Search results for: performance predicting formula
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13788

Search results for: performance predicting formula

11778 Effects of MBSR on Self-Esteem and Well-Being: The Key Role of Contingent Self-Esteem in Predicting Well-Being Compared to Explicit Self-Esteem

Authors: Sergio Luna, Raquel Rodríguez-Carvajal

Abstract:

This research examines the effectiveness of a mindfulness-based intervention in optimizing psychological well-being, with a particular focus on self-esteem, due to the rapid growth and consolidation of social network use and the increased frequency and intensity of upward comparisons of the self. The study aims to assess the potential of a mindfulness-based intervention to improve self-esteem and, in particular, to contribute to its greater stability by reducing levels of contingent self-esteem. Results show that an 8-week mindfulness-based stress reduction program was effective in increasing participants' (n=206) trait mindfulness, explicit self-esteem, and well-being, while decreasing contingent self-esteem. Furthermore, the study found that improvements in both explicit and contingent self-esteem were significantly correlated with increases in psychological well-being, but that contingent self-esteem had a stronger effect on well-being than explicit self-esteem. These findings highlight the importance of considering additional dimensions of self-esteem beyond levels, and suggest that mindfulness-based interventions may be a valuable tool for promoting a healthier form of self-esteem that contributes to personal well-being.

Keywords: MBSR, contingent self-esteem, explicit self-esteem, well-being

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11777 The Effect of Photovoltaic Integrated Shading Devices on the Energy Performance of Apartment Buildings in a Mediterranean Climate

Authors: Jenan Abu Qadourah

Abstract:

With the depletion of traditional fossil resources and the growing human population, it is now more important than ever to reduce our energy usage and harmful emissions. In the Mediterranean region, the intense solar radiation contributes to summertime overheating, which raises energy costs and building carbon footprints, alternatively making it suitable for the installation of solar energy systems. In urban settings, where multi-story structures predominate and roof space is limited, photovoltaic integrated shading devices (PVSD) are a clean solution for building designers. However, incorporating photovoltaic (PV) systems into a building's envelope is a complex procedure that, if not executed correctly, might result in the PV system failing. As a result, potential PVSD design solutions must be assessed based on their overall energy performance from the project's early design stage. Therefore, this paper aims to investigate and compare the possible impact of various PVSDs on the energy performance of new apartments in the Mediterranean region, with a focus on Amman, Jordan. To achieve the research aim, computer simulations were performed to assess and compare the energy performance of different PVSD configurations. Furthermore, an energy index was developed by taking into account all energy aspects, including the building's primary energy demand and the PVSD systems' net energy production. According to the findings, the PVSD system can meet 12% to 43% of the apartment building's electricity needs. By highlighting the potential interest in PVSD systems, this study aids the building designer in producing more energy-efficient buildings and encourages building owners to install PV systems on the façade of their buildings.

Keywords: photovoltaic integrated shading device, solar energy, architecture, energy performance, simulation, overall energy index, Jordan

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11776 Investigating Self-Confidence Influence on English as a Foreign Language Student English Language Proficiency Level

Authors: Ali A. Alshahrani

Abstract:

This study aims to identify Saudi English as a Foreign Language (EFL) students' perspectives towards using the English language in their studies. The study explores students' self-confident and its association with students' actual performance in English courses in their different academic programs. A multimodal methodology was used to fulfill the research purpose and answer the research questions. A 25-item survey questionnaire and final examination grades were used to collect data. Two hundred forty-one students agreed to participate in the study. They completed the questionnaire and agreed to release their final grades to be a part of the collected data. The data were coded and analyzed by SPSS software. The findings indicated a significant difference in students' performance in English courses between participants' academic programs on the one hand. Students' self-confidence in their English language skills, on the other hand, was not significantly different between participants' academic programs. Data analysis also revealed no correlational relationship between students' self-confidence level and their language skills and their performance. The study raises more questions about other vital factors such as course instructors' views of the materials, faculty members of the target department, family belief in the usefulness of the program, potential employers. These views and beliefs shape the student's preparation process and, therefore, should be explored further.

