data collected for the Demographic and Health Survey, 2014, this paper reveals that feeding patterns can influence the diarrhea incidence among this group of children to a great extent. This paper finds that the incidence of diarrhea is likely to elevate if diarrhea-affected children are fed plain water from any source and any kind of juice. However, breastfeeding, feeding soup or clear broth, prescribed baby food, and clean water from a tube well tend to help fight diarrhea incidence among children in Bangladesh. The results are found to be consistent even after controlling for sociodemographic variables, including age and sex of children, age and education qualification of the parent, and the number of children in the family. The results of this study could contribute to treating diarrhea among children in Bangladesh as well as similar other countries in the world.

Keywords: feeding patterns, diarrhea, Bangladesh, children

Procedia PDF Downloads 109

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

Abstract:

Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

Procedia PDF Downloads 265

Authors: Ange Meghane Hakizimana, Landry Ndikuriyo

Abstract:

Retention of employees in the hospitality industry is a recurrent agenda in the organization involving all the combined efforts to maintain the best available laborer. The general objective of this research is to assess the impact of effective employee retention strategies on the success of the hotel industry at Galileo Hotel, Huye District in Rwanda, for the period of 2019-2021. Herzberg Two Factor Theory and Equity Theory were used. The study adopted a descriptive research design. Descriptive research design allowed us to study the elements in their natural form without making any alterations to them. Secondary data and primary data and the data collected were sorted and entered into the statistical packages for social sciences for analysis (SPSS) version 26. Frequencies, descriptive statistics and percentages were used to analyze and establish extent to which employee retention strategies impact the success of the hotel industry of Rwanda and this was analyzed using regression and correlation analysis. The results revealed that employee training and development had an influence of 24.8% on the success of the hotel industry in Rwanda. According to the results of our study, the employee reward system contributes 20.7% to the success of the hotel industry in Rwanda, the value of t is 3.475 and this is greater than the standard t value score of 1.96, p-value is 0.002. Therefore the employee reward system has a great positive impact on the success of the hotel industry in Rwanda. The results also show that 15.7% of the success of the hospitality industry in Rwanda is due to the work environment of employees. With a t-value of 4.384 and a p-value of 0.000, the above statistics show a positive impact of the employees' working environment on success of the hospitality industry in Rwanda. A priority to the retention of their employees should be given by the hotel industry and its managers because it has already been proven that it is an effective approach to offering good customer service. In addition, employee retention reduces expenses associated with employee recruitment and turnover.

Keywords: success, hotel industry, training and development, employee reward system, employee work environment

Procedia PDF Downloads 96

Authors: Zarah M. Bello, Nathan Baddoo, Mariana Lilley, Paul Wernick

Abstract:

In this paper, we present findings from a multi-part study to evaluate candidate elements reflecting the level of digital capability maturity (DCM) in higher education and the relationship between these elements. We will use these findings to propose a model of DCM for educational institutions. We suggest that the success of learning in higher education is dependent in part on the level of maturity of digital capabilities of institutions as well as the abilities of learners and those who support the learning process. It is therefore important to have a good understanding of the elements that underpin this maturity as well as their impact and interactions in order to better exploit the benefits that technology presents to the modern learning environment and support its continued improvement. Having identified ten candidate elements of digital capability that we believe support the level of a University’s maturity in this area as well as a number of relevant stakeholder roles, we conducted two studies utilizing both quantitative and qualitative research methods. In the first of these studies, 85 electronic questionnaires were completed by various stakeholders in a UK university, with a 100% response rate. We also undertook five in-depth interviews with management stakeholders in the same university. We then utilized statistical analysis to process the survey data and conducted a textual analysis of the interview transcripts. Our findings support our initial identification of candidate elements and support our contention that these elements interact in a multidimensional manner. This multidimensional dynamic suggests that any proposal for improvement in digital capability must reflect the interdependency and cross-sectional relationship of the elements that contribute to DCM. Our results also indicate that the notion of DCM is strongly data-centric and that any proposed maturity model must reflect the role of data in driving maturity and improvement. We present these findings as a key step towards the design of an operationalisable DCM maturity model for universities.

