Search results for: quality assurance evaluation models
Commenced in January 2007
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Edition: International
Paper Count: 20600

Search results for: quality assurance evaluation models

19310 Determinants of Quality of Life and Mental Health in Medical Students During Two Years Observation

Authors: Szymon Szemik, Małgorzata Kowalska

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Objective: Medical students experience numerous demands during the education process, determining their quality of life (QoL) and health status. POLLEK (POLski LEKarz, eng. Polish Physician) study aims to identify and evaluate the quality of life, mental health status, and ever-recognized chronic diseases by simultaneously assessing their determinants in Polish medical students during long-term observation. Material and Methods: The POLLEK is the follow-up cohort study conducted among medical students at the Medical University of Silesia in Katowice. Students were followed during two observation periods: in their first year of studies, the academic year 2021/2022 (T1), and in their second year, the academic year 2022/2023 (T2). Results: The total number of participants in the first year of observation (T1) was 427 while in the second year (T2) was 335. Obtained results confirmed that the QoL score significantly decreased in their second year of studies mainly in the somatic and psychological domains. Moreover, we observed a significant increase in self-declared scoring of somatic symptoms year by year (from M=4.75 at T1 to M=8.06 at T2, p<0.001) in the GHQ-28 questionnaire survey. The determinants of QoL domains common to T1 and T2 remained self-declared health status, frequency of physical activity, and current financial situation. In the first year of evaluation, 56 students (13.10%) were overweight or obese, and 52 (15.8%) in the second. Regardless of the academic year, the increased risk of being overweight or obese was significantly associated with dissatisfaction with personal health, financial deficiencies, and a diet abundant in meat consumption. Conclusions: The QoL in medical students and selected determinants of their health status deteriorated during the observation period. Our findings suggest that medical schools should actively promote the activity needed to achieve a balance between schoolwork and the personal life of medical students from the beginning of university study.

Keywords: quality of life, mental health, medical students, follow-up study

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19309 Two-Stage Hospital Efficiency Analysis Including Qualitative Evidence: A Greek Case

Authors: Panos Xenos, Milton Nektarios, John Yfantopoulos

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Background: Policy makers, professional organizations and payers have introduced a variety of initiatives and reforms for the health systems worldwide, aimed at improving hospital efficiency. Their efforts are concentrated in two main categories: to constrain increasing healthcare costs and to enhance quality of services provided. Research Objectives: This study examines the efficiency of 112 Greek public hospitals for the year 2009, evaluates the importance of bootstrapping techniques and investigates the effect of contextual factors on hospital efficiency. Furthermore, the effect of qualitative evidence, on hospital efficiency is explored using data from 28 large hospitals. Methods: We applied Data Envelopment Analysis, augmented by bootstrapping techniques, to estimate efficiency scores. In order to measure the effect of environmental factors on hospital efficiency we used Tobit regression analysis. The significance of our models is evaluated using statistical tests to compare distributions. Results: The Kolmogorov-Smirnov test between the original and the bootstrap-corrected efficiency indicates that their distributions are significantly different (p-value<0.01). The environmental factors, that seem to influence efficiency, are Occupancy Rating and the ratio between Outpatient Visits and Inpatient Days. Results indicate that the inclusion of the quality variable in DEA modelling generates statistically significant variations in efficiency scores (p-value<0.05). Conclusions: The inclusion of quality variables and the use of bootstrap resampling in efficiency analysis impose a statistically significant effect on the distribution of efficiency scores. As a policy conclusion we highlight the importance of these methods on hospital efficiency analysis and, by implication, on healthcare resource allocation.

