Search results for: data standardization

Authors: Noel Paolo Domingo, James Paul Menina, Laurente Ferrer

Abstract:

Most people were forced to stay at home and limit their physical contact during the COVID-19 pandemic. Due to the situation, strict implementation of government policies and safety protocols encouraged consumers to utilize cashless or digital transactions through e-wallets. In this study, the researchers aim to investigate the efficiency of using e-wallets as a payment method during the COVID-19 pandemic in Marikina City. The study examined the efficiency of e-wallets in terms of Usefulness, Convenience, and Safety and Security based on respondents’ assessment. Questionnaires developed by the researchers were distributed to a total of 400 e-wallet users in Marikina City aged 15 years old and above to gather data by using a purposive sampling technique. The data collected was processed using SPSS version 26. Frequency, percentage, and mean were utilized to describe the profile of respondents and their assessment of e-wallets in terms of the three constructs. ANOVA and t-tests were also employed to test the significant differences in the respondent’s assessment when the demographic profile was considered. The study revealed that when it comes to usefulness, e-wallet is efficient while in terms of convenience, and safety and security, e-wallet has been proven to be very efficient. During the COVID-19 pandemic, utilizing e-wallets has been embraced by most consumers. By enhancing its features, more people will be satisfied with using e-wallets.

Keywords: efficiency of e-wallets, usefulness, convenience, safety and security

Procedia PDF Downloads 141

Authors: I. T. Adebayo, J. R. Aworemi, V. A. Ogundele, O. J. Babalola, J. O. Ajayi

Abstract:

The behavior of road users is a critical element in road safety. However, despite the proven effectiveness of the seat belt in reducing injury severity, some drivers still do not use the seat belt. The study, therefore, examined seat belt usage among drivers in Ogbomoso, Oyo State, Nigeria. Face-to-face surveys were conducted to elicit data on seat belt usage and road behaviors on 54,038 drivers plying the General-Lautech Road in Ogbomoso over a period of six months. Data collected were analyzed using both descriptive and inferential statistics. Findings revealed that seat belt usage was moderate among private car drivers in the morning (52.75 percent) and much lower in the evening (37.67 percent), while less than 30 percent of the commercial bus/taxi drivers used the seat during both periods. The paired T-test revealed a significant difference in seat belt usage by all the drivers in the morning and in the evening, as indicated with a T value of 113.977 and the level of significance p < 0.05. The study concluded that there is a significant difference in the usage of the seat belt by both private car and commercial bus/taxi drivers in Ogbomoso as most drivers made use of the seat belt, especially in the morning, to avoid being delayed when flagged down and fined for non-compliance with seat belt usage by the road traffic law enforcement agents. However, most of the drivers cited inadequate/lack of enforcement of compulsory use of seat belts by the relevant agencies and discomfort as the major reasons for not using the seat belt while driving.

Keywords: drivers, road , seat belt, traffic psychology

Procedia PDF Downloads 200

Authors: Muhammad Ashraf

Abstract:

It is experimentally conceded reality that education not just promotes social and intellectual abilities yet, in addition, the incomes of people. The present study is directed to investigate the connection between education level and student income. Data of different education levels is acquired from 300 students through field review from four public sector Universities; two from upper Punjab (University of Gujarat and Government college university-Lahore) and two from lower Punjab (Islamia University-Bahawalpur and The University of Sahiwal). Two-phase estimation is based on the Mincerian human capital model. The first stage presents statistical/descriptive investigation, which shows positive linkage among higher education and income of the students. Econometric estimation is estimated in the second stage by applying Ordinary least Square Method (OLS). Econometric examination reaffirms the importance of higher education as the impact of higher education on students’ incomes accelerates as we move from lower-level education to higher-level education. Educational levels, experience, and working hours are sure and noteworthy with student’s income. Econometric estimation additionally investigated that M. Phil and Ph.D. students have a higher income than bachelor students. Concerning the students, the income profile study commended that the Government ought to give part-time jobs or internships to students as indicated to labor market demand.