Keywords: English language intensive program, language proficiency, performance, self-confidence

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11775 Modern Spectrum Sensing Techniques for Cognitive Radio Networks: Practical Implementation and Performance Evaluation

Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

Abstract:

Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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11774 Impact of Emotional Intelligence and Cognitive Intelligence on Radio Presenter's Performance in All India Radio, Kolkata, India

Authors: Soumya Dutta

Abstract:

This research paper aims at investigating the impact of emotional intelligence and cognitive intelligence on radio presenter’s performance in the All India Radio, Kolkata (India’s public service broadcaster). The ancient concept of productivity is the ratio of what is produced to what is required to produce it. But, father of modern management Peter F. Drucker (1909-2005) defined productivity of knowledge work and knowledge workers in a new form. In the other hand, the concept of Emotional Intelligence (EI) originated back in 1920’s when Thorndike (1920) for the first time proposed the emotional intelligence into three dimensions, i.e., abstract intelligence, mechanical intelligence, and social intelligence. The contribution of Salovey and Mayer (1990) is substantive, as they proposed a model for emotional intelligence by defining EI as part of the social intelligence, which takes measures the ability of an individual to regulate his/her personal and other’s emotions and feeling. Cognitive intelligence illustrates the specialization of general intelligence in the domain of cognition in ways that possess experience and learning about cognitive processes such as memory. The outcomes of past research on emotional intelligence show that emotional intelligence has a positive effect on social- mental factors of human resource; positive effects of emotional intelligence on leaders and followers in terms of performance, results, work, satisfaction; emotional intelligence has a positive and significant relationship with the teachers' job performance. In this paper, we made a conceptual framework based on theories of emotional intelligence proposed by Salovey and Mayer (1989-1990) and a compensatory model of emotional intelligence, cognitive intelligence, and job performance proposed by Stephen Cote and Christopher T. H. Miners (2006). For investigating the impact of emotional intelligence and cognitive intelligence on radio presenter’s performance, sample size consists 59 radio presenters (considering gender, academic qualification, instructional mood, age group, etc.) from All India Radio, Kolkata station. Questionnaires prepared based on cognitive (henceforth called C based and represented by C1, C2,.., C5) as well as emotional intelligence (henceforth called E based and represented by E1, E2,., E20). These were sent to around 59 respondents (Presenters) for getting their responses. Performance score was collected from the report of program executive of All India Radio, Kolkata. The linear regression has been carried out using all the E-based and C-based variables as the predictor variables. The possible problem of autocorrelation has been tested by having the Durbinson-Watson (DW) Statistic. Values of this statistic, almost within the range of 1.80-2.20, indicate the absence of any significant problem of autocorrelation. The possible problem of multicollinearity has been tested by having the Variable Inflation Factor (VIF) value. Values of this statistic, around within 2, indicates the absence of any significant problem of multicollinearity. It is inferred that the performance scores can be statistically regressed linearly on the E-based and C-based scores, which can explain 74.50% of the variations in the performance.

Keywords: cognitive intelligence, emotional intelligence, performance, productivity

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11773 Digital Demands: Addressing the Digital Divide in Basic Education and Its Relation to Academic Performance and Aspirations

Authors: Jose Rodrigo Zubiri, Sofia Carmen Tomacruz

Abstract:

Amidst an increasingly digitalized society, information and communication technologies have been seamlessly integrated into the economic, social, and political life of individuals. Information has been regarded as a primary good, essential to the wellbeing and self-respect of individuals in society. The digital engagements of an individual play a key role in a variety of life outcomes ranging from academic performance to entrepreneurial success to health service uptake. As a result of varying degrees of access to the Internet and ICTs across populations and individuals, a digital divide emerges. Education, a sector pivotal to directing individual life trajectories, has been radically transformed with regards to the learning process and access to information and thus faces the implications of the digital divide, as new waves of inequalities are introduced in the classroom. As the period of basic education is critical to transitioning into civic life or higher education, digital inequalities are capable of aggravating pre-existing social inequalities. Through survey-questionnaires, conducted on 152 high school students from a Philippine public school, the study reveals the correlation of academic performance and aspirations (for their highest academic qualification) to access to digital technologies and the Internet, according to Van Dijk’s four measurements of digital poverty, namely: motivational access, material access, skills access, and usage access. The findings reveal a positive correlation for academic performance whereas no correlation was found between aspirations and digital access. In the study, significant correlational differences were also found between genders, specifically, in terms of skills access and academic performance.

Keywords: digital divide, ICTs, inequality, education, life trajectories

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11772 Diagnostic Yield of CT PA and Value of Pre Test Assessments in Predicting the Probability of Pulmonary Embolism

Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

Abstract:

Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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11771 Identification of Bayesian Network with Convolutional Neural Network

Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

Abstract:

In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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11770 Preparation and Performance of Polyphenylene Oxide-Based Anion Exchange Membrane for Vanadium Redox Flow Battery

Authors: Mi-Jung Park, Min-Hwa Lim, Ho-Young Jung

Abstract:

A polyphenylene oxide (PPO)-based anion exchange membrane based on the functionalization of bromomethylated PPO using 1-methylimdazole was fabricated for vanadium redox flow application. The imidazolium-bromomethylated PPO (Im-bPPO) showed lower permeability VO2+ ions (2.9×10⁻¹⁴ m²/sec), compared to Nafion 212 (2.3×10⁻¹² m²/sec) and FAP-450 (7.9×10⁻¹⁴ m²/sec). Even though the Im-bPPO membrane has higher permeability, the energy efficiency of the VRFB with the Im-bPPO membrane was slightly lower than that of Nafion and FAP-450. The Im-bPPO membrane exhibits good voltage efficiency compared to FAP-450 and Nafion 212 because of its better ion conductivity. The Im-bPPo membrane showed up good performance, but a decline in performance at later cycles was observed.