Keywords: hospitals, efficiency, quality, data envelopment analysis, Greek public hospital sector

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19308 An Empirical Assessment of Indoor Environmental Quality in Developing Sub-Saharan Countries: Evaluation of Existing Gaps and Potential Risk

Authors: Jean-Paul Kapuya Bulaba Nyembwe, John Omomoluwa Ogundiran, Manuel Carlos Gameiro da Silva

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Indoor environmental quality (IEQ) remains a global concern because it impacts people's comfort, health, performance, and general well-being. People spend a significant amount of time in buildings or while commuting, hence ensuring the minimal risk in indoor spaces by ensuring suitable IEQ. IEQ studies are limited regarding developing sub-Saharan countries, whereas there is also a huge risk and concern for the current population and geometric growth as many cities in the region will become mega-cities by 2040 (World Bank report). The absence of suitable IEQ regulations and energy poverty are reasons to assess the IEQ gaps for increased awareness of sustainable interventions to minimize the associated risk. This study evaluates the gaps and potential hazards that exist in the IEQ of sub-Saharan countries using empirical studies of hospital occupants and BRT bus passengers and drivers. The Surveys were conducted in 3 cities of the Democratic Republic of Congo and Lagos metropolis of Nigeria. The results suggest that gaps exist in IEQ for these regions. The gaps indicate existential risk to people’s health, comfort, and well-being. The inferential conclusions are that there is a need for further scientific studies, improvement in IEQ conditions, and ensuring suitable regulations for developing sub-Saharan countries.

Keywords: health hazards, hospitals indoor environmental quality, indoor spaces, occupants, sub-Saharan countries, vehicles

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19307 Assessment of the Electrical, Mechanical, and Thermal Nociceptive Thresholds for Stimulation and Pain Measurements at the Bovine Hind Limb

Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

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Background: Three nociceptive thresholds of thermal, electrical, and mechanical thresholds commonly use to evaluate the local anesthesia in many species, for instance, cow, horse, cat, dog, rabbit, and so on. Due to the lack of investigations to evaluate and/or validate such those nociceptive thresholds, our plan was the comparison of two-foot local anesthesia methods of Intravenous Regional Anesthesia (IVRA) and our modified four-point Nerve Block Anesthesia (NBA). Materials and Methods: Eight healthy nonpregnant nondairy Holstein Frisian cows in a cross-over study design were selected for this study. All cows divided into two different groups to receive two local anesthesia techniques of IVRA and our modified four-point NBA. Three thermal, electrical, and mechanical force and pinpricks were applied to evaluate the quality of local anesthesia methods before and after local anesthesia application. Results: The statistical evaluation demonstrated that our four-point NBA has a qualification to select as a standard foot local anesthesia. However, the recorded results of our study revealed no significant difference between two groups of local anesthesia techniques of IVRA and modified four-point NBA related to quality and duration of anesthesia stimulated by electrical, mechanical and thermal nociceptive stimuli. Conclusion and discussion: All three nociceptive threshold stimuli of electrical, mechanical and heat nociceptive thresholds can be applied to measure and evaluate the efficacy of foot local anesthesia of dairy cows. However, our study revealed no superiority of those three nociceptive methods to evaluate the duration and quality of bovine foot local anesthesia methods. Veterinarians to investigate the duration and quality of their selected anesthesia method can use any of those heat, mechanical, and electrical methods.

Keywords: mechanical, thermal, electrical threshold, IVRA, NBA, hind limb, dairy cow

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19306 Plant Identification Using Convolution Neural Network and Vision Transformer-Based Models

Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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19305 Evaluation of Patients’ Quality of Life After Lumbar Disc Surgery and Movement Limitations

Authors: Shirin Jalili, Ramin Ghasemi

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Lumbar microdiscectomy is the most commonly performed spinal surgery strategy; it is regularly performed to lighten the indications and signs of sciatica within the lower back and leg caused by a lumbar disc herniation. This surgery aims to progress leg pain, reestablish function, and enable a return to ordinary day-by-day exercises. Rates of lumbar disc surgery show critical geographic varieties recommending changing treatment criteria among working specialists. Few population-based considers have investigated the hazard of reoperation after disc surgery, and regional or inter specialty varieties within the reoperations are obscure. The conventional approach to recouping from lumbar microdiscectomy has been to restrain bending, lifting, or turning for a least 6 weeks in arrange to anticipate the disc from herniating once more. Traditionally, patients were exhorted to limit post-operative action, which was accepted to decrease the hazard of disc herniation and progressive insecurity. In modern hone, numerous specialists don't limit understanding of postoperative action due to the discernment this practice is pointless. There's a need of thinks about highlighting the result by distinctive scores or parameters after surgery for repetitive circle herniations of the lumbar spine at the starting herniation location. This study will evaluate the quality of life after surgical treatment of recurrent herniations with distinctive standardized approved result instruments.