Keywords: digital capability, elements, maturity, maturity framework, university

Procedia PDF Downloads 143

Authors: Muthukumarasamy Govindarajan

Abstract:

Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

Procedia PDF Downloads 142

Authors: Gholamreza Madad

Abstract:

The role of medical equipment in modern advanced hospitals is irrefutable. Despite limited financial resources, developing countries have taken an uncontrollable manner to the purchase of complex and expensive equipment, although they have not taken good maintenance to keep these huge capitals. In our country, limited studies have indicated that the irregularities exist in the management of medical equipment maintenance. Research method: The research was done as a cross-sectional one, and in this study, a questionnaire was used to collect data in 10 hospitals. After distributing and collecting questionnaires in person, the collected data were analyzed using descriptive statistics and SPSS software. Research findings: According to the obtained results from the four dimensions of the management of medical equipment maintenance, only (maintenance planning) was in a moderate position and other components with a score of less than 50% were at a low level. There was a direct relationship between the total score of maintenance management and guidance points and coordination of medical equipment maintenance, and as well as the age of hospital managers. Discussion and conclusion: In sum, we can say that problems such as lack of skilled staff in medical engineering departments of hospitals, lack of funds and unaware of the authorities of medical engineering units to their duties have caused that the maintenance situation of medical equipment maintenance is in poor condition (near average). The low inexperience of the authorities of the unit has also contributed to this problem.

Keywords: equipment, maintenance, medical equipment, hospitals

Procedia PDF Downloads 162

Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 297

Authors: Dong Wu, Michael Grenn

Abstract:

Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

Procedia PDF Downloads 79

Authors: Nur Aidya Hanum Aizam, Vikneswary Uvaraja

Abstract:

The agenda of showing the scheduled time for performing certain tasks is known as timetabling. It widely used in many departments such as transportation, education, and production. Some difficulties arise to ensure all tasks happen in the time and place allocated. Therefore, many researchers invented various programming model to solve the scheduling problems from several fields. However, the studies in developing the general integer programming model for many timetabling problems are still questionable. Meanwhile, this thesis describe about creating a general model which solve different types of timetabling problems by considering the basic constraints. Initially, the common basic constraints from five different fields are selected and analyzed. A general basic integer programming model was created and then verified by using the medium set of data obtained randomly which is much similar to realistic data. The mathematical software, AIMMS with CPLEX as a solver has been used to solve the model. The model obtained is significant in solving many timetabling problems easily since it is modifiable to all types of scheduling problems which have same basic constraints.

Keywords: AIMMS mathematical software, integer linear programming, scheduling problems, timetabling

Procedia PDF Downloads 436

Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

Abstract:

Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

Procedia PDF Downloads 115

Authors: Melis Inalpulat, Levent Genc

Abstract:

Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), and Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased % 29 between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32 °C in 1984 and 27-33 °C in 2014. Minimum temperature of agricultural lands was increased 3 °C and reached to 23 °C. In contrast, maximum temperature of A class decreased to 41 °C from 44 °C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2 °C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: census data, landsat, land surface temperature (LST), land use land cover (LULC)

Procedia PDF Downloads 392

Authors: Jhoga Parth, T. Nasar, K. V. Anand

Abstract:

An idealized definition of shoreline is that it is the zone of coincidence of three spheres such as atmosphere, lithosphere, and hydrosphere. Despite its apparent simplicity, this definition in practice a challenge to apply. In reality, the shoreline location deviates continually through time, because of various dynamic factors such as wave characteristics, currents, coastal orientation and the bathymetry, which makes the shoreline volatile. This necessitates us to monitor the shoreline in a temporal basis. If shoreline’s nature is understood at particular coastal stretch, it need not be the same trend at the other location, though belonging to the same sea front. Shoreline change is hence a local phenomenon and has to be studied with great intensity considering as many factors involved as possible. Erosion and accretion of sediment are such natures of a shoreline, which needs to be quantified by comparing with its predeceasing variations and understood before implementing any coastal projects. In recent years, advent of Global Positioning System (GPS) and Geographic Information System (GIS) acts as an emerging tool to quantify the intra and inter annual sediment rate getting accreted or deposited compared to other conventional methods in regards with time was taken and man power. Remote sensing data, on the other hand, paves way to acquire historical sets of data where field data is unavailable with a higher resolution. Short term and long term period shoreline change can be accurately tracked and monitored using a software residing in GIS - Digital Shoreline Analysis System (DSAS) developed by United States Geological Survey (USGS). In the present study, using DSAS, End Point Rate (EPR) is calculated analyze the intra-annual changes, and Linear Rate Regression (LRR) is adopted to study inter annual changes of shoreline. The shoreline changes are quantified for the scenario during the construction of breakwater in Ponnani river inlet along Kerala coast, India. Ponnani is a major fishing and landing center located 10°47’12.81”N and 75°54’38.62”E in Malappuram district of Kerala, India. The rate of erosion and accretion is explored using satellite and field data. The full paper contains the rate of change of shoreline, and its analysis would provide us understanding the behavior of the inlet at the study area during the construction of the training walls.