Keywords: education, student’s income, experience, universities

Procedia PDF Downloads 117

Authors: K. V. Venugopalan

Abstract:

Micro, Small and Medium Enterprises (MSMEs) have been accepted as the engine of economic growth and for promoting equitable development. The major advantage of the sector is its employment potential at low capital cost. The labour intensity of the MSME sector is much higher than that of the large enterprises. The MSMEs constitute over 90% of total enterprises in most of the economies and are credited with generating the highest rates of employment growth and account for a major share of industrial production and exports. Kerala is a small state in India with the limited land area with high potential in educated human resources need micro, small and medium enterprises for development. Kerala has the highest Physical Quality of Life Index (PQLI) in India and the highest Human Development Index (HDI) at par with the developed countries SME play an important role in alleviating poverty and contribute significantly towards the growth of developing economies. Financial institutions can play a vital role for the promotion of micro, small and medium enterprises in Kerala. The study entitled “Financial Institutions and its role in the promotion of Small and Medium Enterprises in Kerala “examine the progress of MSME in Kerala and India and also the role of financial institutions and the problems faced by entrepreneurs for getting advances with reference to ‘Kerala Financial Corporation’-an agency set up by the government for promoting small and medium enterprises in the state. This study is based on both secondary and primary data. Primary data for the study was collected from those entrepreneurs who availed advances from financial institutions. The secondary data include the investment made, goods and services provided, the employment generated and the number of units registered in MSME sector for the last 10 years in Kerala. The study concluded that financial institutions providing finance with simple procedures and charging smaller interest rates will increase the number of MSME's and also contribute gross state domestic product and reduce the unemployment problem and poverty in the economy.

Keywords: gross state domestic product, human development index, micro, small and medium enterprises

Procedia PDF Downloads 410

Authors: David Quevedo, Diana Coronel

Abstract:

The present article carries out an evaluation of the drinking water system in the Bellavista sector of the city of Azogues, with the purpose of determining the appropriate equipment to record the actual consumption flows of the inhabitants in said sector. Taking into account that the study area is located in a rural and economically disadvantaged area, there is an urgent need to establish a control system for the consumption of drinking water in order to conserve and manage the vital resource in the best possible way, considering that the water source supplying this sector is approximately 9km away. The research began with the collection of cartographic, demographic, and statistical data of the sector, determining the coverage area, population projection, and a provision that guarantees the supply of drinking water to meet the water needs of the sector's inhabitants. By using hydraulic modeling through the United States Environmental Protection Agency Application for Modeling Drinking Water Distribution Systems EPANET 2.0 software, theoretical hydraulic data were obtained, which were used to design and justify the most suitable measuring equipment for the Bellavista drinking water system. Taking into account a minimum service life of the drinking water system of 30 years, future flow rates were calculated for the design of the macro-measuring device. After analyzing the network, it was evident that the Bellavista sector has an average consumption of 102.87 liters per person per day, but considering that Ecuadorian regulations recommend a provision of 180 liters per person per day for the geographical conditions of the sector, this value was used for the analysis. With all the collected and calculated information, the conclusion was reached that the Bellavista drinking water system needs to have a 125mm electromagnetic macro-measuring device for the first three quinquenniums of its service life and a 150mm diameter device for the following three quinquenniums. The importance of having equipment that provides real and reliable data will allow for the control of water consumption by the population of the sector, measured through micro-measuring devices installed at the entrance of each household, which should match the readings of the macro-measuring device placed after the water storage tank outlet, in order to control losses that may occur due to leaks in the drinking water system or illegal connections.

Keywords: macrometer, hydraulics, endowment, water

Procedia PDF Downloads 73

Authors: A. Dėdelė, A. Miškinytė

Abstract:

The assessment of air pollution exposure in different microenvironments is important for better understanding the relationship between health effects caused by air pollution. The recent researches revealed that the level of air pollution in transport microenvironment contributes considerably to the total exposure of air pollution. The aim of the study was to determine air pollution of nitrogen dioxide and to assess the exposure of NO2 dependence on the chosen commuting mode using a global positioning system (GPS). The same travel destination was chosen and 30 rides in three different commuting modes: cycling, walking, and public transport were made. Every different mean of transport is associated with different route. GPS device and travel diary data were used to track all routes of different commuting modes. Air pollution of nitrogen dioxide was determined using the ADMS-Urban dispersion model. The average annual concentration of nitrogen dioxide was modeled for 2011 year in Kaunas city. The geographical information systems were used to visualize the travel routes, to create maps indicating the route of different commuting modes and to combine modelled nitrogen dioxide data. The results showed that there is a significant difference between the selected commuting mode and the exposure of nitrogen dioxide. The concentrations in the microenvironments were 22.4 μg/m3, 21.4 μg/m3, and 25.9 μg/m3 for cycling, walking and public transport respectively. Of all the modes of commuting, the highest average exposure of nitrogen dioxide was found travelling by public transport, while the lowest average concentration of NO2 was determined by walking.