Keywords: post-operative activity, disc, quality of life, treatment, movements

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19304 Deteriorating Ambient Air Quality Resulted from Invasion of Foreign Air Pollutants

Authors: Kuo-C. Lo, Chung-H. Hung

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Invasion of foreign air pollutants to deteriorate local air quality has become an emerging international issue of concern. This study aimed to apply meteorological and air quality model, WRF-Chem (V3.1), for simulating and analyzing the phenomenon of forming of high-concentrated particulate matters, PM10 and PM2.5, in ambient air of Taiwan during January 17th to 19th, 2014. The foreign air pollutants were mainly from long-distance transport of air pollutants of China being transported with a strong continental cold high. It was observed that PM10 and PM2.5 peaked as high as 182~588 μg/m3 and 95~165 μg/m3, respectively, in the ambient air of west side of Taiwan. They were about 2~3 folds higher than the usual concentrations of particulate matters in these seasons.

Keywords: WRF-Chem, air pollution, PM2.5, ambient air quality

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19303 The Impact and Performances of Controlled Ventilation Strategy on Thermal Comfort and Indoor Atmosphere in Building

Authors: Selma Bouasria, Mahi Abdelkader, Abbès Azzi, Herouz Keltoum

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Ventilation in buildings is a key element to provide high indoor air quality. Its efficiency appears as one of the most important factors in maintaining thermal comfort for occupants of buildings. Personal displacement ventilation is a new ventilation concept that combines the positive features of displacement ventilation with those of task conditioning or personalized ventilation. This work aims to study numerically the supply air flow in a room to optimize a comfortable microclimate for an occupant. The room is heated, and a dummy is designed to simulate the occupant. Two types of configurations were studied. The first consist of a room without windows; and the second one is a local equipped with a window. The influence of the blowing speed and the solar radiation coming from the window on the thermal comfort of the occupant is studied. To conduct this study we used the turbulence models, namely the high Reynolds k-e, the RNG and the SST models. The numerical tool used is based on the finite volume method. The numerical simulation of the supply air flow in a room can predict and provide a significant information about indoor comfort.

Keywords: local, comfort, thermique, ventilation, internal environment

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19302 Pharmaceutical Evaluation of Five Different Generic Brands of Prednisolone

Authors: Asma A. Ben Ahmed, Hajer M. Alborawy, Alaa A. Mashina, Pradeep K. Velautham, Abdulmonem Gobassa, Emhemmed Elgallal, Mohamed N. El Attug

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Generic medicines are those where patent protection has expired, and which may be produced by manufacturers other than the innovator company. Use of generic medicines has been increasing in recent years, primarily as a cost saving measure in healthcare provision. Generic medicines are typically 20 – 90 % cheaper than originator equivalents. Physicians often continue to prescribe brand-name drugs to their patients even when less expensive pharmacologically equivalent generic drugs are available. Because generics are less expensive than their brand-name counterparts, the cost-savings to the patient is not the only factor that physicians consider when choosing between generic and brand-name drugs. Unfortunately Physicians in general and Libyan Physicians in particular tend to prescribe brand-name drugs, even without evidence of their therapeutic superiority, because neither they nor their insured patients bear these drugs’ increased cost with respect to generic substitutes. This study is to compare the quality of five different prednisolone tablets of the same strength from different companies under different trade names: Julphar, October pharma, Akums, Actavis, Pfizer compared them with pure prednisolone reference (BPCRS).