Keywords: anion exchange membranes, vanadium redox flow battery, polyphenylene oxide, energy efficiency (EE)

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11769 The Rayleigh Quotient for Structural Element Vibration Analysis with Finite Element Method

Authors: Falek Kamel

Abstract:

Various approaches are usually used in the dynamic analysis of beams vibrating transversally. For this, numerical methods allowing the solving of the general eigenvalue problem are utilized. The equilibrium equations describe the movement resulting from the solution of a fourth-order differential equation. Our investigation is based on the finite element method. The findings of these investigations are the vibration frequencies obtained by the Jacobi method. Two types of the elementary mass matrix are considered, representing a uniform distribution of the mass along with the element and concentrated ones located at fixed points whose number is increased progressively separated by equal distances at each evaluation stage. The studied beams have different boundary constraints representing several classical situations. Comparisons are made for beams where the distributed mass is replaced by n concentrated masses. As expected, the first calculus stage is to obtain the lowest number of beam parts that gives a frequency comparable to that issued from the Rayleigh formula. The obtained values are then compared to theoretical results based on the assumptions of the Bernoulli-Euler theory. These steps are used for the second type of mass representation in the same manner.

Keywords: structural elements, beams vibrating, dynamic analysis, finite element method, Jacobi method

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11768 Wait-Optimized Scheduler Algorithm for Efficient Process Scheduling in Computer Systems

Authors: Md Habibur Rahman, Jaeho Kim

Abstract:

Efficient process scheduling is a crucial factor in ensuring optimal system performance and resource utilization in computer systems. While various algorithms have been proposed over the years, there are still limitations to their effectiveness. This paper introduces a new Wait-Optimized Scheduler (WOS) algorithm that aims to minimize process waiting time by dividing them into two layers and considering both process time and waiting time. The WOS algorithm is non-preemptive and prioritizes processes with the shortest WOS. In the first layer, each process runs for a predetermined duration, and any unfinished process is subsequently moved to the second layer, resulting in a decrease in response time. Whenever the first layer is free or the number of processes in the second layer is twice that of the first layer, the algorithm sorts all the processes in the second layer based on their remaining time minus waiting time and sends one process to the first layer to run. This ensures that all processes eventually run, optimizing waiting time. To evaluate the performance of the WOS algorithm, we conducted experiments comparing its performance with traditional scheduling algorithms such as First-Come-First-Serve (FCFS) and Shortest-Job-First (SJF). The results showed that the WOS algorithm outperformed the traditional algorithms in reducing the waiting time of processes, particularly in scenarios with a large number of short tasks with long wait times. Our study highlights the effectiveness of the WOS algorithm in improving process scheduling efficiency in computer systems. By reducing process waiting time, the WOS algorithm can improve system performance and resource utilization. The findings of this study provide valuable insights for researchers and practitioners in developing and implementing efficient process scheduling algorithms.

Keywords: process scheduling, wait-optimized scheduler, response time, non-preemptive, waiting time, traditional scheduling algorithms, first-come-first-serve, shortest-job-first, system performance, resource utilization

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11767 The Impact of Digitalization and Sustainability on Professionals’ Performance in the Built Environment in Nigeria

Authors: Taiwo, Richard Oluseyi, Morakinyo, Kolawole O., Oyeniran, Demilade O.

Abstract:

This study examines the effects of digitalization and sustainability on professionals' performance within the built environment. By examining the interplay between these two transformative forces, the study seeks to unravel the complexities and opportunities presented by digital technologies in fostering sustainable practices across various professional disciplines. Through an extensive analysis of literature and expert interviews, this research explores how digitalization can enhance professionals' abilities to incorporate sustainability principles, optimize resource utilization, and promote resilient and inclusive built environments. Furthermore, it examines the challenges and barriers professionals face in adapting to and harnessing the potential of digital tools and processes. The findings will contribute to a greater comprehension of the beneficial interactions between digitalization and sustainable development and provide valuable insights for policymakers, practitioners, and educators in fostering an ecosystem that supports professionals' capacity building, collaboration, and innovation toward achieving sustainable goals in the built environment.