Keywords: nitrogen dioxide, dispersion model, commuting mode, GPS

Procedia PDF Downloads 432

Authors: Mahfoodh Saleh Al Sabbagh, Venkoba Rao

Abstract:

There is plenty of research, both in academic and consultancy circles, about the importance and benefits of employee engagement and customer engagement and how it gives organization an opportunity to reduce variability and improve performance. Customer engagement is directly related to the engagement level of the organization's employees. It is therefore important to measure both. This research drawing from the work of Human Sigma by Fleming and Asplund, attempts to assess engagement level of customer and employees - the human systems of business - in an educational setup. Student is important to an educational institute and is a customer to be served efficiently and effectively. Considering student as customer and faculty as employees serving them, in–depth interviews were conducted to analyze the relationship between faculty and student engagement in two leading colleges in Oman, one from private sector and another from public sector. The study relied mainly on secondary data sources to understand the concept of engagement. However, the search of secondary sources was extensive to compensate the limited primary data. The results indicate that high faculty engagement is likely to lead to high student engagement. Engaged students were excited about learning, loved the feeling of they being cared as a person by their faculty and advocated the organization to other. The interaction truly represents an opportunity to build emotional connection to the organization. This study could be of interest to organizations interest in building and maintaining engagement with employees and customers.

Keywords: customer engagement, consumer psychology, strategy, educational institutes

Procedia PDF Downloads 472

Authors: Nuno Biga

Abstract:

Artificial Intelligence (AI) has the potential to transform management into several impactful ways. It allows machines to interpret information to find patterns in big data and learn from context analysis, optimize operations, make predictions sensitive to each specific situation and support data-driven decision making. The introduction of an 'artificial brain' in organization also enables learning through complex information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) sensitive to context, that provides users useful suggestions to pursue the following operations such as: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time existing bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed and demonstrated through a pilot project (BIG-AI). Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of data is powered in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" (VA) that players can use during the Game. Each participant in the VA permanently asks himself about the decisions he should make during the game to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making, through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, as they gain a better understanding of the issues along time, reflect on good practice and rely on their own experience, capability and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator designated as “Serious Game Controller” (SGC) is responsible for supporting the players with further analysis. The recommended actions by the SGC may differ or be similar to the ones previously provided by the VA, ensuring a higher degree of robustness in decision-making. Additionally, all the information should be jointly analyzed and assessed by each player, who are expected to add “Emotional Intelligence”, an essential component absent from the machine learning process.

Keywords: artificial intelligence, gamification, key performance indicators, machine learning, management simulators, serious games, virtual assistant

Procedia PDF Downloads 105

Authors: Noga Bregman

Abstract:

Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

Procedia PDF Downloads 52

Authors: Dennis Okora Amima Ondieki

Abstract:

Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

Procedia PDF Downloads 102

Authors: Polycarp A. Igbojekwe, Chizoba Amajuoyi, Peterson Nwokorie

Abstract:

The main purpose of this study was to carry out a survey of customer’s aggression towards hotel workers and make contributions on the prevalence and rationale behind customer’s aggression. Data for the study were gathered with a four-point Likert type rating scale. Samples were drawn from frontline hotel employees, managers and customers of twelve (12) hotels selected from three zones of Imo State. Data analyses were conducted using simple percentage, descriptive statistics; and Z-test statistical technique was used to test hypotheses. Among other factors, service failure and verbal abuse by service providers and poor quality product compared to price were identified by customers as the three major factors that can lead to customer aggression. Frontline employees indentified verbal abuse as the most common mode of aggression and that customer aggression causes emotional disturbance in them. The study also revealed that customer aggression is more prevalent in the 1&2 star hotels than it is in 3-5 star hotels. Most of the hotels have not institutionalized systematic approaches needed to effectively face the challenges of customer aggression, thus, customer aggression has become a common feature in the industry. Frontline jobs demand high emotional input. Therefore, we recommend that frontline employees should be given emotional support by their managers and also trained on how to cope with emotional disturbance.