Keywords: quality control, pharmaceutical analysis, generic medicines, prednisolone

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19301 Sensitivity and Uncertainty Analysis of One Dimensional Shape Memory Alloy Constitutive Models

Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

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19300 Perceptions and Expectations by Participants of Monitoring and Evaluation Short Course Training Programmes in Africa

Authors: Mokgophana Ramasobana

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Background: At the core of the demand to utilize evidence-based approaches in the policy-making cycle, prioritization of limited financial resources and results driven initiatives is the urgency to develop a cohort of competent Monitoring and Evaluation (M&E) practitioners and public servants. The ongoing strides in the evaluation capacity building (ECB) initiatives are a direct response to produce the highly-sought after M&E skills. Notwithstanding the rapid growth of M&E short courses, participants perceived value and expectation of M&E short courses as a panacea for ECB have not been empirically quantified or measured. The objective of this article is to explicitly illustrate the importance of measuring ECB interventions and understanding what works in ECB and why it works. Objectives: This article illustrates the importance of establishing empirical ECB measurement tools to evaluate ECB interventions in order to ascertain its contribution to the broader evaluation practice. Method: The study was primarily a desktop review of existing literature, juxtaposed by a survey of the participants across the African continent based on the 43 M&E short courses hosted by the Centre for Learning on Evaluation and Results Anglophone Africa (CLEAR-AA) in collaboration with the Department of Planning Monitoring and Evaluation (DPME) Results: The article established that participants perceive short course training as a panacea to improve their M&E practical skill critical to executing their organizational duties. In tandem, participants are likely to demand customized training as opposed to general topics in Evaluation. However, the organizational environments constrain the application of the newly acquired skills. Conclusion: This article aims to contribute to the 'how to' measure ECB interventions discourse and contribute towards the improvement to evaluate ECB interventions. The study finds that participants prefer training courses with longer duration to cover more topics. At the same time, whilst organizations call for customization of programmes, the study found that individual participants demand knowledge of generic and popular evaluation topics.

Keywords: evaluation capacity building, effectiveness and training, monitoring and evaluation (M&E) short course training, perceptions and expectations

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19299 Measuring Environmental Efficiency of Energy in OPEC Countries

Authors: Bahram Fathi, Seyedhossein Sajadifar, Naser Khiabani

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Data envelopment analysis (DEA) has recently gained popularity in energy efficiency analysis. A common feature of the previously proposed DEA models for measuring energy efficiency performance is that they treat energy consumption as an input within a production framework without considering undesirable outputs. However, energy use results in the generation of undesirable outputs as byproducts of producing desirable outputs. Within a joint production framework of both desirable and undesirable outputs, this paper presents several DEA-type linear programming models for measuring energy efficiency performance. In addition to considering undesirable outputs, our models treat different energy sources as different inputs so that changes in energy mix could be accounted for in evaluating energy efficiency. The proposed models are applied to measure the energy efficiency performances of 12 OPEC countries and the results obtained are presented.

Keywords: energy efficiency, undesirable outputs, data envelopment analysis

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19298 Improvement in Oral Health-Related Quality of Life of Adult Patients After Rehabilitation With Partial Dentures: A Systematic Review and Meta-Analysis

Authors: Adama NS Bah

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Background: Loss of teeth has a negative influence on essential oral functions such as phonetics, mastication, and aesthetics. Dentists treat people with prosthodontic rehabilitation to recover essential oral functions. The oral health quality of life inventory reflects the success of prosthodontic rehabilitation. In many countries, the current conventional care delivered to replace missing teeth for adult patients involves the provision of removable partial dentures. Aim: The aim of this systematic review and meta-analysis is to gather the best available evidence to determine patients’ oral health-related quality of life improvement after treatment with partial dentures. Methods: We searched electronic databases from January 2010 to September 2019, including PubMed, ProQuest, Science Direct, Scopus and Google Scholar. In this paper, studies were included only if the average age was 30 years and above and also published in English. Two reviewers independently screened and selected all the references based on inclusion criteria using the PRISMA guideline, and assessed the quality of the included references using the Joanna Briggs Institute quality assessment tools. Data extracted were analyzed in RevMan 5.0 software, the heterogeneity between the studies was assessed using Forest plot, I2 statistics and chi-square test with a statistical P value less than 0.05 to indicate statistical significance. Random effect models were used in case of moderate or high heterogeneity. Four studies were included in the systematic review and three studies were pooled for meta-analysis. Results: Four studies included in the systematic review and three studies included in the meta-analysis with a total of 285 patients comparing the improvement in oral health-related quality of life before and after rehabilitation with partial denture, the pooled results showed a better improvement of oral health-related quality of life after treatment with partial dentures (mean difference 5.25; 95% CI [3.81, 6.68], p < 0.00001) favoring the wearing of partial dentures. In order to ascertain the reliability of the included studies for meta-analysis risk of bias was assessed and found to be low in all included studies for meta-analysis using the Cochrane collaboration tool for risk of bias assessment. Conclusion: There is high evidence that rehabilitation with partial dentures can improve the patient’s oral health-related quality of life measured with Oral Health Impact Profile 14. This review has clinical evidence value for dentists treating the expanding vulnerable adult population.

