Search results for: streaming data

Authors: Obaidullah Molakhail, R. Reshmi

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Objective: This study explains the impact of talent management on employee loyalty in the IT sector in Kerala, India. Methods: A descriptive investigation was conducted within the confines of this paper to gain insight into the ramifications of talent management on enhancing employee allegiance to the organization. A quantitative study was conducted by distributing questionnaires to respondents in three IT companies. One hundred and seventy questionnaires were distributed, with `150 being utilized and the remainder being discarded. Data was collected from various departments within the companies, and the selection of respondents was conducted randomly. statistical software SPSS (version 26) was used to analyze the data and determine the outcomes. Results: The objective was examined through Pearson correlation to find the relation, and linear regression was used to find the strength of variables as talent management is independent and employee loyalty is the dependent variable. The results reveal that talent management is essential to employee loyalty. If there is a high-level implementation of talent management practices, there will be low turnover rate, it reflected employee loyalty towards the organization. Conclusion: Strategic planners ought to devote their attention to the realm of talent management due to the existence of a correlation between talent management and the loyalty exhibited by employees. The results of this study suggest that there is a favorable correlation between talent management and employee loyalty.

Keywords: talent management, employee loyalty, IT sector, quantitative study

Procedia PDF Downloads 59

Authors: Turkyh Alotibi, Ghadah Obeid Alrasheed, Afaf Saad Alshaibani, Moneerah Obeid Alrasheed

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This study explores factors that influence MBA enrolment and investigates strategic prerequisites for developing a viable online MBA program at Alfaisal University in the Kingdom of Saudi Arabia. It compares students’ perspectives about online MBA against the face-to-face on-site MBA program. With the self-administered online survey tool, we collected data from 52 first- and second-year MBA students enrolled at Alfaisal University for the 2021 Fall Semester. The data from the survey questionnaire, distributed at the university’s College of Business, reports that approximately 60% of MBA students prefer face-to-face, in-person courses. Their preference for considering an online MBA, primarily rests on two factors, the university’s ranking (68% would enroll for an online MBA program offered by Harvard Business School) and 34.07% for the program timing (timetable). Alfaisal University’s outstanding ranking makes it viable to offer an online MBA either independently or in collaboration with other internationally reputed business schools. The paper contains useful insights to set “the strategic agenda for Online MBA program” in no accredited University but with a good reputation. The information from the case study could be useful for supporting the strategic intent to start an Online MBA program in Saudi Arabia.

Keywords: online MBA, online education demand, university management, course evaluation, blended learning

Procedia PDF Downloads 127

Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Seyran Naghdi

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Background: Orphan drug development is limited by very high costs attributed to the research and development and small size market. How health policymakers address this challenge to consider both supply and demand sides need to be explored for directing the policies and plans in the right way. The price is an important signal for pharmaceutical companies’ profitability and the patients’ accessibility as well. Objective: This study aims to find out the orphan drugs' price-setting patterns and approaches in health systems through a systematic review of the available evidence. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach was used. MedLine, Embase, and Web of Sciences were searched via appropriate search strategies. Through Medical Subject Headings (MeSH), the appropriate terms for pricing were 'cost and cost analysis', and it was 'orphan drug production', and 'orphan drug', for orphan drugs. The critical appraisal was performed by the Joanna-Briggs tool. A Cochrane data extraction form was used to obtain the data about the studies' characteristics, results, and conclusions. Results: Totally, 1,197 records were found. It included 640 hits from Embase, 327 from Web of Sciences, and 230 MedLine. After removing the duplicates, 1,056 studies remained. Of them, 924 studies were removed in the primary screening phase. Of them, 26 studies were included for data extraction. The majority of the studies (>75%) are from developed countries, among them, approximately 80% of the studies are from European countries. Approximately 85% of evidence has been produced in the recent decade. Conclusions: There is a huge variation of price-setting among countries, and this is related to the specific pharmacological market structure and the thresholds that governments want to intervene in the process of pricing. On the other hand, there is some evidence on the availability of spaces to reduce the very high costs of orphan drugs development through an early agreement between pharmacological firms and governments. Further studies need to focus on how the governments could incentivize the companies to agree on providing the drugs at lower prices.