Keywords: customer aggression, emotional disturbance, employee well-being, service failure, verbal abuse

Procedia PDF Downloads 277

Authors: Raj C. Aparna

Abstract:

In India, the mandatory clause on Corporate Social Responsibility (CSR) in Companies Act, 2013 has led to varying responses from the companies. From excessive spending to resistance, the private and the public stakeholders have been considering the law from different perspectives. This paper tends to study the characteristics of CSR spending in India with emphasis on the locations to which the funds are routed. This study examines the effects of CSR fund flow on regional development by considering the growth in Gross State Domestic Product (GSDP), agriculture, education and healthcare using panel data for the 29 States in the country. The results confirm that the CSR funds have been instrumental in improving the quality of teaching and healthcare in the areas around the industrial hubs. However, the study shows that the corporates mostly invest in regions which are easily accessible to them, by their physical presence, irrespective of whether the area is developed or not. Such a skewness is visible in the extensive spending in and around the metropolitan cities, the established centers, in the country to which large chunks of CSR funds are channeled. The results show that there is a variation from what the government had proposed while initiating the CSR law to promote social inclusion and equality in the rural and isolated areas in the country. The implication is that even though societal improvement is the aim of CSR, ease of access to the needy is an essential factor in corporate choices. As poverty and lack of facilities are found in the innermost parts, it is vital to have government policies for their aid as corporate help.

Keywords: corporate social responsibility, geographic spread, panel data analysis, strategic implementation

Procedia PDF Downloads 110

Authors: Akinwale Olusola Mokayode, Emaanuel Adu, Seriki Idowu Ibrahim

Abstract:

Small business can serve as a tool for poverty reduction in South Africa, but it requires adequate support and development for its continuous sustenance in spite of rigorous challenges, especially in the rural environment. This study explored the challenges faced by the small business owners in the rural Eastern Cape Province of South Africa. The objective of the study is to identify the challenges faced by small business owners in the case study area and to examine the effects of those challenges on poverty rate. Survey research design was adopted, with the distribution of structured questionnaire for data collection through a simple random sampling method. Descriptive and inferential statistics was used to analyse the data. Findings showed that small business owners face various challenges in their commercial operations. It was also made clearer that these challenges have effects on the poverty rate as well as crime rate. In conclusion, in other for small businesses to be effective instrument to tackle poverty, certain measure must be taken into considerations. This therefore necessitates recommendation from the researcher that potential and current business owners must seek valuable advice from the more experienced business tycoon and seek information about the business assistance programmes provided by government and private sectors.

Keywords: eastern cape, poverty, poverty reduction, rural, small business, sustainable livelihood

Procedia PDF Downloads 488

Authors: Julie A. Baldwin, Robert T. Trotter, Mark Remiker, C. Loren Buck, Amanda Aguirre, Trudie Milner, Emma Torres, Frank A. von Hippel

Abstract:

Introduction: In the past, there have been concerns about contaminants in the water sources in Yuma, Arizona, including the Colorado River. Prolonged exposure to contaminants, such as perchlorate and heavy metals, can lead to deleterious health effects in humans. This project examined the association between the concentration of environmental contaminants and patient health outcomes in Yuma residents, using a community-engaged approach to data collection. Methods: A community-engaged design allowed community partners and researchers to establish joint research goals, recruit participants, collect data, and formulate strategies for dissemination of findings. Key informant interviews were conducted to evaluate adherence to models of community-based research. Results: The training needs, roles, and expectations of community partners varied based on available resources, prior research experience, and perceived research challenges and ways to address them. Conclusions: Leveraging community-engaged approaches for studies of environmental contamination in marginalized communities can expedite recruitment efforts and stimulate action that can lead to improved community health.

Keywords: community engaged research, environmental contaminants, underserved populations, health equity

Procedia PDF Downloads 139

Authors: Keita Nishio, Takashi Kaburagi, Yosuke Kurihara

Abstract:

Recent advances in medical technology have served to enhance average life expectancy. However, the total time for which the patients are prescribed complete bedrest has also increased. With patients being required to maintain a constant lying posture- also called bedsore- development of a system to detect patient roll-over becomes imperative. For this purpose, extant studies have proposed the use of cameras, and favorable results have been reported. Continuous on-camera monitoring, however, tends to violate patient privacy. We have proposed unconstrained bio-signal measurement system that could detect body-motion during sleep and does not violate patient’s privacy. Therefore, in this study, we propose a roll-over detection method by the date obtained from the bi-signal measurement system. Signals recorded by the sensor were assumed to comprise respiration, pulse, body motion, and noise components. Compared the body-motion and respiration, pulse component, the body-motion, during roll-over, generate large vibration. Thus, analysis of the body-motion component facilitates detection of the roll-over tendency. The large vibration associated with the roll-over motion has a great effect on the Root Mean Square (RMS) value of time series of the body motion component calculated during short 10 s segments. After calculation, the RMS value during each segment was compared to a threshold value set in advance. If RMS value in any segment exceeded the threshold, corresponding data were considered to indicate occurrence of a roll-over. In order to validate the proposed method, we conducted experiment. A bi-directional microphone was adopted as a high-sensitivity pressure sensor and was placed between the mattress and bedframe. Recorded signals passed through an analog Band-pass Filter (BPF) operating over the 0.16-16 Hz bandwidth. BPF allowed the respiration, pulse, and body-motion to pass whilst removing the noise component. Output from BPF was A/D converted with the sampling frequency 100Hz, and the measurement time was 480 seconds. The number of subjects and data corresponded to 5 and 10, respectively. Subjects laid on a mattress in the supine position. During data measurement, subjects—upon the investigator's instruction—were asked to roll over into four different positions—supine to left lateral, left lateral to prone, prone to right lateral, and right lateral to supine. Recorded data was divided into 48 segments with 10 s intervals, and the corresponding RMS value for each segment was calculated. The system was evaluated by the accuracy between the investigator’s instruction and the detected segment. As the result, an accuracy of 100% was achieved. While reviewing the time series of recorded data, segments indicating roll-over tendencies were observed to demonstrate a large amplitude. However, clear differences between decubitus and the roll-over motion could not be confirmed. Extant researches possessed a disadvantage in terms of patient privacy. The proposed study, however, demonstrates more precise detection of patient roll-over tendencies without violating their privacy. As a future prospect, decubitus estimation before and after roll-over could be attempted. Since in this paper, we could not confirm the clear differences between decubitus and the roll-over motion, future studies could be based on utilization of the respiration and pulse components.

Keywords: bedsore, high-sensitivity pressure sensor, roll-over, unconstrained bio-signal measurement

Procedia PDF Downloads 121

Authors: Abdull Halim

Abstract:

The Standard Penetration Test (SPT-N) is the most common in situ test for soil investigations. The Shearing Seismic Standard Penetration Test (SSPT-N), on the other hand, is a new method using shearing wave with propagation exponent equation between the shearing wave, Vs., and hardness, N values without any need for borehole data. Due to the fast and accurate results that can be obtained, the SSPT has found many applications such as in the field rectification buried pipe line, the acid tank settlement and foundation design analyses, and the quality control assessment. Many geotechnical regimes and properties have attempted to correlate both the SSPT and the SPT-N values. Various foundation design methods have been developed based on the outcomes of these tests. Hence, it is pertinent to correlate these tests so that either one of the test can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationship between the SSPT-N and SPT-N values for different types of cohesive soil in Peninsular Malaysia. Data were collected from four different sites, and the correlations were established between the hardness N values, principal stress-strain Mohr circle curve, cohesion, friction angle and vertical effective stress. A positive exponent relationship was found between the shearing wave, sVs., and the hardness N values of the soil. In general, the SSPT-N value was slightly lower than the SPT-N value due to the upper limit boundary of the soil layer.

Keywords: InsituSoil determination; shearing wave; hardness; correlation, SSPT-N, SPT-N

Procedia PDF Downloads 184

Authors: Abdmohammad Mousavi, Mohsen Shams, Mehdi Akbartabar Toori, Ali Mousavizadeh, Mohammad Ali Morowatisharifabad

Abstract:

Introduction: The effectiveness of Transtheoretical Model constructs on dietary behavior change has been subject to questions by some studies. The objective of this study was to determine the relationship between self–efficacy and decisional balance as mediator variables and transfer obese and overweight women among the stages of behavior change of calorie balanced dietary intake. Method: In this cross-sectional study, 448 obese and overweight 20-44 years old women were selected from three health centers in Yasuj, a city in south west of Iran. Anthropometric data were measured using standard techniques. Demographic, stages of change, self-efficacy and decisional balance data were collected by questionnaires and analyzed using One–Way ANOVA and Generalized Linear Models tests. Results: Demographic and anthropometric variables were not different significantly in different stages of change related to calorie intake except the pre-high school level of education (P=.047, OR=502, 95% CI= .255 ~ .990). Mean scores of Self-efficacy ( F(4.425)= 27.09, P= .000), decisional balance (F(4.394), P= .004), and pros (F(4.430)=5.33, P=000) were different significantly in five stages of change. However, the cons did not show a significant change in this regard (F(4.400)=1.83, P=.123). Discussion: Women movement through the stages of changes for calorie intake behavior can be predicted by self efficacy, decisional balance and pros.