Keywords: digitisation, sustainability, professional performance, built environment

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11766 Machine Learning Approaches Based on Recency, Frequency, Monetary (RFM) and K-Means for Predicting Electrical Failures and Voltage Reliability in Smart Cities

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

Abstract:

As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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11765 Using Health Literacy and Medico-Legal Guidance to Improve Restorative Dentistry Patient Information Leaflets

Authors: Hasneet K. Kalsi, Julie K. Kilgariff

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Introduction: Within dentistry, the process for gaining informed consent has become more complex. To consent for treatment, patients must understand all reasonable treatment options and associated risks and benefits. Consenting is therefore deeply embedded in health literacy. Patients attending for dental consultation are often presented with an array of information and choices, yet studies show patients recall less than half of the information provided immediately after. Appropriate and comprehensible patient information leaflets (PILs) may be useful aid memories. In 2016 the World Health Organisation set improving health literacy as a global priority. Soon after, Scotland’s 2017-2025 Making it Easier: A Health Literacy Action Plan followed. This project involved the review of Restorative PILs used within Dundee Dental Hospital to assess the Content and Readability. Method: The current PIL on Root Canal Treatment (RCT) was created in 2011. This predates the Montgomery vs. NHS Lanarkshire case, a ruling which significantly impacted dental consenting processes, as well as General Dental Council’s (GDC’s) Standards for the Dental Team and Faculty of General Dental Practice’s Good Practice Guidance on Clinical Examination and Record-Keeping. Current evidence-based guidance, including that stipulated by the GDC, was reviewed. A 20-point Essential Content Checklist was designed to conform to best practice guidance for valid consenting processes. The RCT leaflet was scored against this to ascertain if the content was satisfactory. Having ensured the content satisfied medicolegal requirements, health literacy considerations were reviewed regarding readability. This was assessed using McLaughlin’s Simple Measure of Gobbledygook (SMOG) formula, which identifies school stages that would have to be achieved to comprehend the PIL. The sensitivity of the results to alternative readability methods were assessed. Results: The PIL was not sufficient for modern consenting processes and reflected a suboptimal level of health literacy. Evaluation of the leaflet revealed key content was missing, including information pertaining to risks and benefits. Only five points out of the 20-point checklist were present. The readability score was 16, equivalent to a level 2 in National Adult Literacy Standards/Scottish Credit and Qualification Framework Level 5; 62% of Scottish adults are able to read to this standard. Discussion: Assessment of the leaflet showed it was no longer fit for purpose. Reasons include a lack of pertinent information, a text-heavy leaflet lacking flow, and content errors. The SMOG score indicates a high level of comprehension is required to understand this PIL, which many patients may not possess. A new PIL, compliant with medicolegal and health literacy guidance, was designed with patient-driven checklists, notes spaces for annotations/ questions and areas for clinicians to highlight important case-specific information. It has been tested using the SMOG formula. Conclusion: PILs can be extremely useful. Studies show that interactive use can enhance their effectiveness. PILs should reflect best practice guidance and be understood by patients. The 2020 leaflet designed and implemented aims to fulfill the needs of a modern healthcare system and its service users. It embraces and embeds Scotland’s Health Literacy Action Plan within the consenting process. A review of further leaflets using this model is ongoing.

Keywords: consent, health literacy, patient information leaflet, restorative dentistry

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11764 Techno-Economic Study on the Potential of Dimethyl Ether (DME) as a Substitute for LPG

Authors: Widya Anggraini Pamungkas, Rosana Budi Setyawati, Awaludin Fitroh Rifai, Candra Pangesti Setiawan, Anatta Wahyu Budiiman, Inayati, Joko Waluyo, Sunu Herwi Pranolo

Abstract:

The increase in LPG consumption in Indonesia is not balanced with the amount of supply. The high demand for LPG due to the success of the government's kerosene-to-LPG conversion program and the Covid-19 pandemic in 2020 led to an increase in LPG consumption in the household sector and caused Indonesia's trade balance to experience a deficit. The high consumption of LPG encourages the need for alternative fuels as a substitute or which aims to substitute LPG; one of the materials that can be used is Dimethyl Ether (DME). Dimethyl ether (DME) is an organic compound with the chemical formula CH 3. OCH 3 has a high cetane number and has characteristics similar to LPG. DME can be produced from various sources, such as coal, biomass and natural gas. Based on the economic analysis conducted at 10% IRR, coal has the largest NPV of Rp. 20,034,837,497,241 with a payback period of 3.86 years, then biomass with an NPV of Rp. 10,401,526,072,850 and a payback period of 5.16. the latter is natural gas with an NPV of IDR 7,401,272,559,191 and a payback period of 6.17 years. Of the three sources of raw materials used, if the sensitivity is calculated using the selling price of DME equal to the selling price of LPG, it will get an NPV value that is greater than the NPV value when using the current DME price. The advantages of coal as a raw material for DME are not only because it is profitable, namely: low price and abundant resources, but has high greenhouse gas emissions.