Keywords: DSAS, end point rate, field measurements, geo-informatics, shoreline variation

Procedia PDF Downloads 258

Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

Abstract:

We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

Procedia PDF Downloads 369

Authors: B. G. Abiona

Abstract:

This study compared profitability analysis of integrated and non-integrated fish farming in Ogun State, Nigeria. Primary data were collected using interview guide. Random sampling techniques was used to select 133 non-integrated fish farmers (NIFF) and 216 integrated fish farmers (IFF) (n = 349) from the study area. Data were analyzed using Chi-square, T-test and Pearson Product moment correlation. Results showed that 92.5% of NIFF was male compared to IFF (90.7%). Also, 96.8% of IFF and 79.7% of NIFF were married. The mean ages of sampled farmers were 44 years (NIFF) and 46 years (IFF) while the mean fish farming experiences were 4 years (NIFF) and 5 years (IFF). Also, the average net profit per year of integrated fish farmers was ₦162,550 compared to NIFF (₦61,638). The chi-square analyses showed that knowledge of fish farming had significant relationship with respondents sex (χ2 = 9.44, df = 2, p < 0.05), age (r = 0.20, p< 0.05) and farming experience (r = p = 0.05). Significant differences exist between integrated and non-integrated fish farming, considering their knowledge of fish farming (t = 21.5, χ = 43.01, p < 0.05). The study concluded that IFF are more profitable compared to NIFF. It was recommended that private investors and NGOs should sponsor short training and courses which will enhance efficiency of fish farming to boost productivity among fish farmers.

Keywords: profitability analysis, farms, integration

Procedia PDF Downloads 336

Authors: Zainab A. Alaghbri, Labiba A., Esam A.

Abstract:

Tuberculosis (TB) is the fourth leading cause of death in Yemen and is considered a major priority by the Ministry of Public Health. The war in Yemen has led to the emergence of one of the worst humanitarian crises in the world. These circumstances may lead to exacerbate the situation of tuberculosis. This study aims to describe the trend and incidence of TB in north and east governorates, Yemen 2019-2021 and provide recommendations for interventions. A descriptive analysis was conducted during July to September 2022. Data of TB cases were obtained from the national tuberculosis program as soft copy. The Data included the TB case collected and diagnosed during 2019-2021. The data contains the following variables: Sex, age, governorates, smear-positive cases, extra-pulmonary cases, and treatment outcomes. 16791 TB cases were notified for an overall case notification rate 65.5/100000 for all forms (smear positive and Extra-pulmonary), There was a slightly declined in 2020 and 2021 by 1%. Both the pulmonary smear positive and Extra pulmonary rates were slightly decreased from 8.8 to 7.7 and 13.5 to 12.8 / 100, 000 populations respectively. For Tuberculosis cases by type of patient, the incidence of extra-pulmonary was the highest (12,9, 11.3 and 12,2/100000) over the three years. However, the incidence of pulmonary failure was the lowest. The majority of cases were in the age group 25-34. The overall treatment success rate for smear-positive patients was 88%. Of the 627 patients with documented unsuccessful outcomes (e.g., failure, death, and default), 165 (23%) died, 52 (8.3%) failed treatment, and 410 (65%) defaulted. Overall, the magnitude of tuberculosis decreased over the periods reviewed. The proportion of Extra-pulmonary TB was the highest. The success rate achieved after treatment was below the levels established by the WHO End Tuberculosis Strategy (90%). Failure to complete treatment may be responsible for the low success rate. Monitoring and addressing the risk factors that were associated with treatment outcomes and duration may help improve the likelihood of achieving favorable outcomes among cases of smear-positive pulmonary TB.