Keywords: meta-analysis, oral health impact profile, partial dentures, systematic review

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19297 Deciphering Information Quality: Unraveling the Impact of Information Distortion in the UK Aerospace Supply Chains

Authors: Jing Jin

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The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

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19296 Enhancing Model Interoperability and Reuse by Designing and Developing a Unified Metamodel Standard

Authors: Arash Gharibi

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Mankind has always used models to solve problems. Essentially, models are simplified versions of reality, whose need stems from having to deal with complexity; many processes or phenomena are too complex to be described completely. Thus a fundamental model requirement is that it contains the characteristic features that are essential in the context of the problem to be solved or described. Models are used in virtually every scientific domain to deal with various problems. During the recent decades, the number of models has increased exponentially. Publication of models as part of original research has traditionally been in in scientific periodicals, series, monographs, agency reports, national journals and laboratory reports. This makes it difficult for interested groups and communities to stay informed about the state-of-the-art. During the modeling process, many important decisions are made which impact the final form of the model. Without a record of these considerations, the final model remains ill-defined and open to varying interpretations. Unfortunately, the details of these considerations are often lost or in case there is any existing information about a model, it is likely to be written intuitively in different layouts and in different degrees of detail. In order to overcome these issues, different domains have attempted to implement their own approaches to preserve their models’ information in forms of model documentation. The most frequently cited model documentation approaches show that they are domain specific, not to applicable to the existing models and evolutionary flexibility and intrinsic corrections and improvements are not possible with the current approaches. These issues are all because of a lack of unified standards for model documentation. As a way forward, this research will propose a new standard for capturing and managing models’ information in a unified way so that interoperability and reusability of models become possible. This standard will also be evolutionary, meaning members of modeling realm could contribute to its ongoing developments and improvements. In this paper, the current 3 of the most common metamodels are reviewed and according to pros and cons of each, a new metamodel is proposed.

Keywords: metamodel, modeling, interoperability, reuse

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19295 Implied Adjusted Volatility by Leland Option Pricing Models: Evidence from Australian Index Options

Authors: Mimi Hafizah Abdullah, Hanani Farhah Harun, Nik Ruzni Nik Idris

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With the implied volatility as an important factor in financial decision-making, in particular in option pricing valuation, and also the given fact that the pricing biases of Leland option pricing models and the implied volatility structure for the options are related, this study considers examining the implied adjusted volatility smile patterns and term structures in the S&P/ASX 200 index options using the different Leland option pricing models. The examination of the implied adjusted volatility smiles and term structures in the Australian index options market covers the global financial crisis in the mid-2007. The implied adjusted volatility was found to escalate approximately triple the rate prior the crisis.

Keywords: implied adjusted volatility, financial crisis, Leland option pricing models, Australian index options

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19294 Thermodynamic Evaluation of Coupling APR-1400 with a Thermal Desalination Plant

Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

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Growing human populations have placed increased demands on water supplies and a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over the use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP which is the IAEA desalination program, it is approved to be capable of analyzing power generation systems coupled to desalination systems through various steam extraction positions, taking into consideration the isolation loop between the APR-1400 and the thermal desalination plant for safety concern.

Keywords: APR-1400, desalination, DE-TOP, IAEA, MSF, MED, MED-TVC, RO

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19293 Using 3D Satellite Imagery to Generate a High Precision Canopy Height Model

Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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19292 Transformation of Industrial Policy towards Industry 4.0 and Its Impact on Firms' Competition

Authors: Arūnas Burinskas

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Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

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19291 “Presently”: A Personal Trainer App to Self-Train and Improve Presentation Skills

Authors: Shyam Mehraaj, Samanthi E. R. Siriwardana, Shehara A. K. G. H., Wanigasinghe N. T., Wandana R. A. K., Wedage C. V.