Keywords: LPG, DME, coal, biomass, natural gas

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11763 Determination of Effect Factor for Effective Parameter on Saccharification of Lignocellulosic Material by Concentrated Acid

Authors: Sina Aghili, Ali Arasteh Nodeh

Abstract:

Tamarisk usage as a new group of lignocelluloses material to produce fermentable sugars in bio-ethanol process was studied. The overall aim of this work was to establish the optimum condition for acid hydrolysis of this new material and a mathematical model predicting glucose release as a function of operation variable. Sulfuric acid concentration in the range of 20 to 60%(w/w), process temperature between 60 to 95oC, hydrolysis time from 120 to 240 min and solid content 5,10,15%(w/w) were used as hydrolysis conditions. HPLC was used to analysis of the product. This analysis indicated that glucose was the main fermentable sugar and was increased with time, temperature and solid content and acid concentration was a parabola influence in glucose production.The process was modeled by a quadratic equation. Curve study and model were found that 42% acid concentration, 15 % solid content and 90oC were in optimum condition.

Keywords: fermentable sugar, saccharification, wood, hydrolysis

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11762 Non-Performing Assets and Credit Risk Performance: An Evidence of Commercial Banks in India

Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

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This research analyzes the effect of credit risk management practices of commercial banks in India and the relationship with their non-performing assets (NPAs). Required data on credit risk performance was collected through a survey questionnaire from top risk officers of 38 Indian banks. NPA data (period from 2012 to 2016) was collected from Prowess database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was assessed utilizing cross sectional regression method. As expected, the results indicate a negative significant relationship between credit risk management in India banks and their NPA growth. The research has implications for banks given the high level of losses in India and other economies as well, and the implementation of Basel III standards by the central banks. This research would be an evidence on credit risk performance and its relationship with the level of non-performing assets (NPAs) in Indian banks.

Keywords: risk management, risk identification, banks, Non-Performing Assets (NPAs)

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11761 A 2D Numerical Model of Viscous Flow-Cylinder Interaction

Authors: Bang-Fuh Chen, Chih-Chun Chu

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The flow induced cylinder vibration or earthquake-induced cylinder motion are moving in an arbitrary direction with time. The phenomenon of flow across cylinder is highly nonlinear and a linear-superposition of flow pattern across separated oscillating direction of cylinder motion is not valid to obtain the flow pattern across a cylinder oscillating in multiple directions. A novel finite difference scheme is developed to simulate the viscous flow across an arbitrary moving circular cylinder and we call this a complete 2D (two-dimensional) flow-cylinder interaction. That is, the cylinder is simultaneously oscillating in x- and y- directions. The time-dependent domain and meshes associated with the moving cylinder are mapped to a fixed computational domain and meshes, which are time independent. The numerical results are validated by several bench mark studies. Several examples are introduced including flow across steam-wise, transverse oscillating cylinder and flow across rotating cylinder and flow across arbitrary moving cylinder. The Morison’s formula can not describe the complex interaction phenomenon between cross flow and oscillating circular cylinder. And the completed 2D computational fluid dynamic analysis should be made to obtain the correct hydrodynamic force acting on the cylinder.

Keywords: 2D cylinder, finite-difference method, flow-cylinder interaction, flow induced vibration

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11760 Study Of Cu Doped Zns Thin Films Nanocrystalline by Chemical Bath Deposition Method

Authors: H. Merzouka, D. T. Talantikitea, S. Fettouchib, L. Nessarkb

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Recently New nanosized materials studies are in huge expansion worldwide. They play a fundamental role in various industrial applications thanks their unique and functional properties. Moreover, in recent years, a great effort has been made in design and control fabrication of nano-structured semiconductors such as zinc sulphide. In recent years, much attention has been accorded in doped and co-doped ZnS to improve the ZnS films quality. We present in this work preparation and characterization of ZnS and Cu doped ZnS thin films. Nanoparticles ZnS and Cu doped ZnS films are prepared by chemical bath deposition method (CBD), for various dopant concentrations. Thin films are deposed onto commercial microscope glass slides substrates. Thiourea is used as sulfide ion source, zinc acetate as zinc ion source and copper acetate as Cu ion source in alkaline bath at 90 °C. X-ray diffraction (XRD) analyses are carried out at room temperature on films and powders with a powder diffractometer, using CuK radiation. The average grain size obtained from the Debye–Scherrer’s formula is around 10 nm. Films morphology is examined by scanning electron microscopy. IR spectra of representative sample are recorded with the FTIR between 400 and 4000 cm-1. The transmittance is more than 70 % is performed with the UV–VIS spectrometer in the wavelength range 200–800 nm. This value is enhanced by Cu doping.