Keywords: transtheoretical model, stages of change, self efficacy, decisional balance, calorie intake, women

Procedia PDF Downloads 428

Authors: Fathul Mubin, Budi E. Nurcahya

Abstract:

In 2006, a large earthquake ever occurred in the province of Yogyakarta, which caused considerable damage. This is the basis need to investigate the seismic vulnerability index in around of the earthquake zone. This research is called microzonation of earthquake hazard. This research has been conducted at the site and surrounding of Prambanan Temple, includes homes and civil buildings. The reason this research needs to be done because in the event of an earthquake in 2006, there was damage to the temples at Prambanan temple complex and its surroundings. In this research, data collection carried out for 60 minutes using three component seismograph measurements at 165 points with spacing of 1000 meters. The data recorded in time function were analyzed using the spectral ratio method, known as the Horizontal to Vertical Spectral Ratio (HVSR). Results from this analysis are dominant frequency (Fg) and maximum amplification factor (Ag) are used to obtain seismic vulnerability index. The results of research showed the dominant frequency range from 0.5 to 30 Hz and the amplification is in interval from 0.5 to 9. Interval value for seismic vulnerability index is 0.1 to 50. Based on distribution maps of seismic vulnerability index and impact of buildings damage seemed for suitability. For further research, it needs to survey to the east (klaten) and south (Bantul, DIY) to determine a full distribution maps of seismic vulnerability index.

Keywords: amplification factor, dominant frequency, microzonation analysis, seismic vulnerability index

Procedia PDF Downloads 195

Authors: E. J. Spamer, J. M. Van Zyl, MHA Combrinck

Abstract:

The Unit for Open Distance Learning (UODL) at the North-West University (NWU), South Africa was established in 2013 with its main function to deliver open distance learning (ODL) programmes to approximately 30 000 students from the Faculties of Education Sciences, Health Sciences, Theology and Arts and Culture. Quality operational and administrative processes are key components in the delivery of these programmes and they need to function optimally for students to be successful in their studies. Operational and administrative processes include aspects such as applications, registration, dissemination of study material, availability of electronic platforms, the management of assessment, and the dissemination of important information. To be able to ensure and enhance quality during these processes, it is vital to determine students’ perceptions with regards to these mentioned processes. A questionnaire was available online and also distributed to the 63 tuition centres. The purpose of this research was to determine the perceptions of ODL students from NWU regarding operational and administrative processes. 1903 students completed and submitted the questionnaire. The data was quantitatively analysed and discussed. Results indicated that the majority of students are satisfied with the operational and administrative processes; however, the results also indicated some areas that need improvement. The data gathered is important to identify strengths and areas for improvement and form part of a bigger strategy of qualitative assurance at the UODL.

Keywords: administrative support, ODL programmes, quantitative study, students' perceptions

Procedia PDF Downloads 272

Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

Abstract:

Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

Procedia PDF Downloads 177

Authors: Agâh Tuğrul Korucu, Ismail Fatih Yavuzaslan, Lale Toraman

Abstract:

Nowadays, thanks to development of technology, integration of technology into teaching and learning activities is spreading. Increasing technological literacy which is one of the expected competencies for individuals of 21st century is associated with the effective use of technology in education. The most important factor in effective use of technology in education institutions is ICT teachers. The concept of computer assisted instruction (CAI) refers to the utilization of information and communication technology as a tool aided teachers in order to make education more efficient and improve its quality in the process of educational. Teachers can use computers in different places and times according to owned hardware and software facilities and characteristics of the subject and student in CAI. Analyzing teachers’ use of computers in education is significant because teachers are the ones who manage the course and they are the most important element in comprehending the topic by students. To accomplish computer-assisted instruction efficiently is possible through having positive attitude of teachers. Determination the level of knowledge, attitude and behavior of teachers who get the professional knowledge from educational faculties and elimination of deficiencies if any are crucial when teachers are at the faculty. Therefore, the aim of this paper is to identify ICT teachers' attitudes toward computer-assisted instruction in terms of different variables. Research group consists of 200 prospective ICT teachers studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education CEIT department. As data collection tool of the study; “personal information form” developed by the researchers and used to collect demographic data and "the attitude scale related to computer-assisted instruction" are used. The scale consists of 20 items. 10 of these items show positive feature, while 10 of them show negative feature. The Kaiser-Meyer-Olkin (KMO) coefficient of the scale is found 0.88 and Barlett test significance value is found 0.000. The Cronbach’s alpha reliability coefficient of the scale is found 0.93. In order to analyze the data collected by data collection tools computer-based statistical software package used; statistical techniques such as descriptive statistics, t-test, and analysis of variance are utilized. It is determined that the attitudes of prospective instructors towards computers do not differ according to their educational branches. On the other hand, the attitudes of prospective instructors who own computers towards computer-supported education are determined higher than those of the prospective instructors who do not own computers. It is established that the departments of students who previously received computer lessons do not affect this situation so much. The result is that; the computer experience affects the attitude point regarding the computer-supported education positively.

Keywords: computer based instruction, teacher candidate, attitude, technology based instruction, information and communication technologies

Procedia PDF Downloads 295

Authors: Naritphol Boonjyakiat

Abstract:

This research attempts to investigate the effects of corporate social responsibility and knowledge management factors on students’ job performance of the Silpakorn University’s internship program within various organizations. The goal of this study is to fill the literature gap by gaining an understanding of corporate social responsibility and the knowledge management factors that fundamentally relate to students’ job performance within the organizations. Thus, this study will focus on the outcomes that were derived from a set of secondary data that were obtained using a Silpakorn university’s data base of 200 students and selected employer assessment and evaluation forms from the companies. The results represent the perceptions of students towards the corporate social responsibility aspects and knowledge management factors within the university and their job performance evaluation from the employers in various organizations. The findings indicate that corporate social responsibility and knowledge management have significant effects on students’ job performance. This study may assist us in gaining a better understanding of the integrated aspects of university and workplace environments to discover how to optimally allocate university’s resources and management approaches to gain benefits from corporate social responsibility and knowledge management practices toward students’ job performance within an organizational experience settings. Therefore, there is a sufficient reason to believe that the findings can contribute to research in the area of CSR, KM, and job performance as essential aspect of involved stakeholder.

Keywords: corporate social responsibility, knowledge management, job performance, internship program

Procedia PDF Downloads 332

Authors: Khitem Amiri, Mohamed Farah

Abstract:

Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

Procedia PDF Downloads 280

Authors: F. N. Bolu-Steve, T. A. Ajiboye

Abstract:

A study was carried out on the awareness of counselling needs of psychiatric patients as perceived by medical personnel in the Federal Neuropsychiatric hospital, Aro, Abeokuta, Nigeria. The respondents comprised of medical personnel of the Neuropsychiatric hospital in Aro. Purposive sampling technique was used to select the respondents. The target population of the study consisted of all medical doctors treating the psychiatric patients. A total of 200 respondents participated in the study out of which 143 were males and 57 of them were females. With their years of experience as a medical doctors, 49.5% of them have worked between 1-5 years, 30.5% of the respondents have 6-10 years’ experience while those with 16 years and above experience are 7.0%. The major counselling need of psychiatric patients as expressed by medical doctors is the need to have information about the right balance diet. The data were analyzed using percentages, mean, frequency, Analysis of Variance (ANOVA) and t-test statistical tools. The instrument used for data collection was the structured questionnaire titled “Counselling Needs of Psychiatric Patients Questionnaire” (CNPPQ). This instrument was drafted by the researchers through the review of related literature. The reliability of the instrument was established using test-retest method. A reliability index of 0.74 was obtained. Three of the hypotheses were rejected while two of them were accepted at 0.05 alpha level of significance. Based on the findings of the study, it was recommended that broad based counselling services should be provided to psychiatric patients in order to assist them to develop positive self- image and to cope with their challenges.