Keywords: orphan drugs, orphan drug production, pricing, costs, cost analysis

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Authors: Madalin Enache, Simona Neagu, Roxana Cojoc, Ioana Gomoiu, Delia Ionela Dobre, Ancuta Roxana Trifoi

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Various types of halophilic and halotolerant microorganisms able to be cultivated in laboratory on culture media with a wide range of sodium chloride content are isolated from several salted environments. The extracellular enzymes of these microorganisms showed the enzymatic activity in these spectrums of salinity thus being attractive for several biotechnological processes developed at high ionic strength. In present work, a number of amylase, protease, esterase, lipase, cellulase, pectinase, xilanases and innulinase were identified for more than 50th bacterial strains isolated from water samples and sapropelic mud from four saline and hypersaline lakes located in Romanian plain. On the other hand, the cellulase and pectinase activity were also detected in some halotolerant microorganisms isolated from secondary agricultural flow of grapes processing. The preliminary data revealed that from totally tested strains seven harbor proteases activity, eight amylase activity, four for esterase and another four for lipase, three for pectinase and for one strain were identified either cellulase or pectinase activity. There were no identified enzymes able to hydrolase innulin added to culture media. Several strains isolated from sapropelic mud showed multiple extracellular enzymatic activities, namely three strains harbor three activities and another seven harbor two activities. The data revealed that amylase and protease activities were frequently detected if compare with other tested enzymes. In the case of pectinase were investigated, their ability to be used for increasing resveratrol recovery from material resulted after grapes processing. In this way, the resulted material from grapes processing was treated with microbial supernatant for several times (two, four and 24 hours) and the content of resveratrol was detected by High Performance Liquid Chromatography method (HPLC). The preliminary data revealed some positive results of this treatment.

Keywords: halophilic microorganisms, enzymes, pectinase, salinity

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Nipon Sasithornsaowapa

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This research aims to study the impact of personality and family status on women executives’ career success of the primary education department of Thailand. The independent variable includes three factors, namely family status, personality, and knowledge-skill-experience, while the dependent variable is the career success. The population of this study includes 2,179 female management officials in the department of primary education. A total of 400 female managers is interviewed and utilized as a sample group. A questionnaire is developed and used as a research tool for data collection. Content analysis is performed to get the quantitative data. Descriptive statistics in this research is conducted by SPSS program. The findings revealed that personality and family status of samples have an influence on the overall career success of women executives in terms of their objective career success. However, in terms of specific factors of personality or family status, it is found that there is no relevance of each factor on the women executives’ career success. It can be concluded that the factor affecting the women executives’ career success is subjective career success including the happiness and enjoyment with the job not factor concerning materials. Their success is the result of each individual working experience. However, their personal characteristics do not affect their success.

Keywords: career success, women executives, primary education, knowledge-skill-experience

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Authors: Abhijitsinh Gohil, Kaushal Wadhvaniya, Kuldipsinh Jadeja

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Road Safety is a multi-sectoral and multi-dimensional issue. An effective model can assess the risk associated with highway safety. A questionnaire survey is very essential to identify the events or activities which are causing unsafe condition for traffic on an urban highway. A questionnaire of standard questions including vehicular, human and infrastructure characteristics can be made. Responses from the age wise group of road users can be taken on field. Each question or an event holds a specific risk weightage, which contributes in creating an inappropriate and unsafe flow of traffic. The probability of occurrence of an event can be calculated from the data collected from the road users. Finally, the risk score can be calculated by considering the risk factor and the probability of occurrence of individual event and addition of all risk score for the individual event will give the total risk score of a particular road. Standards for risk score can be made and total risk score can be compared with the standards. Thus road can be categorized based on risk associated and traffic safety on it. With this model, one can assess the need for traffic safety improvement on a given road, and qualitative data can be analysed.

Keywords: probability of occurrence, questionnaire, risk factor, risk score

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Chi T. L. Pham, L. Vu, Hoang T. Le, Huong T. T. Le, Quyen T. T. Bui

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Burning joss paper and incense during religious and cultural ceremonies is common in Vietnam. This study aims to measure the impact of burning joss paper and incense during Vu Lai festival (full moon of July) in Vietnam. Data of Hanoi air quality in year 2020 was used. Interrupted time series analysis was employed to examine the changes in pattern of various air quality indicators before and after the festival period. The results revealed that burning joss paper and incense led to an immediate increase of 15.94 units in the air quality index on the first day, which gradually rose to 47.4 units by the end of the full moon period. Regarding NO2, PM10, and PM25, there was no significant immediate change at the start of the intervention period (August 29th, 2020). However, significant increases in levels and an upward trend were observed during the intervention time, followed by substantial decreases after the intervention period ended (September 3rd, 2020). This analysis did not find a significant impact on CO, SO2, and O3 due to burning joss paper and incense. These findings provide valuable insights for policymakers and stakeholders involved in managing and enhancing air quality in regions where such practices are prevalent.