Keywords: tuberculosis, trend, incidence, yemen

Procedia PDF Downloads 97

Authors: Kibret Berhanu Getinet

Abstract:

Off-farm income diversification by farm rural households has gained the attention of researchers and policymakers due to the fact that agriculture failed to meet the needs of people in developing countries like Ethiopia. The objective of this study was to investigate income diversification strategies into off-farm activities among rural households in Hawassa Zuria Woreda, Sidama National Regional State, Ethiopia. The study used primary and secondary data sources for the primary data collection questionnaire employed as a data collection instrument. A multistage sampling technique was used to collect data from a total of 197 sample households from four kebeles of the study area. Descriptive statistics, as well as econometrics methods of data analysis, were employed. The descriptive statistics result indicates that the majority of sample rural households (68.53 %) have engaged in off-farm income diversification activities while the remaining 31.47% of households did not participate in the diversification in the study area. The choice of participants among the strategies indicates that 6.60% of respondents participated in off-farm wage employment, 30.46% participated in off-farm self-employment, and about 31.47% of them participated in both off-farm wage employment. The study revealed that the share of off-farm income in total annual earnings of households was about 48.457%, and thus, the off-farm diversification significantly contributes to the rural household income. Moreover, binary and multinomial logistic regression models were employed to identify factors that affect the participation and the choices of the off-farm income diversification strategies, respectively. The binary logit model result indicated that agro-ecological zone, education status of the households, available technical skills of the household, household saving, total livestock owned by the households, access to electricity, road access and being married of household head were significant and positively affected the chance of diversification in off-farm activities while the on-farm income of households is negatively affected the chance of diversification. Similarly, the multinomial logistic regression model estimate revealed that agroecological zone, on-farm income, available technical skills, household savings, and access to electricity are positively related and significantly influenced the household’s choice of employment into off-farm wage employment. The off-farm self-employment diversification choice is significantly influenced by on-farm income, available technical skills, household savings, total livestock owned, and access to electricity. Moreover, the result showed that the factors that affect the choice of farm households to engage in both off-farm wage and self-employment are ecological zone, education status, on-farm income, available technical skills, household own saving, market access, total livestock owned, access to electricity and road access. Thus, due attention should be given to addressing the demographic, socio-economic, and institutional constraints to strengthen off-farm income diversification strategies to improve the income of rural households.

Keywords: off-farm, incoem, diversification, logit model

Procedia PDF Downloads 55

Authors: Oral S. Saulters, Shanon D. Goldberg, Wendy A. Staples, Ellena I. Martinez, Lorie M. Sanchez, Diego E. Archuleta, Deborah L. Williams, Scot D. Johnson

Abstract:

To address an important set of unverified field conditions, the Los Alamos National Laboratory Waste Compliance and Tracking System (WCATS) Wall-to-Wall Team performed an unprecedented and advanced inventory. This reconciliation involved confirmation analysis for approximately 5850 hazardous, low-level, mixed low-level, and transuranic waste containers located in more than 200 staging and storage areas across 33 technical areas. The interdisciplinary team scoped, planned, and developed the multidimensional assessments. Through coordination with cross-functional site hosts, they were able to verify and validate data while resolving discrepancies identified in WCATS. The results were extraordinary with an updated inventory, tailored outreach, more cohesive communications, and timely closed-loop feedback.

Keywords: circular economy, environmental performance data, social-ecological-technological systems, waste management

Procedia PDF Downloads 128

Authors: S. M. Anowarul Haque, Md. Asiful Islam

Abstract:

Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

Procedia PDF Downloads 171

Authors: Chutima Klaysung

Abstract:

This research aims to study the factors that influence the decision to choose the spa service of consumers in Amphawa, Samut Songkhram, Thailand. The research method will use quantitative research; data were collected by questionnaires distributed to spa consumers, both female and male, aged between 20 years and 70 years in the Amphawa, Samut Songkhram area for 400 samples by convenience sampling method. The data were analyzed using descriptive statistics including percentage, mean, standard deviation and inferential statistics, including Pearson correlation for hypothesis testing. The results showed that the demographic variables including age, education, occupation, income and frequency of access to service spa were related to the decision to choose the spa service of consumers in Amphawa, Samut Songkhram. In addition, the researchers found the marketing mixed factors such as products, prices, places, promotion, personnel selling, physical evidence and processes were associated with the decision to choose the spa service of consumers in Amphawa, Samut Songkhram, Thailand.