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A presentation is a critical tool for conveying not just spoken information but also a wide spectrum of human emotions. The single most effective thing to make the presentation successful is to practice it beforehand. Preparing for a presentation has been shown to be essential for improving emotional control, intonation and prosody, pronunciation, and vocabulary, as well as the quality of the presentation slides. As a result, practicing has become one of the most critical parts of giving a good presentation. In this research, the main focus is to analyze the audio, video, and slides of the presentation uploaded by the presenters. This proposed solution is based on the Natural Language Processing and Computer Vision techniques to cater to the requirement for the presenter to do a presentation beforehand using a mobile responsive web application. The proposed system will assist in practicing the presentation beforehand by identifying the presenters’ emotions, body language, tonality, prosody, pronunciations and vocabulary, and presentation slides quality. Overall, the system will give a rating and feedback to the presenter about the performance so that the presenters’ can improve their presentation skills.

Keywords: presentation, self-evaluation, natural learning processing, computer vision

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19290 Leveraging Unannotated Data to Improve Question Answering for French Contract Analysis

Authors: Touila Ahmed, Elie Louis, Hamza Gharbi

Abstract:

State of the art question answering models have recently shown impressive performance especially in a zero-shot setting. This approach is particularly useful when confronted with a highly diverse domain such as the legal field, in which it is increasingly difficult to have a dataset covering every notion and concept. In this work, we propose a flexible generative question answering approach to contract analysis as well as a weakly supervised procedure to leverage unannotated data and boost our models’ performance in general, and their zero-shot performance in particular.

Keywords: question answering, contract analysis, zero-shot, natural language processing, generative models, self-supervision

Procedia PDF Downloads 194
19289 Dow Polyols near Infrared Chemometric Model Reduction Based on Clustering: Reducing Thirty Global Hydroxyl Number (OH) Models to Less Than Five

Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

Abstract:

Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

Procedia PDF Downloads 135
19288 Ecotoxicity Evaluation and Suggestion of Remediation Method of ZnO Nanoparticles in Aqueous Phase

Authors: Hyunsang Kim, Younghun Kim, Younghee Kim, Sangku Lee

Abstract:

We investigated ecotoxicity and performed an experiment for removing ZnO nanoparticles in water. Short-term exposure of hatching test using fertilized eggs (O. latipes) showed deformity in 5 ppm of ZnO nanoparticles solution, and in 10ppm ZnO nanoparticles solution delayed hatching was observed. Herein, chemical precipitation method was suggested for removing ZnO nanoparticles in water. The precipitated ZnO nanoparticles showed the form of ZnS after addition of Na2S, and the form of Zn3(PO4)2 for Na2HPO4. The removal efficiency of ZnO nanoparticles in water was closed to 100% for two case. In ecotoxicity evaluation of as-precipitated ZnS and Zn3(PO4)2, they did not cause any acute toxicity for D. magna. It is noted that this precipitation treatment of ZnO is effective to reduce the potential cytotoxicity.

Keywords: ZnO nanopraticles, ZnS, Zn3(PO4)2, ecotoxicity evaluation, chemical precipitation

Procedia PDF Downloads 278
19287 Towards Sustainable Concrete: Maturity Method to Evaluate the Effect of Curing Conditions on the Strength Development in Concrete Structures under Kuwait Environmental Conditions

Authors: F. Al-Fahad, J. Chakkamalayath, A. Al-Aibani

Abstract:

Conventional methods of determination of concrete strength under controlled laboratory conditions will not accurately represent the actual strength of concrete developed under site curing conditions. This difference in strength measurement will be more in the extreme environment in Kuwait as it is characterized by hot marine environment with normal temperature in summer exceeding 50°C accompanied by dry wind in desert areas and salt laden wind on marine and on shore areas. Therefore, it is required to have test methods to measure the in-place properties of concrete for quality assurance and for the development of durable concrete structures. The maturity method, which defines the strength of a given concrete mix as a function of its age and temperature history, is an approach for quality control for the production of sustainable and durable concrete structures. The unique harsh environmental conditions in Kuwait make it impractical to adopt experiences and empirical equations developed from the maturity methods in other countries. Concrete curing, especially in the early age plays an important role in developing and improving the strength of the structure. This paper investigates the use of maturity method to assess the effectiveness of three different types of curing methods on the compressive and flexural strength development of one high strength concrete mix of 60 MPa produced with silica fume. This maturity approach was used to predict accurately, the concrete compressive and flexural strength at later ages under different curing conditions. Maturity curves were developed for compressive and flexure strengths for a commonly used concrete mix in Kuwait, which was cured using three different curing conditions, including water curing, external spray coating and the use of internal curing compound during concrete mixing. It was observed that the maturity curve developed for the same mix depends on the type of curing conditions. It can be used to predict the concrete strength under different exposure and curing conditions. This study showed that concrete curing with external spray curing method cannot be recommended to use as it failed to aid concrete in reaching accepted values of strength, especially for flexural strength. Using internal curing compound lead to accepted levels of strength when compared with water cuing. Utilization of the developed maturity curves will help contactors and engineers to determine the in-place concrete strength at any time, and under different curing conditions. This will help in deciding the appropriate time to remove the formwork. The reduction in construction time and cost has positive impacts towards sustainable construction.

Keywords: curing, durability, maturity, strength

Procedia PDF Downloads 304
19286 Text Similarity in Vector Space Models: A Comparative Study

Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

Abstract:

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

Procedia PDF Downloads 175
19285 Modeling Geogenic Groundwater Contamination Risk with the Groundwater Assessment Platform (GAP)

Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

Abstract:

One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

Procedia PDF Downloads 348
19284 Implementing Total Quality Management in Higher Education

Authors: Abbos Utkirov

Abstract:

Total Quality Management (TQM) in the context of educational institutions requires careful planning and the implementation of an annual quality program to achieve its vision effectively. By applying TQM concepts, the higher education system can experience significant improvements. This study aims to examine TQM in higher education, focusing on Critical Success Factors (CSF) and their implementation across all areas. The study ultimately concludes that CSF and their execution play a crucial role in higher education institutions. Some institutions have already benefited from TQM methods by dedicating themselves to the system and using it to achieve their objectives. Through this review, recent studies shed light on how the TQM system can employ various strategies and hypotheses to empower employees, foster a positive and supportive environment, and emphasize the importance of enabling students to unleash their full potential.

Keywords: total quality management (TQM), critical success factor (CSF), organizational performance, quality management practices

Procedia PDF Downloads 89
19283 Keyframe Extraction Using Face Quality Assessment and Convolution Neural Network

Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

Abstract:

Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

Procedia PDF Downloads 233
19282 An Investigation of Food Quality and Risks in Thailand: A Case of Inbound Senior Tourists

Authors: Kevin Wongleedee

Abstract:

Food quality and risks are major concerns for inbound senior tourists when visiting tourist destinations in Thailand. The purposes of this study were to investigate food quality and risks perceived by inbound senior tourists. This paper drew upon data collection from an inbound senior tourist survey conducted in Thailand during summer 2013. Summer time in Thailand is a high season for inbound tourists. It is also a high risk period in which a variety food safety issues and incidents have often occurred. The survey was structured primarily to obtain inbound senior tourists’ concerns toward a variety of food quality and risks they encountered during their trip in Thailand. A total of 400 inbound senior tourists were elicited as data input for mean and standard deviation. The findings revealed that inbound tourists rated the overall food quality at a high level and the three most important perceived food risks were 1) unclean physical cooking facility, 2) toxic chemical handling, and 3) unclean water.

Keywords: food quality, inbound senior tourists, risks, Thailand

Procedia PDF Downloads 397
19281 Automated Process Quality Monitoring and Diagnostics for Large-Scale Measurement Data

Authors: Hyun-Woo Cho

Abstract:

Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

Procedia PDF Downloads 401