Keywords: air pollution, incense, ITSA, joss paper, religious activities

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Maide Yesilyurt, Saide Faydalı

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Patients experience pain at different intensities in postoperative. The diagnosis of the pain, the assessment and the success of the treatment and care make the measurement of this finding compulsory. The aim of the study is to determine the evaluation differences numeric pain scales. The descriptive study was conducted with 360 patients with in postoperative. The data were obtained from questionnaires related to six numeric pain scales most preferred in clinical use, and a face-to-face interview technique was used by the researcher. Regarding to numeric pain scale, questions include forth positive and one negative statement. In evaluating the data; chi-square and Pearson correlation tests were used. For the study, the patients’ informed consents, the institution and the ethics committee received permission. In this study, patients' ages are between 18-80, 95.8% of the patients were not informed about pain assessment. Patients evaluated the 5-item numeric scale as the easy, can be answered quickly, accurate, and appropriate for clinical use and the 101 items numeric scale as complex than other scales. Regarding to numeric pain scales with positive statements between age, marital status, educational status, previous surgery, having chronic disease and getting information about pain assessment significant difference has been detected. All numeric pain scales are correlated to each other. As a result, it was determined that as the items in the numerical scales decreased, the patients were able to perceive the scales better, and the items in the scales increased, the patients were in trouble to understand.

Keywords: numeric pain scales, nurse, pain assessment, patient

Procedia PDF Downloads 290

Authors: Celine Davis

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The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

Procedia PDF Downloads 53

Authors: Boonrat Plangsorn

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Using ebooks can make not only a meaningful learning and achievement for students, but also can help teacher effectively enhance and improve their teaching. Nowadays, teachers try to develop ebooks for their class but it does not success in some cases because they do not have clear understanding on how to design, develop, and using ebooks that align with their teaching and learning objectives. Thus, the processes of using, designing, and producing ebooks have become one of important competency for teacher because it will enhance teacher’s knowledge for ebooks production. The purposes of this research were: (1) to develop the competency of producing and using ebooks of teachers in Chachengsao and (2) to promote the using ebooks of teachers in Chachengsao. The research procedures were divided into four phases. Phase I (study components and process of the designing and development of ebooks) was an interview in which the qualitative data were collected from five experts in instructional media. Phase II (develop teachers’ competency of producing ebooks) was a workshop for 28 teachers in Chachengsao. Phase III (study teachers’ using ebooks) was an interview in which the qualitative data were collected from seven teachers. Phase IV (study teachers’ using ebooks) was an interview in which the qualitative data were collected from six teachers. The research findings were as follows: 1. The components of ebooks comprised three components: ebooks structure, multimedia, and hyperlink. The eleven processes of design ebooks for education included (1) analyze the ebooks objective, (2) analyze learner characteristics, (3) set objective, (4) set learning content, (5) learner’s motivation, (6) design and construct activity, (7) design hyperlink, (8) produce script and storyboard, (9) confirm storyboard by expert, (10) develop ebooks, and (11) evaluate ebooks. 2. The evaluation of designing and development of ebooks for teacher workshop revealed the participants’ highest satisfaction (M = 4.65). 3. The teachers’ application of ebooks were found that obstacles of producing an ebooks: Time period of producing ebooks, a readiness of school resources, and small teacher network of producing and using ebooks. The result of using ebooks was students’ motivation. 4. The teachers’ ebooks utilization through educational research network of teacher in Chachengsao revealed that the characteristic of ebooks consist of picture, multimedia, voice, music, video, and hyperlink. The application of ebooks caused students interested in the contents; enjoy learning, and enthusiastic learning.