Keywords: Cu doped ZnS, nanostructured, thin films, CBD, XRD, FTIR

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11759 Evaluating Cement Brands in Southwestern Nigeria for Local Construction Industries

Authors: Olonade, K. A., Jaji, M. B., Rasak, S. A., Ojo, B. A., Adefuye, O. E.

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Different brands of cement are used in Nigeria by local contractors for various works without prior knowledge of their performance. Qualities of common cement brands in Southwestern Nigeria were investigated. Elephant, Dangote, Gateway, Purechem, Burham and Five Star cements were selected for the study. Fineness, setting times, chemical composition, compressive and flexural strengths of each of the cement brands were determined. The results showed that all the cement brands contained major oxides in amount within the acceptable values except that the sulphite content of Gateway fell outside the range. Strength comparison indicated that Burham had highest flexural and compressive strength, followed by Elephant and then Dangote while Gateway had the lowest strength at 28 days. It was observed that Dangote cement set earlier than other cement brands. The study has shown that there were differences in performance of the selected cement brands and concluded that the choice of cement brand should be based on the expected performance.

Keywords: cement brand, compressive strength, flexural strength, local construction industries

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11758 Predicting the Frequencies of Tropical Cyclone-Induced Rainfall Events in the US Using a Machine-Learning Model

Authors: Elham Sharifineyestani, Mohammad Farshchin

Abstract:

Tropical cyclones are one of the most expensive and deadliest natural disasters. They cause heavy rainfall and serious flash flooding that result in billions of dollars of damage and considerable mortality each year in the United States. Prediction of the frequency of tropical cyclone-induced rainfall events can be helpful in emergency planning and flood risk management. In this study, we have developed a machine-learning model to predict the exceedance frequencies of tropical cyclone-induced rainfall events in the United States. Model results show a satisfactory agreement with available observations. To examine the effectiveness of our approach, we also have compared the result of our predictions with the exceedance frequencies predicted using a physics-based rainfall model by Feldmann.

Keywords: flash flooding, tropical cyclones, frequencies, machine learning, risk management

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11757 Cognitive Performance and Everyday Functionality in Healthy Greek Seniors

Authors: George Pavlidis, Ana Vivas

Abstract:

The demographic change into an aging population has stimulated the examination of seniors’ mental health and ability to live independently. The corresponding literature depicts the relation between cognitive decline and everyday functionality with aging, focusing largely in individuals that are reaching or have bridged the threshold of various forms of neuropathology and disability. In this context, recent meta-analysis depicts a moderate relation between cognitive performance and everyday functionality in AD sufferers. However, there has not been an analogous effort for the examination of this relation in the healthy spectrum of aging (i.e, in samples that are not challenged from a neurodegenerative disease). There is a consensus that the assessment tools designed to detect neuropathology with those that assess cognitive performance in healthy adults are distinct, thus their universal use in cognitively challenged and in healthy adults is not always valid. The same accounts for the assessment of everyday functionality. In addition, it is argued that everyday functionality should be examined with cultural adjusted assessment tools, since many vital everyday tasks are heterotypical among distinct cultures. Therefore, this study was set out to examine the relation between cognitive performance and everyday functionality a) in the healthy spectrum of aging and b) by adjusting the everyday functionality tools EPT and OTDL-R in the Greek cultural context. In Greece, 107 cognitively healthy seniors ( Mage = 62.24) completed a battery of neuropsychological tests and everyday functionality tests. Both were carefully chosen to be sensitive in fluctuations of performance in the healthy spectrum of cognitive performance and everyday functionality. The everyday functionality assessment tools were modified to reflect the local cultural context (i.e., EPT-G and OTDL-G). The results depicted that performance in all everyday functionality measures decline with age (.197 < r > .509). Statistically significant correlations emerged between cognitive performance and everyday functionality assessments that range from r =0.202 to r=0.510. A series of independent regression analysis including the scores of cognitive assessments has yield statistical significant models that explained 20.9 < AR2 > 32.4 of the variance in everyday functionality scored indexes. All everyday functionality measures were independently predicted by the TMT B-A index, and indicator of executive function. Stepwise regression analyses depicted that TMT B-A and age were statistically significant independent predictors of EPT-G and OTDL-G. It was concluded that everyday functionality is declining with age and that cognitive performance and everyday functional may be related in the healthy spectrum of aging. Age seems not to be the sole contributing factor in everyday functionality decline, rather executive control as well. Moreover, it was concluded that the EPT-G and OTDL-G are valuable tools to assess everyday functionality in Greek seniors that are not cognitively challenged, especially for research purposes. Future research should examine the contributing factors of a better cognitive vitality especially in executive control, as vital for the maintenance of independent living capacity with aging.