Keywords: consumer in amphawa, samut songkhram, decision to choose the spa service, marketing mixed factor, spa service

Procedia PDF Downloads 238

Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

Abstract:

The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

Procedia PDF Downloads 76

Authors: V. Davaakhuu, D. Tserendagva, D. Amarsaikhan, T. Altanstetseg

Abstract:

In this study we aimed to detect main risk factors for diabetes in Mongolia and obtain data we used survey modified questionnaire. Survey data were obtained from 634 valid nurses (day work nurses-317, shift work nurses-317). Participants who were pregnant, less than 20 years old and no check for fasting glucose level were excluded from the survey in order to determine the risk factors of diabetes. Our study result shows the main risk factors of diabetes were physical inactivity, overweight and obesity, alcohol and tobacco use and lack of vegetable and fruit consumption. Peripheral blood glucose level was normal in subjects with BMI 26.28 ± 0.56, but 20 % of the subjects with normal blood glucose level were obese. Blood glucose level was higher in subjects with BMI 28.63 ± 2.32 and 36 % of them were obese. According to our study results, 3.62% of the surveyed population were identified having no diabetes risk factors, 52.3% were at risk, 28.8% were in higher risk for diabetes by the WHO criteria. In general, the prevalence of blood glucose were especially higher in shift work nurses.

Keywords: day work nurses, shift work nurses, BMI, WHR

Procedia PDF Downloads 593

Authors: Koko Wangjam, Naresh Kumar Sharma

Abstract:

The concern for most public health policies and decision- makers is the equitable distribution of health care resource of the nation. Also, in public health care system, the primary aim is assuaging the burden of the disease. Objective: This paper captures and evaluates some important theories in equity in health with its relevance with the ART program in India. Methodology: The paper is exploratory and descriptive study based on secondary data. The sources of secondary data are published official reports from NACO (National AIDS Control Organisation), United Nations AIDS Program (UNAIDS), World Health Organisation (WHO) etc. Observation: The roll-out of the ART program in 2004 by the Govt. of India made a paradigm shift in HIV/AIDS scenario in the country. Conclusion: There are many theoretical injunctions in most of the principles and approaches in existing theories of health equity. The enervation of HIV infection by taking ART drugs had helped in curbing the prevalence and the fact that it is provided at free of cost has proven this program to be an epitome in distributive justice in public health.

Keywords: art program, burden of the disease, health equity, hiv/aids

Procedia PDF Downloads 394

Authors: Gyumin Hwang, Jihong Lee

Abstract:

This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1 m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: chirp spread spectrum, indoor localization, pattern-matching, time of arrival, multi-path, mahalanobis distance, reception rate, simultaneous localization and mapping, laser range finder

Procedia PDF Downloads 244

Authors: Xizhen Zhou, Yanjie Ji

Abstract:

The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

Procedia PDF Downloads 71

Authors: Tumisang Seodigeng, Hilary Rutto

Abstract:

In this study we investigate the use of a laboratory batch digester to derive kinetic parameters for anaerobic digestion of garden grass and cattle dung. Laboratory experimental data from a 5 liter batch digester operating at mesophilic temperature of 32 C is used to derive parameters for Michaelis-Menten kinetic model. These fitted kinetics are further used to predict the scale-up parameters of a batch digester using DynoChem modeling and scale-up software. The scale-up model results are compared with performance data from 20 liter, 50 liter, and 200 liter batch digesters. Michaelis-Menten kinetic model shows to be a very good and easy to use model for kinetic parameter fitting on DynoChem and can accurately predict scale-up performance of 20 liter and 50 liter batch reactor based on parameters fitted on a 5 liter batch reactor.

Keywords: Biogas, kinetics, DynoChem Scale-up, Michaelis-Menten

Procedia PDF Downloads 497

Authors: Thanawat Chuleekiat

Abstract:

Socketing of bored piles in rock is always seen as a matter of debate on construction sites between consultants and contractors. The socketing depth normally depends on the type of rock, depth at which the rock is available below the pile cap and load carrying capacity of the pile. In this paper, the review of field load test data of drilled shaft socketed in weathered limestone conducted using conventional static pile load test and dynamic pile load test was made to evaluate a unit shaft friction for the bored piles socketed in weathered limestone (weak rock). The borehole drilling data were also reviewed in conjunction with the pile test result. In addition, the back-calculated unit shaft friction was reviewed against various empirical methods for bored piles socketed in weak rock. The paper concludes with an estimated ultimate unit shaft friction from the case study in Qatar for preliminary design.

Keywords: piled foundation, weathered limestone, shaft friction, rock socket, pile load test

Procedia PDF Downloads 180