Keywords: ebooks, producing ebooks competency, using ebooks competency, educational research network

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Authors: Ben-Caleb Egbide, Egharevba Mathew, Achugamonu Uzoma, Faboyede Samuel

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The importance of budgeting in government and corporate entities as medium for the efficient management of scarce resources is self-evident. But when it comes to home or personal budgeting, there seem to be lingering misconceptions as regards its relevance. While most people view personal budgeting merely as a tool for tracking expenses and schedule for paying bills and indebtedness, very few consider it as one of the most important device for sound financial planning, money management instrument and/or wealth-creation mechanism. This paper is conceptualised to investigate the association between personal budgeting and financial well-being among staffers of tertiary institution in the South West Nigeria. Underpinned by the individualistic/cultural theory of well-being and the adoption of a survey research design, a structured questionnaire was used to gather data from a cross section of staff of tertiary Institutions in Ogun State. A Spearman Rank Correlation was utilised for analysis of data. The result indicates a high positive relationship between personal budgeting and tendencies for enhanced financial well-being among staff. The paper established that a change of value and behavioural pattern by individuals and household, especially in the areas of personal spending and budgeting could drastically reduce the incidence of the severity of financial stress, hence, enhanced wellness among staff.

Keywords: personal budgeting, financial well-being, tertiary institutions staffers, Nigeria

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Authors: Sheena K. J., Jyoti Badge, Sayed Mohammed Zeeshan

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A Comparative Study of Exponential and Logistic Population Growth Models in India India is the second most populous city in the world, just behind China, and is going to be in the first place by next year. The Indian population has remarkably at higher rate than the other countries from the past 20 years. There were many scientists and demographers who has formulated various models of population growth in order to study and predict the future population. Some of the models are Fibonacci population growth model, Exponential growth model, Logistic growth model, Lotka-Volterra model, etc. These models have been effective in the past to an extent in predicting the population. However, it is essential to have a detailed comparative study between the population models to come out with a more accurate one. Having said that, this research study helps to analyze and compare the two population models under consideration - exponential and logistic growth models, thereby identifying the most effective one. Using the census data of 2011, the approximate population for 2016 to 2031 are calculated for 20 Indian states using both the models, compared and recorded the data with the actual population. On comparing the results of both models, it is found that logistic population model is more accurate than the exponential model, and using this model, we can predict the future population in a more effective way. This will give an insight to the researchers about the effective models of population and how effective these population models are in predicting the future population.

Keywords: population growth, population models, exponential model, logistic model, fibonacci model, lotka-volterra model, future population prediction, demographers

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, SamutSongkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: (1) The identity of Amphur (District) Mueang, SamutSongkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. (2) The communication of the identity of AmphurMueang, SamutSongkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of AmphurMueang, SamutSongkram province 2) WatPhetSamutWorrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep AmphurMueang, SamutSongkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Saima Nasreen, Uzaira Rafique, Shery Ehrman, Muhammad Aqeel Ashraf

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The release of heavy metals into the environment is a potential threat to water and soil quality as well as to plant, animal and human health. In current research work, organically functionalized mesoporous silicates (MSU-H) were prepared by the co-condensation between sodium silicate and oregano alkoxysilanes in the presence of the nonionic surfactant triblock copolymer P104. The surfactant was used as a template for improving the porosity of the hybrid gels. Synthesized materials were characterized by TEM, FT-IR, SEM/EDX, TG, surface area analysis. The surface morphology and textural properties of such materials varied with various kinds of groups in the channels. In this study, removal of some heavy metals ions from aqueous solution by adsorption process was investigated. Batch adsorption studies show that the adsorption capacity of metal ions on the functionalized silicates is more than that on pure MSU-H. Data shows adsorption on synthesized materials is a time efficient process, suggesting adsorption on external surface as well as the mesoporous process. Adsorption models of Langmuir, Freundlich, and Temkin depicted equal goodness for all adsorbents, whereas pseudo 2nd order kinetics is in best agreement with experimental data.