Keywords: cognition, everyday functionality, aging, cognitive decline, healthy aging, Greece

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11756 Time Series Forecasting (TSF) Using Various Deep Learning Models

Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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11755 A Detailed Study of Two Different Airfoils on Flight Performance of MAV of Same Physical Dimension

Authors: Shoeb A. Adeel, Shashant Anand, Vivek Paul, Dinesh, Suraj, Roshan

Abstract:

The paper presents a study of micro air vehicles (MAVs) with wingspans of 20 Cm with two different airfoil configurations. MAVs have vast potential applications in both military and civilian areas. These MAVs are fully autonomous and supply real-time data. The paper focuses on two different designs of the MAVs one being N22 airfoil and the other a flat plate with similar dimension. As designed, the MAV would fly in a low Reynolds-number regime at airspeeds of 15 & 20 m/sec. Propulsion would be provided by an electric motor with an advanced lithium. Because of the close coupling between vehicle elements, system integration would be a significant challenge, requiring tight packaging and multifunction components to meet mass limitations and Centre of Gravity (C.G) balancing. These MAVs are feasible and within a couple of years of technology development in key areas including sensors, propulsion, Aerodynamics, and packaging these would be easily available to the users at affordable prices. The paper finally compares the flight performance of the two configurations.

Keywords: airfoil, CFD, MAV, flight performance, endurance, climb, lift, drag

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11754 On an Approach for Rule Generation in Association Rule Mining

Authors: B. Chandra

Abstract:

In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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11753 Driving Performance Improvement in Mini Markets: The Impact of Talent Management, Business Skills, and Technology Adoption in Johannesburg and Cape Town, South Africa

Authors: Fedil Jemal Ahmed

Abstract:

This conference abstract paper presents a study that aimed to explore the impact of talent management and business skills on performance improvement in mini markets located in Johannesburg and Cape Town, South Africa. Mini markets are small retail stores that play a crucial role in providing essential goods and services to communities. However, due to their small size, they often face significant challenges in terms of resources and management. The study conducted interviews with mini market owners and managers in Johannesburg and Cape Town to understand their approach to talent management, business skills, and their impact on business performance. The results showed that effective talent management practices, including recruitment, training, and retention, along with strong business skills, had a significant positive impact on business performance in mini markets. Furthermore, the study found that the use of technology, such as point of sale systems and inventory management software, can also contribute to business performance improvement in mini markets. The results suggest that mini market owners and managers should prioritize talent management, business skills, and invest in technology to improve their business performance. Comparing the improvements made by mini markets in Johannesburg and Cape Town to those made by others, the study found that the adoption of effective talent management practices and strong business skills were key factors in driving performance improvement. Mini market owners and managers who invested in these areas were better equipped to manage their resources, enhance their customer service, and increase their profitability. When comparing the personal experiences of the fedil jemal who improved their business performance from a small market to a large one, they found that effective talent management practices and strong business skills were crucial in achieving success. Through the adoption of effective talent management practices, the fedil was able to attract and retain top talent, ensuring that the business was managed effectively. Furthermore, the fedil invested in improving their business skills, such as financial management, marketing, and customer service, which helped to increase their revenue and profitability. In terms of technology adoption, the author found that the use of point-of-sale systems and inventory management software were essential in managing their inventory and improving their customer service. By investing in technology, the fedil was able to streamline their operations and enhance their overall business performance. In conclusion, this study provides valuable insights into the importance of talent management, business skills, and technology adoption in improving business performance in mini markets. It highlights the need for mini market owners and managers to prioritize these areas and invest in them to enhance their business performance. The findings of this study have practical implications for mini market owners and managers who are looking to improve their business performance and compete in a highly competitive market. By adopting effective talent management practices, developing strong business skills, and investing in technology, mini market owners and managers can improve their operations and increase their profitability.