Keywords: counselling, needs, psychiatric, medical personnel, patients

Procedia PDF Downloads 422

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 266

Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

Abstract:

In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

Procedia PDF Downloads 90

Authors: Muktar Haruna

Abstract:

This research work examines the International Financial Reporting Standard (IFRS) adoption and value relevance of earnings of listed consumer goods companies in the Nigerian. The population of the study comprises 22 listed consumer goods companies, out of which 15 were selected as sample size of the study. The scope of the study is a 12-year period covering from 2006 to 2018. Secondary data from the annual report of sampled companies were used, which consists of earnings per share (EPS), the book value of equity per share (BVE) as independent variables; firm size (FSZ) as a control variable, and market share price of sampled companies from Nigerian stock exchange as dependent variable. Multiple regressions were used to analyze the data. The results of the study showed that IFRS did not improve the value relevance of earnings after the adoption, which translates to a decrease in value relevance of accounting numbers in the post-adoption period. The major recommendation is that the Nigerian Reporting Council should ensure full compliance to all provisions of IFRS and provide uniformity in the presentation of non-current assets in the statement of financial position, where some present only net current assets leaving individual figures for current assets and liabilities invisible.

Keywords: IFRS, adoption, value relevance, earning per share, book value of equity per share

Procedia PDF Downloads 148

Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, Kh. Khandan-Barani

Abstract:

The textile industries are becoming a major source of environmental contamination because an alarming amount of dye pollutants are generated during the dyeing processes. Organic dyes are one of the largest pollutants released into wastewater from textile and other industrial processes, which have shown severe impacts on human physiology. Nano-structure compounds have gained importance in this category due their anticipated high surface area and improved reactive sites. In recent years several novel adsorbents have been reported to possess great adsorption potential due to their enhanced adsorptive capacity. Nano-MnO2 has great potential applications in environment protection field and has gained importance in this category because it has a wide variety of structure with large surface area. The diverse structures, chemical properties of manganese oxides are taken advantage of in potential applications such as adsorbents, sensor catalysis and it is also used for wide catalytic applications, such as degradation of dyes. In this study, adsorption of Methyl Violet (MV) dye from aqueous solutions onto MnO2 nanoparticles (MNP) has been investigated. The surface characterization of these nano particles was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) were also determined and evaluated.

Keywords: MnO2 nanoparticles, adsorption, methyl violet, isotherm models, kinetic models, surface chemistry

Procedia PDF Downloads 258

Authors: Oladipo Joseph Ajayi, Yakubu Muhammed, Caleb Galadima

Abstract:

This study was conducted to examine the income diversification of smallholder farmers in Bosso Local Government area of Niger state, Nigeria. The specific objectives were to examine the socio-economic characteristics of the farmers, identify the sources of income among the farmers, determine the pattern of income diversification and evaluate the determinants of income diversification of farmers in the study area. A multi-stage sampling technique was used to select 94 respondents for the study. Primary data were used, and these were collected with aid of a well structured interview schedule. Descriptive statistics, diversity index, and Tobit regression model were employed to analyze the data. The mean age of the farmers was 44 years. The average household size was 8 members per household, and the average farming experience was 12 years. 21.27 percent did not have formal education. It was further found that 69.1 percent of the respondents had an income diversity index of 0.3-0.4. This indicated that their level of income diversification was moderately low. The determinants of income diversification in the study area were education, household size, marital status, and primary income. These variables were positively related to income diversification. The study revealed that diversification into various income sources has helped to increase household income to sustain the family demands even though their level of income diversification was low within the study area.

Keywords: diversification, income, households, smallholder farmers

Procedia PDF Downloads 252

Authors: Mayurachat Kanyamee, Srisuda Rassameepong, Narunest Chulakarn

Abstract:

This experimental pretest-posttest control group design aimed to examine the effects of a family-based intervention on increasing fruit and vegetable intake and reduce fat and sugar intake and nutritional status among school-age children. Children were randomized to experimental 68 children and control 68 children. The experimental group received the intervention based on Social Cognitive Theory. The control group received the school’s usual educational program regarding healthy eating behavior. Data were collected via three questionnaires including: demographic characteristics; fruit and vegetable intake; and fat and sugar intake at baseline, sixteen weeks after baseline. Analysis of the data included the use of descriptive statistic and independent t-test. Results revealed the significant differences between the experimental and control group, regarding: fruit and vegetable intake, fat and sugar intake and nutritional status at sixteenth week after baseline. The findings suggest a family-based intervention, based on SCT, appears to be effective to improve eating behavior, and nutritional status of school -age children. So, the intervention can be applied to improve eating behavior among other groups of children.

Keywords: family-based intervention, children, unhealthy food, food safety

Procedia PDF Downloads 275