Keywords: heavy metals, mesoporous silica, hybrid, adsorption, freundlich, langmuir, temkin

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Authors: Chuanju Cheng

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In Taiwan, the system of indigenous reserved land was established in 1928 during the Japanese rule. The purpose of setting up indigenous reserved land is to support the livelihood of tribal peoples who live in the mountainous area. Since 1945, the KMT government has kept the indigenous reserved land; in principle, only indigenous people can use indigenous reserved land. However, the government also makes some exceptions for non-indigenous peoples to use the land. Furthermore, since 1966, an indigenous individual can have ownership (fee simple) over the land he/she uses. Recent studies showed that there are many problems regarding the indigenous reserved lands, such as indigenous peoples have been losing ownership of their land (both legally and illegally), mismatched data of the true owner and the nominal owner, overutilization of the reserved land and so on. Using a Truku tribe in Hualien County as an example, this paper tries to find out how many people still own indigenous reserved land, do land owners constantly utilize their lands, and if so, whether or not (and by what extent) the indigenous reserved land support the livelihood of tribal peoples? After ten months of working data-collecting, we’ve successfully collected 327 questionnaires (70% of total households); preliminary research results show that less than 5% of indigenous reserved land in and around that specific Truku tribe is owned by tribal people. And most of the landowners do not utilize indigenous reserved land. It seems that the indigenous reserved land system does not meet its legislative goals and needs to be redesigned.

Keywords: indigenous people, truku nation, taiwan, indigenous reserved land, poverty, economic development

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Authors: Lauren Freed

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This research proposal outlines an examination of homeschool oversight in the Massachusetts educational system amid the backdrop of ideological differences between various parties with contributing interests. This mixed methodology study will follow an interpretive policy research approach, involving the use of existing data, surveys, and focus groups. The aim is to capture distinct sets of meanings, values, feelings, and beliefs by principal stakeholders, while exploring the ways in which they/each interact with, interpret, and implement homeschool guidelines set forth by the Massachusetts Supreme Judicial Court Decision Care and Protection of Charles (1987). This analysis will identify and contextualize the attitudes, administrative choices, financial implications, and educational impacts that result from the process and practice of enacting current homeschool oversight policy in Massachusetts. The following question will guide this study: How do districts, homeschooling parents, and Massachusetts Department of Elementary and Secondary Education (DESE) regulate, fund, collect, interpret, implement and report Massachusetts homeschool oversight policy? The resulting analysis will produce a unique and original baseline snapshot of qualitative and quantifiable point-in-time data based on the registered homeschool population in the state of Massachusetts.

Keywords: alternative education, homeschooling, home education, home schooling policy

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Authors: Selma Karabinar

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Lifelong learning can be described as a system where learning takes place for a person over the course of a lifespan and comprises formal, non-formal and informal learning to achieve the maximum possible improvement in personal, social, and vocational life. 21st century is marked with the digital technologies and people need to learn and adapt to new literacies as part of their lifelong learning. Our current knowledge gap brings to mind several questions: Do people with digital mindsets have different assumptions about affordances of digital technologies? How do digital mindsets lead language learners use digital technologies within and beyond classrooms? Does digital literacies have different significance for the learners? The presentation is based on a study attempted to answer these questions and show the relationship between lifelong learning and digital literacies. The study was conducted with learners of English language at a state university in Istanbul. The quantitative data in terms of participants' lifelong learning perception was collected through a lifelong learning scale from 150 students. Then 5 students with high and 5 with low lifelong learning perception were interviewed. They were questioned about their personal sense of agency in lifelong learning and how they use digital technologies in their language learning. Therefore, the qualitative data was analyzed in terms of their knowledge about digital literacies and actual use of it in their personal and educational life. The results of the study suggest why teaching new literacies are important for lifelong learning and also suggests implications for language teachers' education and language pedagogy.

Keywords: digital mindsets, language learning, lifelong learning, new literacies

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Authors: Henok Asfaw Hailu, P. D. Rwelamila

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Creating a suitable environment for successful projects needs a rethink of the organisational design of the parent organisations. A Project-based organisation (PBO) is a unique organizational form suitable for implementing and managing business activities around projects. A construction firm is inherently a PBO as it executes most of its activities through projects. PBO design and development require an empirical foundation. This study aimed to fill this gap by developing a conceptual model to help transform Ethiopian construction firms (ECFs) into full-fledged PBOs by assimilating the required PBO characteristics. The study used an exploratory QUAL-quant research design approach. A thematic content analysis was performed to analyse the qualitative (Interviews) research data. Means, standard deviations, frequencies, percentages, one-way ANOVA, and Pearson correlation were used to analyse the quantitative data. A transformational conceptual model was proposed and illustrated that transformation needs to begin by assessing the environment, strategic documents, and PBO characteristics. Assimilating missing PBO characteristics into ECFs is vital to realise organisations’ transformation into full-fledged PBOs.