Keywords: talent management, business skills, technology adoption, mini markets

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11752 Seismic Performance of Isolated Bridge Configurations with Soil Structure Interaction

Authors: Davide Forcellini

Abstract:

The most recent development of earthquake engineering is based on concept of design consisting in prescribed performance rather than the more traditional prescriptive approaches. The paper aims to assess the effects of isolation devices and soil structure interaction on a benchmark bridge adopting a Performance-Based Earthquake Engineering methodology. Several isolated configurations of abutments and pier connections are compared performing the most representative isolation devices. Isolation systems suitability depends on many factors, mainly connected with ground effects. In this regard, the second purpose of this paper is to assess the effects of soil-structure interaction (SSI) on the studied bridge configurations. Contributions of isolation technique and soil structure interaction are assessed evaluating the resistance effects applied to Peak Ground Acceleration (PGA) levels in terms of cost and time repair quantities.

Keywords: base isolation, bridge, earthquake engineering, non linearity, PBEE methodology, seismic assessment, soil structure interaction

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11751 Compromising Relevance for Elegance: A Danger of Dominant Growth Models for Backward Economies

Authors: Givi Kupatadze

Abstract:

Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.

Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities

Procedia PDF Downloads 358
11750 Are Oral Health Conditions Associated with Children’s School Performance and School Attendance in the Kingdom of Bahrain - A Life Course Approach

Authors: Seham A. S. Mohamed, Sarah R. Baker, Christopher Deery, Mario V. Vettore

Abstract:

Background: The link between oral health conditions and school performance and attendance remain unclear among Middle Eastern children. The association has been studied extensively in the Western region; however, several concerns have been raised regarding the reliability and validity of measures, low quality of studies, inadequate inclusion of potential confounders, and the lack of a conceptual framework. These limitations have meant that, to date, there has been no detailed understanding of the association or of the key social, clinical, behavioural and parental factors which may impact the association. Aim: To examine the association between oral health conditions and children’s school performance and attendance at Grade 2 in Muharraq city in the Kingdom of Bahrain using Heilmann et al.’s (2015) life course framework for oral health. Objectives: To (1) describe the prevalence of oral health conditions among 7-8 years old schoolchildren in the city of Muharraq; (2) analyse the social, biological, behavioural, and parental pathways that link early and current life exposures with children’s current oral health status; (3) examine the association between oral health conditions and school performance and attendance among schoolchildren; (4) explore the early and current life course social, biological, behavioural and parental factors associated with children’s school outcomes. Design: A time-ordered-cross-sectional study was conducted with 466 schoolchildren aged 7-8 years and their parents from Muharraq city in KoB. Data were collected through parents’ self-administered questionnaires, children’s face-face interviews, and dental clinical examinations. Outcome variables, including school performance and school attendance data, were obtained from the parents and school records. The data were analysed using structural equation modelling (SEM). Results: Dental caries, the consequence of dental caries (PUFA/pufa), and enamel developmental defects (EDD) prevalence were 93.4%, 25.7%, and 17.2%, respectively. The findings from the SEM showed that children born in families with high SES were less likely to suffer from dentine dental caries (β= -0.248) and more likely to earn high school performance (β= 0.136) at 7-8 years of age in Muharraq. From the current life course of children, the dental plaque was associated significantly and directly with enamel caries (β= 0.094), dentine caries (β= 0.364), treated teeth (filled or extracted because of dental caries) (β= 0.121), and indirectly associated with dental pain (β= 0.057). Further, dentine dental caries was associated significantly and directly with low school performance (β= -0.155). At the same time, the dental plaque was indirectly associated with low school performance via dental caries (β = −0.044). Conversely, treated teeth were associated directly with high school performance (β= 0.100). Notably, none of the OHCs, biological, SES, behavioural, or parental conditions was related to school attendance in children. Conclusion: The life course approach was adequate to examine the role of OHCs on children’s school performance and attendance. Birth and current (7-8-year-olds) social factors were significant predictors of poor OH and poor school performance.

Keywords: dental caries, life course, Bahrain, school outcomes

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11749 Computational Fluid Dynamics Study on Water Soot Blower Direction in Tangentially Fired Pulverized-Coal Boiler

Authors: Teewin Plangsrinont, Wasawat Nakkiew

Abstract:

In this study, computational fluid dynamics (CFD) was utilized to simulate and predict the path of water from water soot blower through an ambient flow field in 300-megawatt tangentially burned pulverized coal boiler that utilizes a water soot blower as a cleaning device. To predict the position of the impact of water on the opposite side of the water soot blower under identical conditions, the nozzle size and water flow rate were fixed in this investigation. The simulation findings demonstrated a high degree of accuracy in predicting the direction of water flow to the boiler's water wall tube, which was validated by comparison to experimental data. Results show maximum deviation value of the water jet trajectory is 10.2 percent.

Keywords: computational fluid dynamics, tangentially fired boiler, thermal power plant, water soot blower

Procedia PDF Downloads 193