Keywords: project-based organization, organizational design, dimensions, construction firms

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Authors: A. D. Susanti, W. B. Sediawan, S. K. Wirawan, Budhijanto, Ritmaleni

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Rice bran oil contains significant amounts of oryzanol, a natural antioxidant that considered has higher antioxidant activity than vitamin E (tocopherol). Oryzanol reviewed has several health properties and interested in pharmacy, nutrition, and cosmetics. For practical usage, isolation and purification would be necessary due to the low concentration of oryzanol in crude rice bran oil (0.9-2.9%). Batch chromatography has proved as a promising process for the oryzanol recovery, but productivity was still low and scale-up processes of industrial interest have not yet been described. In order to improve productivity of batch chromatography, a continuous chromatography design namely Simulated Moving Bed (SMB) concept have been proposed. The SMB concept has interested for continuous commercial scale separation of binary system (oryzanol and rice bran oil), and rice bran oil still obtained as side product. Design of SMB chromatography for oryzanol separation requires quantification of its equilibrium. In this study, equilibrium of oryzanol separation conducted in batch adsorption using silica as the adsorbent and n-hexane/acetone (9:1) as the eluent. Three isotherm models, namely the Henry, Langmuir, and Freundlich equations, have been applied and modified for the experimental data to establish appropriate correlation for each sample. It turned out that the model quantitatively describe the equilibrium experimental data and will directed for design of SMB chromatography.

Keywords: adsorption, equilibrium, oryzanol, rice bran oil, simulated moving bed

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

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Authors: Yobo Opare-Addo

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Ghana came under a military and democratic rule of the same leadership from 1981-2000. These were the Provisional National Defense Council (PNDC), a military government and a democratic government, the National Democratic Congress (NDC) both under the leadership of Flt. Lt. J.J. Rawlings. Meanwhile the year 1985 marked a turning point in the development of the tourism industry in Ghana. Interest in tourism among African governments and for that matter the ‘PNDC cum NDC Government’ (PNDC/NDC) arose because of adverse developments in intangible exports and a corresponding decline in commodity export earnings. The ‘PNDC/NDC Government’ undertook measures and policies to improve the tourism industry and at the same time embarked on export diversification to reap the foreign exchange that the industry could generate in Ghana. The objective of this paper is to examine the measures and policies of the PNDC/NDC to improve the tourism industry in order to reap the foreign exchange. It specifically interrogates the role of the government as an agent of tourism development, through its deliberate creation of a conducive environment for tourism to flourish, the involvement of the private sector both foreign and local and the provision of tourism facilities and infrastructure and how these factors impacted on the tourism industry in Ghana. In the final analysis it evaluates the degree of success of the PNDC/NDC Government in this arena of Ghana’s socio-cultural and economic development. Introduction The Provisional National Defense Council (PNDC), a military government under the leadership of Flt. Lt J.J. Rawlings overthrew a constitutionally elected government of People’s National Party in 1981. In 1992, the National Democratic Congress (NDC) won the general election conducted in December. Flt. Lt. J.J. Rawlings, the party’s leader became the President of the Fourth Republic from January 1993 to December 2000. It was refreshing to see Ghanaians embrace democracy with renewed energy, zeal, and enthusiasm. This paper takes a critical look at the efforts of the PNDC cum NDC Government (PNDC/NDC) to develop tourism in Ghana during the period from 1981-2000 Methodology: Qualitative method of research was adopted for the study. Data was collected from both primary and secondary sources, and analysis was done using descriptive analysis because descriptive analysis made it possible to describe or summarize the statistical data in the research. To gather data from primary sources, questionnaires, oral interviews, and semi-structured discussions were conducted. Respondents included public officials from Ghana Tourist Board, Ministry of Tourism, Hoteliers, restaurant operators and travel and tour operators in Accra. Secondary data sources included articles in journals, reports, magazines, bulletins, and books. The major findings included statistical data for tourism arrivals and receipts during the period and the status of the industry by the year 2000. Conclusion: The paper contributes to knowledge on political and historical aspects of tourism development in Ghana, which is almost non-existent, attitudes of the PNDC cum NDC government towards tourism development and the debates on the generation of foreign exchange to Ghana and third world countries.

Keywords: ghana, infrastructure, policies, privatization, tourism facilities

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Authors: Aysegul Sener, Gonca Tuncel Memis, Mirac Kamislioglu

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Chaos theory is one of the new paradigms of science since the last century. After determining chaos in the weather systems by Edward Lorenz the popularity of the theory was increased. Chaos is observed in many natural systems and studies continue to defect chaos to other natural systems. Acid rain is one of the environmental problems that have negative effects on environment and acid rains values are monitored continuously. In this study, we aim that analyze the chaotic behavior of acid rains in Turkey with the chaotic defecting approaches. The data of pH degree of rain waters, concentration of sulfate and nitrate data of wet rain water samples in the rain collecting stations which are located in different regions of Turkey are provided by Turkish State Meteorology Service. Lyapunov exponents, reconstruction of the phase space, power spectrums are used in this study to determine and predict the chaotic behaviors of acid rains. As a result of the analysis it is found that acid rain time series have positive Lyapunov exponents and wide power spectrums and chaotic behavior is observed in the acid rain time series.

Keywords: acid rains, chaos, chaotic analysis, Lypapunov exponents

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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Authors: Jiyoung Kim, Chae Weon Chung

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Labor pain is one of the most common concerns of pregnant women, thus women are in need of possible options they could take to control the pain. So, this study aimed to explore maternal perception of epidural anesthesia and to compare the childbirth outcomes according to the use of epidural anesthesia. For this descriptive study, women who were over 36 weeks of pregnancy were recruited from an out-patient obstetric clinic in a public hospital in Seoul. Women were included in the study if agreed to participate, were pregnant singleton, without pregnancy complication, and expecting a natural birth. Data collection was done twice, the first one at the prenatal care visit and the second one at an in-patient ward on 2nd day postpartum. The instrument of the beliefs about epidural anesthesia, one item of asking intention to use epidural anesthesia, demographics, and obstetrical characteristics were incorporated into a questionnaire. One nurse researcher performed data collection with the structured questionnaire after the approval of the institutional review board. At the initial data collection 133 women were included, while 117 were retained at the second point after excluded 13 women due to the occurrence of complications. Analyses were done by chi-square, t-test, and ANOVA using the SPSS program. Women were aged 32.5 years old, 22.2% were over 35 years old. The average gestational age was 38.5 weeks, and 67.5% were nulliparous. Out of 38 multiparous women, 20 women (52.6%) had received epidural anesthesia in the previous delivery. At the initial interview, 62.6% (n=73) of women wanted to receive epidural anesthesia while 22.4% answered not decided and 15.4% did not want to take the procedure. However, there were changes in proportions between women’s intention to take it and actual procedures done, particularly, two-thirds of women (n=26) who had been undecided were found to receive epidural anesthesia during labor. There was a significant difference in the perception of epidural anesthesia measured before delivery between women who received and not received it (t=3.68, p < .001). Delivery outcomes were statistically different between the two groups in delivery mode (chi-square=8.64, p=.01), O₂ supply during labor (chi-square =5.01, p=.03), duration of 2nd stage of labor (t=3.70, p < .001), and arterial cord blood pH (t=2.64, p=.01). Interestingly, there was no difference in labor pain perceived between women with and without epidural anesthesia. Considering the preference and use of epidural anesthesia, health professionals need to assess coping ability of women undergoing delivery and to provide accurate information about pain control to support their decision making and eventually to enhance delivery outcomes for mothers and neonates.

Keywords: epidural anesthesia, delivery outcomes, labor pain, perception

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Authors: Davoud Maleki, Neda Zamani

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The present study aims at exploring the effective accountability model of Islamic Azad University using a qualitative approach of grounded theory. The data of this study were obtained from semi-structured interviews with 25 professors and scholars in Islamic Azad University of Tehran who were selected by theoretical sampling method. In the data analysis, the stepwise method and Strauss and Corbin analytical methods (1992) were used. After identification of the main component (balanced response to stakeholders’ needs) and using it to bring the categories together, expressions and ideas representing the relationships between the main and subcomponents, and finally, the revealed components were categorized into six dimensions of the paradigm model, with the relationships among them, including causal conditions (7 components), main component (balanced response to stakeholders’ needs), strategies (5 components), environmental conditions (5 components), intervention features (4 components), and consequences (3 components). Research findings show an exploratory model for describing the relationships between causal conditions, main components, accountability strategies, environmental conditions, university environmental features, and that consequences.

Keywords: accountability, effectiveness, Islamic Azad University, grounded theory

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